EERAdata Wiki - User contributions [en]

Timeline

2023-01-05T09:01:54Z

Valerias: /* November */

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 3rd policy brief "Realising a humancentred digitalisation of the energy sector" published
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 14th Discussion with A. el Gammal, preparation of [https://www.sintef.no/en/events/why-modelling-and-data-sharing-is-crucial-in-the-global-energy-transition/ presentation]
* 15th 3rd project meeting StoRIES, Almeria
* 21st Answering questionnaire in [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronization event]
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd EB meeting
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 5th platform meeting with AIT
* 12th platform meeting with AIT
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding
* 15th [https://eurec.be/event/online-seminar-digitalisation-of-the-energy-system/ EUREC Webinar Digitalization of the Energy System]

== Year 2023 ==

=== January ===

* 9th Preparation meeting educational material and platform
* 13th preparation meeting for 6. workshop
* 20th EB meeting

=== February ===

* 21st - 23rd 6. workshop (Bergen)

Timeline

2023-01-05T08:21:46Z

Valerias:

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 14th Discussion with A. el Gammal, preparation of [https://www.sintef.no/en/events/why-modelling-and-data-sharing-is-crucial-in-the-global-energy-transition/ presentation]
* 15th 3rd project meeting StoRIES, Almeria
* 21st Answering questionnaire in [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronization event]
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd EB meeting
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 5th platform meeting with AIT
* 12th platform meeting with AIT
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding
* 15th [https://eurec.be/event/online-seminar-digitalisation-of-the-energy-system/ EUREC Webinar Digitalization of the Energy System]

== Year 2023 ==

=== January ===

* 9th Preparation meeting educational material and platform
* 13th preparation meeting for 6. workshop
* 20th EB meeting

=== February ===

* 21st - 23rd 6. workshop (Bergen)

Timeline

2022-12-19T11:18:56Z

Valerias: /* December */

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 14th Discussion with A. el Gammal, preparation of [https://www.sintef.no/en/events/why-modelling-and-data-sharing-is-crucial-in-the-global-energy-transition/ presentation]
* 15th 3rd project meeting StoRIES, Almeria
* 21st Answering questionnaire in [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronization event]
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd EB meeting
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 5th platform meeting with AIT
* 12th platform meeting with AIT
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding
* 15th [https://eurec.be/event/online-seminar-digitalisation-of-the-energy-system/ EUREC Webinar Digitalization of the Energy System]

Timeline

2022-11-22T18:04:07Z

Valerias: /* November */

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 14th Discussion with A. el Gammal, preparation of [https://www.sintef.no/en/events/why-modelling-and-data-sharing-is-crucial-in-the-global-energy-transition/ presentation]
* 15th 3rd project meeting StoRIES, Almeria
* 21st Answering questionnaire in [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronization event]
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd EB meeting
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 5th platform meeting with AIT
* 12th platform meeting with AIT
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding
* 19th platform meeting with AIT

Timeline

2022-11-19T08:45:14Z

Valerias: /* November */

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 14th Discussion with A. el Gammal, preparation of [https://www.sintef.no/en/events/why-modelling-and-data-sharing-is-crucial-in-the-global-energy-transition/ presentation]
* 15th 3rd project meeting StoRIES, Almeria
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd EB meeting
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 5th platform meeting with AIT
* 12th platform meeting with AIT
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding
* 19th platform meeting with AIT

Timeline

2022-11-18T11:18:05Z

Valerias: /* November */

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 14th Discussion with A. el Gammal, preparation of presentation
* 15th 3rd project meeting StoRIES, Almeria
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd EB meeting
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 5th platform meeting with AIT
* 12th platform meeting with AIT
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding
* 19th platform meeting with AIT

Contents for analysing data

2022-11-17T15:11:55Z

Valerias:

Contents for analysing data

2022-11-17T14:29:25Z

Valerias:

Contents for analysing data

2022-11-17T14:26:46Z

Valerias:

Contents for analysing data

2022-11-17T14:25:23Z

Valerias:

Contents for analysing data

2022-11-17T14:21:36Z

Valerias:

A proper understanding of the data is essential for carrying out any FAIRification activity. If the data are own data or coming from an in-house activity, such an understanding may come easily. But if the data are provided by a third party, a detailed analysis might be necessary. To name a few examples, such an analysis involves:

This step analyses the data to support the FAIRification step:

*

* Are already some FAIR features already are existing in the data such as persistent identifiers. If the data are extensive, running a (semi-) automatic FAIR assessmen

The second step is to analyze the data to prepare for subsequent FAIRification (e.g., improving
interoperability) and is within the pre-FAIRification phase of the workflow. This process may include:
1) investigating the data in whatever form(s) it is available (specified in Step 1) and checking whether
both the data representation (format) and the meaning of the data elements (the data semantics) are clear
and unambiguous, and 2) checking whether the data already contain FAIR features, such as persistent
unique identifiers for data elements [14] (FAIR principle F1 [1]) by e.g., using FAIRness assessment tooling
[2, 3, 4]. It is evident that this step is tightly connected with Step 1 since e.g., selecting a relevant subset
of the data and defining driving user questions(s) are highly relying on being familiar with the data.

Contents for analysing data

2022-11-17T11:15:43Z

Valerias:

A proper understanding of the data is essential for carrying out any FAIRification activity. If the data are own data or coming from an in-house activity, such an understanding may come easily. But if the data are provided by a third party, a detailed analysis might be necessary. To name a few examples, such an analysis involves:

This step analyses the data to support the

* Are already some FAIR features already are existing in the data such as persistent identifiers. If the data are extensive, running a (semi-) automatic FAIR assessmen

The second step is to analyze the data to prepare for subsequent FAIRification (e.g., improving
interoperability) and is within the pre-FAIRification phase of the workflow. This process may include:
1) investigating the data in whatever form(s) it is available (specified in Step 1) and checking whether
both the data representation (format) and the meaning of the data elements (the data semantics) are clear
and unambiguous, and 2) checking whether the data already contain FAIR features, such as persistent
unique identifiers for data elements [14] (FAIR principle F1 [1]) by e.g., using FAIRness assessment tooling
[2, 3, 4]. It is evident that this step is tightly connected with Step 1 since e.g., selecting a relevant subset
of the data and defining driving user questions(s) are highly relying on being familiar with the data.

Contents for analysing data

2022-11-17T11:08:09Z

Valerias:

A proper understanding of the data is an essential

This step analyses the data to support the

As a preparation of the FAIRification itself, this step also includes checking if some FAIR features already
are existing in the data such as persistent identifiers. If the data are extensive, running

The second step is to analyze the data to prepare for subsequent FAIRification (e.g., improving
interoperability) and is within the pre-FAIRification phase of the workflow. This process may include:
1) investigating the data in whatever form(s) it is available (specified in Step 1) and checking whether
both the data representation (format) and the meaning of the data elements (the data semantics) are clear
and unambiguous, and 2) checking whether the data already contain FAIR features, such as persistent
unique identifiers for data elements [14] (FAIR principle F1 [1]) by e.g., using FAIRness assessment tooling
[2, 3, 4]. It is evident that this step is tightly connected with Step 1 since e.g., selecting a relevant subset
of the data and defining driving user questions(s) are highly relying on being familiar with the data.

Contents for analysing data

2022-11-17T10:56:31Z

Valerias: Created page with "This step analyses the data to support the As a preparation of the FAIRification itself, this step also includes checking if some FAIR features already are existing in the..."

This step analyses the data to support the

As a preparation of the FAIRification itself, this step also includes checking if some FAIR features already
are existing in the data such as persistent identifiers. If the data are extensive, running

The second step is to analyze the data to prepare for subsequent FAIRification (e.g., improving
interoperability) and is within the pre-FAIRification phase of the workflow. This process may include:
1) investigating the data in whatever form(s) it is available (specified in Step 1) and checking whether
both the data representation (format) and the meaning of the data elements (the data semantics) are clear
and unambiguous, and 2) checking whether the data already contain FAIR features, such as persistent
unique identifiers for data elements [14] (FAIR principle F1 [1]) by e.g., using FAIRness assessment tooling
[2, 3, 4]. It is evident that this step is tightly connected with Step 1 since e.g., selecting a relevant subset
of the data and defining driving user questions(s) are highly relying on being familiar with the data.

Contents for analysing metadata

2022-11-17T09:59:00Z

Valerias: /* The quality of metadata */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed [https://rd-alliance.github.io/metadata-directory/standards/ here].

== The quality of metadata ==
Part of analyzing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by [https://ecommons.cornell.edu/handle/1813/7895 Bruce and Hillman] which proposes completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness, and provenance as quality criteria. A shorter list of has been proposed by [https://dcpapers.dublincore.org/pubs/article/view/923 Margaritopoulos et al.]. Still, operationalizing these terms to assess the quality may result in a substantial number of sub-categories.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

[https://www.cambridge.org/core/books/metadata-for-information-management-and-retrieval/FBDE16B5739A32A6C8D9E56A38AE8223 D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.]

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [https://blog.scholasticahq.com/post/metadata-2020-improve-quality-of-metadata/ Interview - Metadata 2020 working to improve the quality of metadata for research]

* [https://dl.acm.org/doi/10.1145/2964909 Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [https://www.earthdata.nasa.gov/unified-metadata-model-umm Website - EOSDIS Unified Metadata Model]

* [https://link.springer.com/chapter/10.1007/978-3-319-24592-8_5 Article - Measuring Quality in Metadata Repositories]

* [https://link.springer.com/chapter/10.1007/978-3-319-03437-9_11 Tools and Techniques for Assessing Metadata Quality]

* [https://www.cmswire.com/digital-asset-management/what-makes-a-good-metadata-schema/ Opinion piece - Metadata schema design]

* [https://www.sciencedirect.com/science/article/abs/pii/S0306457313000526 Article - Dealing with metadata quality: The legacy of digital library efforts]

* [https://www.tandfonline.com/doi/full/10.1080/07317131.2020.1810443 Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [https://link.springer.com/article/10.1007/s00799-020-00279-3 An analysis and comparison of keyword recommendation methods for scientific data]

* [http://c2metadata.mtna.us/ Website - C2Metadata, continuous capture of metadata]

* [https://www.semanticscholar.org/paper/Scenario-based-Metadata-Design-for-Open-Data-User-Liang/fa355d6bba404dd6fed699e7f7f90e6d3fa15cd5 Article - Scenario-based Metadata Design for Open Data User Interaction]

* [https://link.springer.com/article/10.1007/s13740-018-0091-5 Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T09:50:06Z

Valerias: /* Further reading */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed [https://rd-alliance.github.io/metadata-directory/standards/ here].

== The quality of metadata ==
Part of analyzing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by [https://ecommons.cornell.edu/handle/1813/7895 Bruce and Hillman] which proposes completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness, and provenance as quality criteria. A shorter list of has been proposed by [Margaritopoulos et al.]. Still, operationalizing these terms to assess the quality may result in a substantial number of sub-categories.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

[https://www.cambridge.org/core/books/metadata-for-information-management-and-retrieval/FBDE16B5739A32A6C8D9E56A38AE8223 D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.]

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [https://blog.scholasticahq.com/post/metadata-2020-improve-quality-of-metadata/ Interview - Metadata 2020 working to improve the quality of metadata for research]

* [https://dl.acm.org/doi/10.1145/2964909 Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [https://www.earthdata.nasa.gov/unified-metadata-model-umm Website - EOSDIS Unified Metadata Model]

* [https://link.springer.com/chapter/10.1007/978-3-319-24592-8_5 Article - Measuring Quality in Metadata Repositories]

* [https://link.springer.com/chapter/10.1007/978-3-319-03437-9_11 Tools and Techniques for Assessing Metadata Quality]

* [https://www.cmswire.com/digital-asset-management/what-makes-a-good-metadata-schema/ Opinion piece - Metadata schema design]

* [https://www.sciencedirect.com/science/article/abs/pii/S0306457313000526 Article - Dealing with metadata quality: The legacy of digital library efforts]

* [https://www.tandfonline.com/doi/full/10.1080/07317131.2020.1810443 Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [https://link.springer.com/article/10.1007/s00799-020-00279-3 An analysis and comparison of keyword recommendation methods for scientific data]

* [http://c2metadata.mtna.us/ Website - C2Metadata, continuous capture of metadata]

* [https://www.semanticscholar.org/paper/Scenario-based-Metadata-Design-for-Open-Data-User-Liang/fa355d6bba404dd6fed699e7f7f90e6d3fa15cd5 Article - Scenario-based Metadata Design for Open Data User Interaction]

* [https://link.springer.com/article/10.1007/s13740-018-0091-5 Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T09:46:54Z

Valerias: /* Further reading */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed [https://rd-alliance.github.io/metadata-directory/standards/ here].

== The quality of metadata ==
Part of analyzing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by [https://ecommons.cornell.edu/handle/1813/7895 Bruce and Hillman] which proposes completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness, and provenance as quality criteria. A shorter list of has been proposed by [Margaritopoulos et al.]. Still, operationalizing these terms to assess the quality may result in a substantial number of sub-categories.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [https://blog.scholasticahq.com/post/metadata-2020-improve-quality-of-metadata/ Interview - Metadata 2020 working to improve the quality of metadata for research]

* [https://dl.acm.org/doi/10.1145/2964909 Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [https://www.earthdata.nasa.gov/unified-metadata-model-umm Website - EOSDIS Unified Metadata Model]

* [https://link.springer.com/chapter/10.1007/978-3-319-24592-8_5 Article - Measuring Quality in Metadata Repositories]

* [https://link.springer.com/chapter/10.1007/978-3-319-03437-9_11 Tools and Techniques for Assessing Metadata Quality]

* [https://www.cmswire.com/digital-asset-management/what-makes-a-good-metadata-schema/ Opinion piece - Metadata schema design]

* [https://www.sciencedirect.com/science/article/abs/pii/S0306457313000526 Article - Dealing with metadata quality: The legacy of digital library efforts]

* [https://www.tandfonline.com/doi/full/10.1080/07317131.2020.1810443 Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [https://link.springer.com/article/10.1007/s00799-020-00279-3 An analysis and comparison of keyword recommendation methods for scientific data]

* [http://c2metadata.mtna.us/ Website - C2Metadata, continuous capture of metadata]

* [https://www.semanticscholar.org/paper/Scenario-based-Metadata-Design-for-Open-Data-User-Liang/fa355d6bba404dd6fed699e7f7f90e6d3fa15cd5 Article - Scenario-based Metadata Design for Open Data User Interaction]

* [https://link.springer.com/article/10.1007/s13740-018-0091-5 Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T08:53:53Z

Valerias: /* The quality of metadata */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed [https://rd-alliance.github.io/metadata-directory/standards/ here].

== The quality of metadata ==
Part of analyzing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by [https://ecommons.cornell.edu/handle/1813/7895 Bruce and Hillman] which proposes completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness, and provenance as quality criteria. A shorter list of has been proposed by [Margaritopoulos et al.]. Still, operationalizing these terms to assess the quality may result in a substantial number of sub-categories.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [https://blog.scholasticahq.com/post/metadata-2020-improve-quality-of-metadata/ Interview - Metadata 2020 working to improve the quality of metadata for research]

* [https://dl.acm.org/doi/10.1145/2964909 Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [https://www.earthdata.nasa.gov/unified-metadata-model-umm Website - EOSDIS Unified Metadata Model]

* [https://link.springer.com/chapter/10.1007/978-3-319-24592-8_5 Article - Measuring Quality in Metadata Repositories]

* [https://link.springer.com/chapter/10.1007/978-3-319-03437-9_11 Tools and Techniques for Assessing Metadata Quality]

* [https://www.cmswire.com/digital-asset-management/what-makes-a-good-metadata-schema/ Opinion piece - Metadata schema design]

* [https://www.sciencedirect.com/science/article/abs/pii/S0306457313000526 Article - Dealing with metadata quality: The legacy of digital library efforts]

* [https://www.tandfonline.com/doi/full/10.1080/07317131.2020.1810443 Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [https://link.springer.com/article/10.1007/s00799-020-00279-3 An analysis and comparison of keyword recommendation methods for scientific data]

* [http://c2metadata.mtna.us/ Website - C2Metadata, continuous capture of metadata]

* [Article - Scenario-based Metadata Design for Open Data User Interaction]

* [Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T08:49:13Z

Valerias: /* The quality of metadata */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed [https://rd-alliance.github.io/metadata-directory/standards/ here].

== The quality of metadata ==
Part of analyzing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by [Bruce and Hillman] which proposes completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness, and provenance as quality criteria. A shorter list of has been proposed by [Margaritopoulos et al.]. Still, operationalizing these terms to assess the quality may result in a substantial number of sub-categories.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [https://blog.scholasticahq.com/post/metadata-2020-improve-quality-of-metadata/ Interview - Metadata 2020 working to improve the quality of metadata for research]

* [https://dl.acm.org/doi/10.1145/2964909 Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [https://www.earthdata.nasa.gov/unified-metadata-model-umm Website - EOSDIS Unified Metadata Model]

* [https://link.springer.com/chapter/10.1007/978-3-319-24592-8_5 Article - Measuring Quality in Metadata Repositories]

* [https://link.springer.com/chapter/10.1007/978-3-319-03437-9_11 Tools and Techniques for Assessing Metadata Quality]

* [https://www.cmswire.com/digital-asset-management/what-makes-a-good-metadata-schema/ Opinion piece - Metadata schema design]

* [https://www.sciencedirect.com/science/article/abs/pii/S0306457313000526 Article - Dealing with metadata quality: The legacy of digital library efforts]

* [https://www.tandfonline.com/doi/full/10.1080/07317131.2020.1810443 Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [https://link.springer.com/article/10.1007/s00799-020-00279-3 An analysis and comparison of keyword recommendation methods for scientific data]

* [http://c2metadata.mtna.us/ Website - C2Metadata, continuous capture of metadata]

* [Article - Scenario-based Metadata Design for Open Data User Interaction]

* [Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T08:38:41Z

Valerias: /* Further reading */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed [https://rd-alliance.github.io/metadata-directory/standards/ here].

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [https://blog.scholasticahq.com/post/metadata-2020-improve-quality-of-metadata/ Interview - Metadata 2020 working to improve the quality of metadata for research]

* [https://dl.acm.org/doi/10.1145/2964909 Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [https://www.earthdata.nasa.gov/unified-metadata-model-umm Website - EOSDIS Unified Metadata Model]

* [https://link.springer.com/chapter/10.1007/978-3-319-24592-8_5 Article - Measuring Quality in Metadata Repositories]

* [https://link.springer.com/chapter/10.1007/978-3-319-03437-9_11 Tools and Techniques for Assessing Metadata Quality]

* [https://www.cmswire.com/digital-asset-management/what-makes-a-good-metadata-schema/ Opinion piece - Metadata schema design]

* [https://www.sciencedirect.com/science/article/abs/pii/S0306457313000526 Article - Dealing with metadata quality: The legacy of digital library efforts]

* [https://www.tandfonline.com/doi/full/10.1080/07317131.2020.1810443 Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [https://link.springer.com/article/10.1007/s00799-020-00279-3 An analysis and comparison of keyword recommendation methods for scientific data]

* [http://c2metadata.mtna.us/ Website - C2Metadata, continuous capture of metadata]

* [Article - Scenario-based Metadata Design for Open Data User Interaction]

* [Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T08:34:36Z

Valerias: /* Further reading */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed [https://rd-alliance.github.io/metadata-directory/standards/ here].

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [https://blog.scholasticahq.com/post/metadata-2020-improve-quality-of-metadata/ Interview - Metadata 2020 working to improve the quality of metadata for research]

* [https://dl.acm.org/doi/10.1145/2964909 Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [https://www.earthdata.nasa.gov/unified-metadata-model-umm Website - EOSDIS Unified Metadata Model]

* [https://link.springer.com/chapter/10.1007/978-3-319-24592-8_5 Article - Measuring Quality in Metadata Repositories]

* [https://link.springer.com/chapter/10.1007/978-3-319-03437-9_11 Tools and Techniques for Assessing Metadata Quality]

* [Opinion piece - Metadata schema design]

* [Article - Dealing with metadata quality: The legacy of digital library efforts]

* [Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [An analysis and comparison of keyword recommendation methods for scientific data]

* [Website - C2Metadata, continuous capture of metadata]

* [Article - Scenario-based Metadata Design for Open Data User Interaction]

* [Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T08:30:48Z

Valerias: /* Using metadata standards to compile relevant metadata */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed [https://rd-alliance.github.io/metadata-directory/standards/ here].

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [Interview - Metadata 2020 working to improve the quality of metadata for research]

* [Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [Website - EOSDIS Unified Metadata Model]

* [Article - Measuring Quality in Metadata Repositories]

* [Tools and Techniques for Assessing Metadata Quality]

* [Opinion piece - Metadata schema design]

* [Article - Dealing with metadata quality: The legacy of digital library efforts]

* [Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [An analysis and comparison of keyword recommendation methods for scientific data]

* [Website - C2Metadata, continuous capture of metadata]

* [Article - Scenario-based Metadata Design for Open Data User Interaction]

* [Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T08:29:04Z

Valerias: /* Further reading */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed here.

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

* [https://doi.org/10.3390/en14206692 Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories]

* [https://metadata2020.org/ Website - Metadata 2020 project]

* [Interview - Metadata 2020 working to improve the quality of metadata for research]

* [Article - Automated Quality Assessment of Metadata across Open Data Portals]

* [Website - EOSDIS Unified Metadata Model]

* [Article - Measuring Quality in Metadata Repositories]

* [Tools and Techniques for Assessing Metadata Quality]

* [Opinion piece - Metadata schema design]

* [Article - Dealing with metadata quality: The legacy of digital library efforts]

* [Article - Rethinking Metadata’s Value and How It Is Evaluated]

* [An analysis and comparison of keyword recommendation methods for scientific data]

* [Website - C2Metadata, continuous capture of metadata]

* [Article - Scenario-based Metadata Design for Open Data User Interaction]

* [Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal]

Contents for analysing metadata

2022-11-17T08:24:35Z

Valerias: /* Further reading */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed here.

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) [https://doi.org/10.3390/en14206692 https://doi.org/10.3390/en14206692]

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories
Website - Metadata 2020 project
Interview - Metadata 2020 working to improve the quality of metadata for research
Article - Automated Quality Assessment of Metadata across Open Data Portals
Website - EOSDIS Unified Metadata Model
Article - Measuring Quality in Metadata Repositories
Tools and Techniques for Assessing Metadata Quality
Opinion piece - Metadata schema design
Article - Dealing with metadata quality: The legacy of digital library efforts
Article - Rethinking Metadata’s Value and How It Is Evaluated
An analysis and comparison of keyword recommendation methods for scientific data
Website - C2Metadata, continuous capture of metadata
Article - Scenario-based Metadata Design for Open Data User Interaction
Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

Contents for analysing metadata

2022-11-17T08:23:21Z

Valerias: /* Using metadata standards to compile relevant metadata */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ Dublin core] offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed here.

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) doi

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories
Website - Metadata 2020 project
Interview - Metadata 2020 working to improve the quality of metadata for research
Article - Automated Quality Assessment of Metadata across Open Data Portals
Website - EOSDIS Unified Metadata Model
Article - Measuring Quality in Metadata Repositories
Tools and Techniques for Assessing Metadata Quality
Opinion piece - Metadata schema design
Article - Dealing with metadata quality: The legacy of digital library efforts
Article - Rethinking Metadata’s Value and How It Is Evaluated
An analysis and comparison of keyword recommendation methods for scientific data
Website - C2Metadata, continuous capture of metadata
Article - Scenario-based Metadata Design for Open Data User Interaction
Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

Contents for analysing metadata

2022-11-17T08:22:09Z

Valerias: /* Categorizing metadata to identify relevant metadata */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, or a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee the reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the one provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describes the data by title, author, creation date, etc. but also provides some content information.

* Structural metadata explains how the data is organized e.g. if several tables of data are present or if you have pages bounded together to form a book.

* Administrative metadata may be added to the data during its whole lifetime to track what is happening to the data, e.g. several sets of data compiled into a new dataset, and so on.

* Statistical metadata may be added to the data for e.g. keeping track of access statistics.

* Legal metadata may record information on licenses and copyright and maybe state access restrictions to the data.

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, Dublin core offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed here.

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) doi

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories
Website - Metadata 2020 project
Interview - Metadata 2020 working to improve the quality of metadata for research
Article - Automated Quality Assessment of Metadata across Open Data Portals
Website - EOSDIS Unified Metadata Model
Article - Measuring Quality in Metadata Repositories
Tools and Techniques for Assessing Metadata Quality
Opinion piece - Metadata schema design
Article - Dealing with metadata quality: The legacy of digital library efforts
Article - Rethinking Metadata’s Value and How It Is Evaluated
An analysis and comparison of keyword recommendation methods for scientific data
Website - C2Metadata, continuous capture of metadata
Article - Scenario-based Metadata Design for Open Data User Interaction
Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

Contents for analysing metadata

2022-11-17T08:12:48Z

Valerias: /* Categorizing metadata to identify relevant metadata */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

Another helpful categorization is the provided by [https://en.wikipedia.org/wiki/Metadata wikipedia] classifying metadata as

* Descriptive metadata that describe the data by a title, author, format statements, etc. but also provides some content information.

*

*

*

*

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, Dublin core offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed here.

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) doi

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories
Website - Metadata 2020 project
Interview - Metadata 2020 working to improve the quality of metadata for research
Article - Automated Quality Assessment of Metadata across Open Data Portals
Website - EOSDIS Unified Metadata Model
Article - Measuring Quality in Metadata Repositories
Tools and Techniques for Assessing Metadata Quality
Opinion piece - Metadata schema design
Article - Dealing with metadata quality: The legacy of digital library efforts
Article - Rethinking Metadata’s Value and How It Is Evaluated
An analysis and comparison of keyword recommendation methods for scientific data
Website - C2Metadata, continuous capture of metadata
Article - Scenario-based Metadata Design for Open Data User Interaction
Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

Contents for analysing metadata

2022-11-17T08:08:59Z

Valerias:

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata is information added to the data to increase its functionality. Adding information may occur during the creation but also during the whole lifecycle of the dataset. In the research context, metadata is often used to capture the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow and is closely tight to ensure proper scientific practices such as traceability, reproducibility, and transparency.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point for own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyze and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust, channel results to decision-makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries that inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, test, and validate software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, the purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but are modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allows us to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issue in scientific as well as industrial use of data. Metadata is used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, Dublin core offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed here.

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) doi

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories
Website - Metadata 2020 project
Interview - Metadata 2020 working to improve the quality of metadata for research
Article - Automated Quality Assessment of Metadata across Open Data Portals
Website - EOSDIS Unified Metadata Model
Article - Measuring Quality in Metadata Repositories
Tools and Techniques for Assessing Metadata Quality
Opinion piece - Metadata schema design
Article - Dealing with metadata quality: The legacy of digital library efforts
Article - Rethinking Metadata’s Value and How It Is Evaluated
An analysis and comparison of keyword recommendation methods for scientific data
Website - C2Metadata, continuous capture of metadata
Article - Scenario-based Metadata Design for Open Data User Interaction
Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

Contents for analysing metadata

2022-11-16T18:23:36Z

Valerias: /* Metadata and stakeholder identification */

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata captures the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point of own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyse and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust,channel results to decision makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries who inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
* General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, tests, and validates software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but a modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allow to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issues in scientific as well as industrial use of data. Metadata are used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, Dublin core offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed here.

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) doi

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories
Website - Metadata 2020 project
Interview - Metadata 2020 working to improve the quality of metadata for research
Article - Automated Quality Assessment of Metadata across Open Data Portals
Website - EOSDIS Unified Metadata Model
Article - Measuring Quality in Metadata Repositories
Tools and Techniques for Assessing Metadata Quality
Opinion piece - Metadata schema design
Article - Dealing with metadata quality: The legacy of digital library efforts
Article - Rethinking Metadata’s Value and How It Is Evaluated
An analysis and comparison of keyword recommendation methods for scientific data
Website - C2Metadata, continuous capture of metadata
Article - Scenario-based Metadata Design for Open Data User Interaction
Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

Contents for analysing metadata

2022-11-16T18:23:19Z

Valerias: Created page with "While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata captures the context of data. This means, that all necessa..."

While there is the ubiquitous statement that metadata is data about data, a more helpful definition is that metadata captures the context of data. This means, that all necessary information for understanding the data is described by metadata. For sharing data, metadata serves the purpose for provide this extra information so that someone else is able to work with the data given his or her own background of knowledge. But even if the data is not shared with someone else, metadata documents all relevant information so that at a later point in time the data can be used as easily as during the day of its creation. So, metadata has an important function in the scientific workflow.

== Metadata and stakeholder identification ==
As metadata serves the purpose of communicating information about data between its users, the type and extent of this information naturally has to consider the background of all future stakeholders of this data. The step of "analysing metadata" therefore starts with identifying the future users of the data and envisioning what they may want to do with the data. In the context of low-carbon research data, this e.g. includes:

* Researchers who what to use the data as a starting point of own research activities. Energy domain experts create data from scratch, re-use existing data to curate, aggregate, analyse and publish data. Interdisciplinary scientists inform themselves on (other) expert knowledge, re-use data, aggregate and analyze data, and publish data.
* Science funders of energy R&D activities who inform themselves of the results of funded research and projects. They need the data to monitor and adjust,channel results to decision makers, and plan funding policies and principles to better direct.
* Planners and decision-makers themselves on expert knowledge. They may re-use data, analyze some data, and publish aggregated data and decisions.
* Energy and other industries who inform themselves on expert knowledge and re-use and analyze some data on all aggregation levels.
General public who informs itself to adjust behavior and practices (e.g., energy consumption behavior, voting in elections, engagement as prosumers, activists or citizen-scientists).
* Data scientists who group codes, tests, and validates software with existing data.
* Publishers, librarians, and data curators publish, store, and archive research data. They may re-use data to link them to metrics such as access statistics and to cross-reference.

== Categorizing metadata to identify relevant metadata ==
It is hard to come up with a methodology to ensure an exhaustive recording of all required metadata. In fact, it might be impossible to capture all relevant information and envision all possible future uses for the data. Still, the use of categories and purposes of metadata is helpful to identify necessary information which needs to be collected and recorded. Following Haynes 2018, purposes of metadata include

* Resource description: identify the data e.g. by a DOI or similar identifier and specify properties such as the title, creator, contributor etc.

*Resource discovery: metadata to find the information contained in the data, this might be keywords describing the data or format information about the data.

* Administration and management of resources: In many cases, data are not simply created and stay unchanged but a modified, aggregated or selected during the research. They might be downloaded to a secondary place, incorporated into new resources and so on. Metadata allow to track these changes along the scientific workflow.

* Record of intellectual property rights: Keeping track of license information is an important issues in scientific as well as industrial use of data. Metadata are used to document ownership rights.

* Documenting software and hardware environments: Often, data are created as a result of specific conditions. A specific instrument might be used to record the data, a specific software involved in generating it. Typically, it is crucial to keep this information to understand what the data is about and to guarantee reproducibility of the scientific findings.

* Preservation management of digital resources
* Providing information on context and authenticity

== Using metadata standards to compile relevant metadata ==
Another help in collecting relevant information is the use of metadata standards. There is a whole zoo of suggested standards to be used. Some are created with a broad focus catering many resources and domains. Other standards rather cater specific forms of data, e.g. audio or video data or domain such as engineering, humanities etc. An example of a rather general metadata standard is the Dublin core set of metadata terms. In its basic form, Dublin core offers the following terms to describe a resource: contributor, coverage, creator, date, description, format, identifier, language, publisher, relation, rights, source, subject, title, and type. A list of different metadata standards is listed here.

== The quality of metadata ==
Part of analysing meta is also to assess the quality of metadata. Various quality criteria have been suggested. An example is the framework developed by Bruce and Hillman which propose completeness, accuracy, conformance to expectations, logical consistency and coherence, accessibility, timeliness and provenance as quality criteria.

== Example ==
As a simple example example, consider a csv file created in the context of collecting information on power plants owned by citizen-led initiatives.

== Further reading ==
A good starting point for understanding the metadata creation process specific for the low-carbon energy domain is this publication

A. Wierling et al. Advancing FAIR metadata standards for low carbon energy research. Energies 14, 6692 (2021) doi

Other helpful resources are

D. Haynes. Metadata for Information Management and Retrieval. Facet Publishing, London, 2018.

Further interesting articles are

Article - Metadata for Big Data: A preliminary investigation of metadata quality issues in research data repositories
Website - Metadata 2020 project
Interview - Metadata 2020 working to improve the quality of metadata for research
Article - Automated Quality Assessment of Metadata across Open Data Portals
Website - EOSDIS Unified Metadata Model
Article - Measuring Quality in Metadata Repositories
Tools and Techniques for Assessing Metadata Quality
Opinion piece - Metadata schema design
Article - Dealing with metadata quality: The legacy of digital library efforts
Article - Rethinking Metadata’s Value and How It Is Evaluated
An analysis and comparison of keyword recommendation methods for scientific data
Website - C2Metadata, continuous capture of metadata
Article - Scenario-based Metadata Design for Open Data User Interaction
Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

Timeline

2022-11-11T14:44:34Z

Valerias: /* December */

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 15th 3rd project meeting StoRIES, Almeria
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd EB meeting
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 5th platform meeting with AIT
* 12th platform meeting with AIT
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding
* 19th platform meeting with AIT

Timeline

2022-11-11T14:30:37Z

Valerias: /* December */

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 15th 3rd project meeting StoRIES, Almeria
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd EB meeting
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 5th platform meeting with AIT
* 12th platform meeting with AIT
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding
* 19.12 platform meeting with AIT

Example: Standards on power plants

2022-11-11T08:58:48Z

Valerias: /* Example on standard setting for metadata: power plant information */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph
* [https://www.electropedia.org/ IEC Electropedia]

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/8443 gemet:8443]
literal name: thermal power plant
definition: A power-generating plant which uses heat to produce energy. Such plants may burn fossil fuels or use nuclear energy to produce the necessary thermal energy.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-22 iec:602-01-22]
literal name: thermal power station
definition: a power station in which electricity is generated by conversion of thermal energy

=== Example 6: Geothermal power station ===

* [https://www.wikidata.org/wiki/Q30565277 wikidata:Q30565277]
literal: geothermal power station
definition: power plant in which the source of energy is geothermal energy

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=GeothermalPowerPlant kbpedia:GeothermalPowerPlant]
literal: geothermal power plant
definition: none. Comment: This ‘commodity’ product category is drawn from UNSPSC, readily converted into other widely used systems. This commodity category is for geothermal power plant. This product category corresponds to the UNSPSC code: 26131502.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-28 iec:602-01-28]
literal name:
definition: a thermal power station in which thermal energy is extracted from suitable parts of the Earth's crust

=== Example 7: Heat-only boiler station ===

* [https://www.wikidata.org/wiki/Q918457 wikidata:Q918457]
literal: heat-only boiler station
definition: facility generating thermal energy (no electricity generation)

* []
literal:
definition:

=== Example 8: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:42:19Z

Valerias: /* Services to provide resources */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph
* [https://www.electropedia.org/ IEC Electropedia]

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/8443 gemet:8443]
literal name: thermal power plant
definition: A power-generating plant which uses heat to produce energy. Such plants may burn fossil fuels or use nuclear energy to produce the necessary thermal energy.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-22 iec:602-01-22]
literal name: thermal power station
definition: a power station in which electricity is generated by conversion of thermal energy

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:39:42Z

Valerias: /* Example 5: Thermal power plant */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/8443 gemet:8443]
literal name: thermal power plant
definition: A power-generating plant which uses heat to produce energy. Such plants may burn fossil fuels or use nuclear energy to produce the necessary thermal energy.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-22 iec:602-01-22]
literal name: thermal power station
definition: a power station in which electricity is generated by conversion of thermal energy

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:33:52Z

Valerias: /* Example 5: Thermal power plant */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name:
definition:

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name:
definition:

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:31:47Z

Valerias: /* Example 5: Thermal power plant */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name:
definition:

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:31:29Z

Valerias: /* Example 5: Thermal power plant */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Thermal_power_station dbr:Thermal_power_station]:
literal name: Thermal power station
definition: A thermal power station is a power station in which heat energy is converted to electricity.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name:
definition:

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name:
definition:

The open energy ontology does not provide a class for a general thermal power plant. Only particular types such as gas or oil power plants are provided.

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:16:19Z

Valerias: /* Example 5: Thermal power plant */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name:
definition:

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:15:45Z

Valerias: /* Example 5: Thermal power plant */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name:
definition:

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:14:55Z

Valerias: /* Example 5: Thermal power plant */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

* [https://www.wikidata.org/wiki/Q200297 wikidata:Q200297]:
literal name: thermal power station
definition: facility where heat is converted to electric power

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [http://kbpedia.org/kko/rc/ThermalPowerGenerationComplex kbpedia:ThermalPowerGenerationComplex]
literal name: thermal power plant
definition:

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Example: Standards on power plants

2022-11-11T08:06:35Z

Valerias: /* Example 5: Standalone thermal power plant */

= Example on standard setting for metadata: power plant information =

== Context ==
The purpose of this document is to illustrate, which options are available to reference resources for a given entry in a data table. As an example, resources for the concept of an onshore wind farm, a hydropower station, as well as a lithium battery are considered. The resources themselves are taken from general-purpose, community-edited knowledge graphs such as Wikidata or dbpedia, or specialized ontologies such as the open energy ontology.

== Services to provide resources ==

List of ontologies used to reference power plant types:
* [https://www.wikidata.org/wiki/Wikidata:Main_Page Wikidata] - knowledge base, can be read and edited by both humans and machines, collects structured data in a free and collaborative way
* [https://www.dbpedia.org/ DBpedia] - knowledge graphs that extracts structured content from the information created in the Wikipedia
* [https://openenergy-platform.org/ontology/oeo Open Energy Ontology] - domain ontology within the field of energy system modelling
* [https://op.europa.eu/de/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/eurovoc EuroVoc] - multilingual thesaurus maintained by the Publications Office of the European Union
* [https://www.eionet.europa.eu/gemet/en/about/ GEMET] - GEneral Multilingual Environmental Thesaurus updated by EEA and Eionet
* [FAO]
* [http://kbpedia.org/kko/rc/ KBpedia] - open-source knowledge graph

=== Example 1: Onshore Wind farm ===

This example compares resources for onshore wind farm definition:

* [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555]
literal name: onshore wind farm
definition: group of wind turbines on land

* [https://dbpedia.org/page/Wind_farm dbr:Onshore_wind_farm]
literal name: actual redirects to dbr:Wind_farm
definition: A wind farm or wind park, also called a wind power station or wind power plant, is a group of wind turbines in the same location used to produce electricity. ...

* [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311]
literal name: onshore wind farm
definition: An onshore wind farm is a wind farm that is build on land, ( where a windfarm (OEO_00000447) is a power plant that has wind energy converting units as parts.

* [https://www.eionet.europa.eu/gemet/en/concept/ gemet:9336]
literal name: wind power station
definition: Power station which uses wind to drive a turbine which creates electricity.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=415-01-03 iec:415-01-03]
literal name: wind power station
definition: power station comprising a group or groups of wind turbine generator systems

The problems we encounter here are: GEMET does not offer a resource to directly describe an onshore wind farm. Rather, what is available is a resource related to a wind farm in general. Similarly, KBpedia has only [https://kbpedia.org/knowledge-graph/reference-concept/?uri=WindFarm a resource] relating to a wind farm. Same applies to IEC.DBpedia offers a resource link for an onshore wind farm, but does not provide a separate definition. On the other hand, wikidata and the open energy ontology offer specific definition, which seem to be very similar, if one identifies wind turbines with wind energy converting units.

=== Example 2: Hydropower plant ===

This example compares different definitions of hydropower plants provided by various ontologies/controlled vocabularies:
* [https://www.wikidata.org/wiki/Q15911738 wikidata:Q1591738]:
literal name: hydroelectric power station
definition: facility generating electric power using hydroelectricity

* [http://openenergy-platform.org/ontology/oeo/OEO_00010086 oeo:OEO_00010086]:
literal name: hydro power plant
definition: A hydro power plant is a power plant having an aggregate of hydro power generating units as its power generating unit parts.

* [https://www.eionet.europa.eu/gemet/en/concept/4098 gemet:4098]:
literal name: hydroelectric power plant
definition: Power station which operates with the free renewable source of energy provided by falling water.

* [http://kbpedia.org/kko/rc/HydroelectricPowerStation kbpedia:HydroelectricPowerStation]
literal name: Hydroelectric power station
definition: This commodity category is for hydro power plant. This product category corresponds to the UNSPSC code: 26131503.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-04 iec:602-01-04]
literal name: hydroelectric power station
definition: a power station in which the gravitational energy of water is converted into electricity

* [https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/EnergyResourceOntology.owl#HydroElectricPlant thinkhome:HydroElectricPlant]
literal name:
definition: Hydropower plants capture the energy of falling water to generate electricity.

Note, that dbpedia and EuroVoc do not provide a resource specifically describing a hydropower plant. They rather offer definitions on the general concept of hydropower technology. kbpedia offers no explicit definition, but rather refers to the United Nations Standard Products and Services Code and its entry No. 26131503. Searching for this resource on the [https://www.unspsc.org/ landing page] returns only a literal description as 'Hydro power plants' without further explanation.

=== Example 3: Solar PV plant ===

* [https://www.wikidata.org/wiki/Q1003207 wikidata:Q1003207]
literal name: photovoltaic power station
definition: type of solar power station, large-scale photovoltaic system

* [https://dbpedia.org/page/Photovoltaic_power_station dbr:Photovoltaic_power_station]
literal name: photovoltaic power station
definition: A photovoltaic power station, also known as a solar park, solar farm, or solar power plant, is a large-scale grid-connected photovoltaic power system (PV system) designed for the supply of merchant power.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000324 oeo:OEO_00000324]
literal name: photovoltaic power plant
definition: A photovoltaic power plant is a solar power plant that has PV panels as parts.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=PhotovoltaicPowerStation kbpedia:PhotovoltaicPowerStation]
literal name: photovoltaic power station
definition: Large-scale photovoltaic system.

* [https://www.eionet.europa.eu/gemet/en/concept/7910 gemet:7910]
literal name: solar power station
definition: Plant where energy is generated using radiation from the sun.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=602-01-29 iec:602-01-29]
literal name: solar power station
definition: a power station producing electrical energy from solar radiation directly by photovoltaic effect, or indirectly by thermal transformation

=== Example 4: Heat pump ===

* [https://www.wikidata.org/wiki/Q131313 wikidata:Q131313]
literal name: heat pump
definition: device that transfers thermal energy in the opposite direction of spontaneous heat transfer

* [https://dbpedia.org/page/Heat_pump dbr:Heat_pump]
literal name: Heat pump
definition: A heat pump is a device that transfers thermal energy between spaces, usually between an enclosed space and the outdoors.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000212 oeo:OEO_00000212]
literal name: heat pump
definition: A heat pump is a heater that transforms low temperature heat to high temperature heat using external energy.

* [http://kbpedia.org/kko/rc/HeatPump kbpedia:HeatPump]
literal name: heat pump
definition: The collection of all heat pumps. A type of AirCoolingDevice, MechanicalDevice, ElectricalDevice, ExternallyPoweredDevice, and AirHeatingDevice.

* [http://eurovoc.europa.eu/2549 eurovoc:2549]
literal name: heat pump
definition: none (thesaurus)

* [https://www.eionet.europa.eu/gemet/en/concept/3904 gemet:3904]
literal name: heat pump
definition: A device which transfers heat from a cooler reservoir to a hotter one, expending mechanical energy in the process, especially when the main purpose is to heat the hot reservoir rather than refrigerate the cold one.

* [http://metadata.un.org/thesaurus/1002851 un:1002851]
literal name: HEAT PUMPS
definition: none (thesaurus)

* [http://aims.fao.org/aos/agrovoc/c_24398 agrovoc:24398]
literal name: heat pumps
definition: none (thesaurus)

* [https://www.dco.domos-project.eu/#HeatPumpAppliance dco:HeatPumpAppliance]
literal name: Heat pump appliance
definition: A heat pump appliance is used to warm and, direction in which heat transfer would take place without

* [https://w3id.org/hpont#HeatPumpSystem hpont:HeatPumpSystem]
literal name: Heat Pump System
definition: A system composed of one or many devices that transfer heat from a colder area to a hotter area by using mechanical energy

No entry for heat pump in Electropedia: The World's Online Electrotechnical Vocabulary provided by the International Electrotechnical Commission. The dco definition is apparently not properly reviewed.

=== Example 5: Thermal power plant ===

List of examples for thermal power plant resources

=== Example 6: Lithium-ion battery ===

This example compares resources for lithium-ion batteries provided by the different providers:

* [https://www.wikidata.org/wiki/Q2822895 wikidata:Q2822895]:
literal name: lithium-ion battery
definition: rechargeable battery type

* [https://dbpedia.org/page/Lithium-ion_battery dbr:Lithium-ion_battery]:
literal name: Lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery composed of cells in which lithium ions move from the negative electrode through an electrolyte to the positive electrode during discharge and back when charging.

* [http://openenergy-platform.org/ontology/oeo/OEO_00000248 oeo:OEO_00000248]
literal name: lithium-ion battery
definition: A lithium-ion battery is a battery that is rechargeable and in which lithium ions move from the negative electrode to the positive electrode during discharge, and back when charging. Li-ion batteries use an intercalated lithium compound as one electrode material.

* [https://kbpedia.org/knowledge-graph/reference-concept/?uri=LithiumIonBattery kbpedia:LithiumIonBattery]
literal name: lithium-ion battery
definition: A lithium-ion battery or Li-ion battery is a type of rechargeable battery in which lithium ions move from the negative electrode to the positive electrode during discharge and back when charging.

* [https://www.eionet.europa.eu/gemet/en/concept/745 gemet:745]
literal name: battery
definition: A series of cells, each containing the essentials for producing voltaic electricity, connected together.

* [https://www.electropedia.org/iev/iev.nsf/display?openform&ievref=482-05-07 iec:482-05-07]
literal name: lithium ion battery
definition: secondary battery with an organic solvent electrolyte and positive and negative electrodes which utilize an intercalation compound in which lithium is stored

Note that GEMET does not offer the concept of a lithium-ion battery, available sub-classes are alkaline battery, button-cell battery, cell (energy), and electric battery.

== References ==

Booshehri, M. et al. Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis. ''Energy and AI'' '''5''', 100074 (2021).

Simon Clark, Francesca L. Bleken, Simon Stier, Eibar Flores, Casper Welzel Andersen, Marek Marcinek, Anna Szczesna-Chrzan, Miran Gaberscek, M. Rosa Palacin, Martin Uhrin, and Jesper Friis, Toward a Unified Description of Battery Data, 12, 2102762 () https://onlinelibrary.wiley.com/doi/epdf/10.1002/aenm.202102702

Timeline

2022-11-10T15:19:20Z

Valerias: /* November */

<accesscontrol>Administrators,consortium</accesscontrol>

= Timeline of the implementation of the project =
Overview of steps undertaken in EERAdata to implement the project. The focus is on steps forward and backward. It will help us later to come up with realistic suggestions in the recommendations and lessons learned to help others who are interested in FAIRifying and opening their data. For example, how long does the preparation take? How difficult is the organizational effort? Furthermore, it will support the reporting to EC.

== Year 2020 ==
=== January ===

*7 January 2020, Meeting with CESSDA in Bergen, to discuss involvement in EERAdata and prepare WS 1. Co-hosting institution. Ron Dekkar Member of Advisory Board.
*7 January 2020, Presentation of EERAdata at HVL annual meeting of the Faculty of Engineering and Natural Sciences to reach out beyond the EERAdata consortium.
*15 January 2020, Establishing contact with Philipp Conzett, Univ. of Tromso and DATAVERSE. Linking EERAdata to DATAVERSE.

=== March ===

*'''11-12 March 2020, '''[https://www.open-science-conference.eu/ Open Science Conference 2020]''' and Barcamp, Berlin, Germany:''' Presentation of August Wierling (HVL), incl. abstract: [https://zenodo.org/record/3776858#.XrP-w3Yza90 https://zenodo.org/record/3776858#.XrP-w3Yza90 ]. Establishing personal contact with Ludwig Hülk, Rainer-Lemoine-Institute (Open Mode Initiative).
*'''18 March 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5383483 Executive Board Meeting No. 1], Preparing online kick off
*Establishing contacts with CESSDA, NEIC, EOSC WG FAIR data,
*'''25 March 2020''', Online meeting with Trond Kvamme, Norwegian Center for Research Data (NSD, discussing collaboration on DMP and workshop participation).

=== April ===

*'''3 April 2020, [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5348498 Kickoff workshop of EERAdata]''', online, Starting the project - introduction to organization, objectives, collaboration infrastructure
*'''3 April 2020''', Training on using Only Office online collaboration platform
*'''24 April 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 Executive Board Meeting No. 2], Follow up of kick of, Deliverables D1.1 and D8.1a, website and CI discussion
*27 April 2020, Participation in PiAI seminar, Toyohiro Chikyow, National Institute for Materials Science (NIMS), Japan: How we can increase the data for Materials Informatics?
*'''28 April 2020''', [https://energydata.onlyoffice.eu/products/projects/tasks.aspx?prjID=236894&id=1239815 UC 1 Kickoff], discussing FAIR/O and metadata approach, databases to select. The meeting successfully held. August also participated to deliver the approach of WP2. We clarified a number of questions with the contribution of August and other team members. Road ahead was set. The first task was assigned via only office to the partners that are involved in WP4.

=== May ===

*'''5 May 2020''', [https://www.eera-set.eu/events/859:eera-9th-general-assembly.html EERA General Assembly]: Presentation of EERAdata project by Secretary-General of EERA, Adel al Gamal
*'''6 May 2020''', Online meeting with JP Wind, coordinator Flaminia Riccioni Capelli, to discuss postponed EERA workshop on FAIR and open energy data: when to re-organize and how to best link with EERAdata
*'''6 May 2020''', [https://energydata.onlyoffice.eu/products/projects/messages.aspx?prjID=236894&id=62375#comments Gap analysis] - Online discussion of how to approach and connect with use cases
*'''6 May 2020''', Discussion with Holger Ihssen (KIT, member of the advisory board), Involvement in EERAdata and WS1, linking EERAdata with EERA and JP Digitalization
*'''12 May 2020''', UC 4 kickoff 
*'''13 May 2020''', UC 2 kickoff
*'''14 May 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5311235 EB meeting No. 3] to prepare WS1
*'''14 May 2020,''' Online meeting with Ilaria Fava, OpenAIRE project to discuss linking projects, involvement in WS1 and advisory board. EERAdata considers applying for their fund.
*'''15 May 2020''', UC 3 kickoff
*'''15 May 2020,''' Online meeting with Andreas Jaunsen, Nordforsk & EOSC-Nordic to invite to the workshop as presenter and discussant. Candidate for the EERAdata advisory board.
*'''18 May 2020''', Online meeting with Anna Maria Sempreviva, DTU, and IRP wind to invite to the workshop as presenter and discussant.
*'''18 May 2020''', Online interview about EERAdata with Stavanger Region European Office. Linking to Triangulum project and EU initiative "e-translation" 
*'''18 May 2020''', Online discussion with transversal EERA JP on digitalization (tJP Digitalization). EERAdata (Valeria) to lead the planned subprogram on FAIR and Open energy data.
*'''20 May 2020''', Discussion with Tomasz Miksa (TU Wien, an expert on machine-actionable DMPs), Involvement in EERAdata and WS1
*'''21 May 2020''', Discussion with Elena Giulia (UNITO, member of the advisory board), Involvement in EERAdata and WS1
*'''25 May 2020''', [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1 EERAdata project wiki] established at webfactional
*'''27 May, 2020'''. Online meeting with Diane van Gunten and Jakob Rager to connect with H2020 EnergMap. Projects presented to each other, discussing synergies and collaboration possibilities (incl. joint special issue). Collaboration on platforms useful.
*'''28 May, 2020'''. Online meeting UC 3 (preparation of workshop)
*'''29 May, 2020''', Online meeting UC 2 (preparation of workshop)
*'''29 May''', '''2020''', Online workshop "EERA JP Wind & SETWind Cross-cutting workshop on Open and Fair Data" [https://www.eerajpwind.eu/eera-jp-wind-setwind-cross-cutting-workshop-on-open-fair-data/ Invitation and registration]
*'''29 May, 2020,''' [https://github.com/RDA-DMP-Common/hackathon-2020 Participation in online hackathon for machine-actionable DMPs]
*Establishing contacts with advisory board members: KIT, UNITO, Open AIRE, Nordic EOSC, DLR.

=== June ===

*'''2-4 June 2020, EERAdata Workshop No. 1 as an online hackathon, "Define. Concept for FAIR implementation. '''Skills for FAIR.": [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 Agenda]. Includes EERAdata storyboard and metadata game.
*'''3-5 June, 2020''', [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/ Conference on FAIR data infrastructure for genomics]. EERAdata participated.
*'''5 June 2020,''' Online meeting with Sebastian Duprez from https://www.eccsel.org/, European Carbon Dioxide Capture and Storage Laboratory Infrastructure.
*'''8 June, 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5493018 EB meeting No. 4].
*'''10 June 2020,''' Online meeting with Sarah Barber on FAIR and open data, wind technology. Follow-up from JP Wind workshop. Leader of network  https://www.wedowind.ch/.
*'''11 June, 2020,''' Online meeting with Michael Belsnes, SINTIF and OpenENTRANCE project [https://www.sintef.no/en/projects/open-entrance/ ,  https://www.sintef.no/en/projects/open-entrance/, ]
*'''11 June 2020,''' Drafting of work plan for SP on FAIR and open energy data for tJP Digitalization,
*'''18 June, 2020,''' EERAdata workshop at annual '''EERA e3s''' meeting,
*'''29 June 2020, PiAI Seminar Series "Physics informed AI in Plasma Science"''' (organized by Prof. [https://www.researchgate.net/profile/Satoshi_Hamaguchi Satoshi Hamaguchi], Osaka University), Presentation by Valeria Jana Schwanitz (HVL), "Towards metadata standards in low carbon energy research - insights from the EERAdata project"

=== July ===
*'''20 July 2020,''' 14:00 hrs CEST and it will be about “Scientific Annotation - Engineering Applications, Discovery and Preservation”. If you are interested in participate you can find more information and the registration link here: https://rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-preservation-tools-techniques-and-policies

=== August ===
* '''5 August 2020''', Discussion with Holger Ihssen, KIT, on WS2 strategy

=== September ===

* '''1 September 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5589857 EB meeting No. 5] to prepare WS2, metadata work & platform
* '''1 September 2020''', Kickoff WP3 - Platform meeting
*'''11 September 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''14-18 September 2020''', Participation in [https://www.eerajpwind.eu/?post_type=events&p=1164 EERA JP Wind & SETWind Online Annual Event 2020], [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5704239&action=view EERAdata poster] contribution
*'''15 September 2020''', Participation in online workshop [https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and Building metadata standards within Engineering disciplines and communities]
* '''21 September 2020''', UC 4 meeting to discuss state of the art paper
* '''25 September 2020''', Participation in RDA workshop "[https://www.rd-alliance.org/group/metadata-ig-working-and-interest-group-chairs-fairsharing-registry-wg-connecting-data-and-2 Building metadata standards within Engineering disciplines and communities]".

=== October ===
*'''2 October 2020''', [https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5701552 EB meeting No. 6], all WP progress
*'''9 October 2020''', Participation in RDA seminar, 15.30-17.00, Invitation to follow, EERAdata participates with a presentation
*'''16 October 2020''', Online paper writing workshop "Towards FAIR and open data for low carbon energy - current state and call for action"
*'''16 October 2020''', Online meeting to prepare WS2
*'''19 October 2020''', Presentation of EERAdata at the International Open Access Week
*'''26-30 October 2020''', Week dedicated to work on the state of the art on FAIR/O energy data
*'''October-November 2020''', Participation in the NEIC workshop on FAIRification (biweekly, half day)

=== November ===
*'''3-4 November 2020''', Annual assembly of sister project ENERMAPS, invited to present EERAdata
*'''5 November''', [https://www.eeradata.eu/event/1645:preparatory-workshop-fair-and-open-metadata-for-low-carbon-energy-research.html Preparatory/Briefing workshop to EERAdata Workshop No. 2]
*'''6 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5787317 EB meeting No. 7], all WP progress
*'''9-10 November''', [https://rd-alliance.org/plenaries/rda-16th-plenary-meeting-costa-rica-virtual RDA 16th Plenary Meeting] - Costa Rica (Virtual), participation
*'''11 November''', Participation in ontology developer meeting of [https://openenergy-platform.org/ontology/ open energy ontology]
*'''11 November 2020''', Discussion with Holger Ihssen (KIT) to prepare WS2
*'''11 November 2020''', Discussion with Erik Schultes (GOFAIR) to prepare WS2 and have a joined session to prepare EERAdata M4Mworkshops within the Convergence Symposium 2020
*'''13 November 2020''', Discussion with Peter McQuilton, FAIRSHARING.org and Oxford University about possible contributions of EERAdata to the FAIRSHARing database
*'''16-19 November''', [https://www.eosc-hub.eu/events/realising-european-open-science-cloud REALISING THE EUROPEAN OPEN SCIENCE CLOUD], Towards a FAIR research data landscape for the social sciences, humanities and beyond - Participation with a booth
*'''20 November''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5931610 EB meeting No. 8], all WP progress and WS preparation
*'''20 November''', EERAdata participates in SUPEERA project on policy indicators to connect with the project and co-host of WS2 KIT
*'''30 November - 7 December 2020''', EERAdata Workshop No. 2 "[https://www.eeradata.eu/event/1518:paper-writing-workshop-fair-and-open-metadata-for-low-carbon-energy-research-day-1.html FAIR AND OPEN METADATA FOR LOW CARBON ENERGY RESEARCH]" (7 workshops)
*'''30 November 2020''', planned submission of state of the art paper

=== December ===
*''' 2020, EERAdata Workshop No. 2 as an online hackathon to write a community paper, "FAIR and open metadata for low carbon energy research": [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS2].
Topical workshops:
* 1st of December - EU Policy and Energy Research Taxonomies (lead by GIG), 10am-2pm
* 2nd of December - Buildings efficiency & metadata (led by IUE), 10-12 pm
* 3rd of December - Metadata user stories (led by AIT), 10-12 pm
* 4th of December - Online art project - FAIR data & SDGs, 10-3pm
* 4th of December - Joint session with the [https://conference.codata.org/FAIRconvergence2020/sessions/265/ International FAIR Convergence Symposium "Making domain-relevant machine-actionable metadata at scale"].
* 7th of December - Framing session 10am-4pm
*'''11th of December''', [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=5985372 EB meeting No. 9] to debrief WS2 and the state of EERAdata for 2020

== Year 2021 ==
=== January ===
* January Kick-off of new EERA Joint Program Digitalization of Energy, Valeria to lead the Subprogramme on "Data Science & AI"
* 6th of January - Meeting with general secretary of EERA, Adel El Gamal, to discuss linking EERAdata and EERA with new tjP Digitalization
* 11 th of January - Coordinator meeting of tJP Digitalization of Energy, presentation of EERAdata and invitation to community paper
* 13 th of January - 2-3pm, Discussion with AIT on gap analysis deliverable
* 15 th of January - sending out of 1st draft of community paper on advancing energy FAIR metadata practices
* 22 th of January - discussion of draft for paper on state-of-the-art of FAIR and open energy data
* 22 th of January - [https://energydata.onlyoffice.eu/Products/Files/DocEditor.aspx?fileid=6066674 EB meeting No. 10], upcoming deliverables, planning of WS3
* 27 th of January - Workshop on FAIR and open metadata for the COMETS inventory (use case 'electricity market actors', EERAdata WP5). Collaboration between COMETS and EERAdata consortium 10-3pm.
* 31 st of January - Deadline, first round of review of community paper

=== February ===
*2 nd February - Discussion with Philipp Conzett, Univ. of Tromso and DATAVERSE on preparing the upload of a use case to dataverse.no (incl. PID)
*3 rd February - Participation in NORDIC EOSC Workshop "[https://indico.neic.no/event/171/ FAIRification STEP 2 – FAIR principle F3]"
*4 th Februrary - sending out of 2nd draft of community paper on advancing energy FAIR metadata practices
*20th February - submission of community paper

=== March ===
*9 th March - Participation in [https://www.eosc-nordic.eu/events/second-eosc-nordic-policy-workshop-nordic-and-baltic-collaboration-as-eosc-enabler/ Second EOSC-Nordic Policy Workshop: Nordic and Baltic collaboration as EOSC enabler]
*12th March - EB meeting
*25th March - Presentation of EERAdata/FAIR and open data topic at the [https://www.ucl.ac.uk/artificial-intelligence/public-policy/ai-policy-roundtables UCL Roundtables on AI & Policy], follow up with a policy brief
*29/03-02 April - Participation in the 3rd International Conference on Data-Driven Plasma Science (online conference organized by Univ. of Osaka, Japan)
*31 March - Brainstorming workshop for WS3 in conjunction with EERA tJP Digitization for Energy

=== April ===

*9 th April - Discussion on follow-up project for EERAdata as part of kick-off for tJP DfE SP2
*12 th April - Presentation of EERAdata and idea for follow-up project at the EERA brokerage event.
*16 th April - EB meeting
*20 th April - Meeting with sister project [https://enermaps.eu/ ENERMAPS]
*21 th April - Presentation of EERAdata at [https://www.etip-snet.eu/events/ 11TH ETIP SNET REGIONAL WORKSHOP]
*22 nd April - [https://www.rd-alliance.org/rdas-17th-plenary-meeting-programme RDA, 17th plenary meeting - presentation of EERAdata]
*29 th April - [https://www.eosc-nordic.eu/events/fairification-step-3-generic-metadata-standards/ EOSC Nordic webinar, step 3, generic metadata standards]

=== Mai ===

*6 th May - EERA assembly
*10th May - EM4I - Meeting to prepare workshop series "Energy Materials for Interoperability"
*12th May - Preparation meeting WS3
*18 th May - Consortium meeting energy data space
*17 th May - Submission of proposal to EU Energy Week together with sister project [https://enermaps.eu/ ENERMAPS]
*21 th May - EB meeting
*25-27 May - Participation in data week [https://www.big-data-value.eu/data-week-2021/]
*28 May - Participation in SUPEERA Webinar "A European Green Deal fit for the Digital Age: What’s in for Clean Energy Research?”

=== June ===
* 10 June - Meeting with EERA JP Digitization for Energy (DfE) to brainstorm on collaboration with EERAdata
* 10 June - Consortium meeting for developing a proposal for Energy data space
* 17 June - Consortium meeting for developing a proposal for Energy data space
* 18 June - Meeting with EERA JP DfE, preparation of joined conference/workshop in October
* 21-23 June - Participation in [https://www.go-fair.org/events/fair-festival-2021/ GOFAIR sharing festival]
* 23 June - Participation in meeting to prepare EM4I workshop series (programm committee)
* 24 June - Consortium meeting for developing a proposal for Energy data space

=== July ===
* 1st of July - [https://www.eera-set.eu/events/events-of-eera-and-its-partners/2856:energy-materials-for-innovation-em4i-workshop-series-materials-discovery-and-development.html Energy Materials for Innovation (EM4I) Workshop series] - Materials Discovery and Development
* 2nd of July - EB meeting
* 6th of July - Lecture series and discussion as part of EERAdata workshop no. 3
* 29th of July - Presentation of EERAdata project and aspects of open data and FAIR as tools for implementing Industry 4.0 on the regional workshop in Silesia Region (online, in Polish) "[https://ris.slaskie.pl/czytaj/spotkanie_warsztatowe_online_pt__rozne_perspektywy_budowania_potencjalu_przemyslu_4_0 Challenges and different perspectives on building the potential of Industry 4.0 in Silesia Region]"

=== August ===
* 26th of August - Lead partner meeting prepare midterm reporting
* 27th of August - EB meeting

=== September ===
* 2nd of September - Preparation meeting for Workshop no. 3 to prepare topical sessions of use cases
* 9th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* 16th of September - RDA/EOSC meeting
* 17th of September - EB meeting
* 23th of September - Presentation of EERAdata in the industrial conference “Kraft i Vest/Power in Western Norway '', Norway
* 23th of September - Meeting of core writing team for FEEDS proposal (energy data space)
* ''27th of September - EERAdata meets FAIRsharing (discussion on metadata contribution to FAIRsharing by EERAdata) - postponed''
* 27th of September - 1-day meeting to prepare mid-term report
* 28th of September - Participation in the conference Standards in support of the industrial data value chain (recommendation from advisory board member Tim Austin)

=== October ===
* 1st of October - EB meeting
* 7th of October - EOSC Nordic meeting
* 7th of October - Meeting of the core writing team for FEEDS proposal (energy data space)
* 8th of October - EERAdata meets [https://ontocommons.eu/ ONTOCOMMONS] to explore opportunities for collaboration
* 11th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 12-13 October - [https://www.eeradata.eu/event/3028:eeradata-workshop-no-3-fairification-put-into-practice.html EERAdata Workshop No. 3] back to back with EERA JP Digitization for Energy annual conference, documentation at [[WS3|EERAdata wiki]]
* 18th of October - EUSEW preparation meeting; EERAdata joins energy talks
* 20th of October - FEEDS proposal submitted
* 22nd of October - Joining the [https://ontocommons.eu/ ONTOCOMMONS] workshop “Creating a Knowledge Exchange Space for data management and documentation - KExS”
* 22nd of October - EUSEW preparation meeting; EERAdata joins energy talks
* 26th of October - [https://www.eusew.eu/about-networking EUSEW, energy talks as part of the networking village]
* 28th of October - EERA joins the “[https://farmconners-market-showcase.readthedocs.io/en/latest/ FarmConners project workshop] ´Machine-actionable metadata", organized by DTU

=== November ===
* 5th of November - HVL internal meeting on midterm reporting
* 26th of November - EB meeting

=== December ===
* 6th of December - Mini-workshop WP3 with UC2 - database examples for the platform
* 10th of December - Mini-workshop WP3 with UC1 - database examples for the platform
* 14th of December - Mini-workshop WP3 with UC4 - database examples for the platform

== Year 2022 ==
=== January ===
* 14th of January - EB meeting
* 18th of January - Meeting with CENER, Spain, to consult on FAIR and open data principles for a planned project application.

=== February ===
* 4th of February - Approval of EU project WHITECYCLE with FAIR data industrial use case, follow-up project
* 8th of February - EOSC Nordic event [https://www.eosc-nordic.eu/events/fairification-step-5-webinar-value-and-limitations-of-fair-assessment-tools/ 'FAIRification STEP 5 webinar: Value and limitations of FAIR assessment tools']
* 11th of February - EB meeting
* 14th of February - Meeting to prepare a presentation at EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality], Richard Dennis - Royal Danish Library/KUB
* 17th of February - Meeting with DG Energy - Presentation on Human-centered digitalization of the energy sector
* 24th of February - Webinar FAIRPoints-Step by step publishing with ResearchE [https://www.scilifelab.se/event/fairpoints-researchequals/]

=== March ===
* 1st of March - Meeting with EOSC task force on [https://www.eosc.eu/advisory-groups/fair-metrics-and-data-quality FAIR metrics and data quality]
* 15th of March to 17th of March - Workshop N°4: “Supporting technologies for FAIRification"
* 25th of March - EB meeting

=== April ===
*
=== May ===
* 6th of May - EB meeting
* 30th of May to 1st of June - NeIC 2022 conference Nordic Models for Open Science Collaboration.

=== June ===
* 10th of June - EB meeting
* 16th of June - UC2: ENBP inventory published on dataverse.no

=== July ===
* 20th of July - Meeting with project StoRIES

=== August ===

* 5th of August - EB meeting
* 10th of August - meeting with PANTERA project on the EIRIE platform
* 11th of August - Internal mini-workshop on platform development
* 19th of August - Internal mini-workshop on platform development
* 25th of August - Internal mini-workshop on platform development
* 30th of August - Internal meeting on finalizing web presence deliverable

=== September ===

* 9th of September - EB meeting

=== October ===

* 3rd - 5th of October - 5th workshop
* 24th internal platform meeting AIT: offering extra functionalities
* 25th Preparation meeting with StoRIES
* 25th EB meeting
* 27th StoRIES Workshop LCA and Fair
* 31st internal platform meeting AIT

=== November ===

* 2nd preparation meeting StoRIES DMP
* 7th internal platform meeting AIT
* 8th AIT meeting (offene Projektrunde)
* 10th meeting EERAdata - DANS [https://fair-impact.eu/ Fair impact]
* 11th AIT meeting
* 15th 3rd project meeting StoRIES, Almeria
* 24th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Metadata

=== December ===
* 2nd [https://site.uit.no/dataverseno/nn/2022/11/06/dataverseno-5-arsjubileum/ DataverseNO 5th anniversary seminar, University of Tromsø]
* 12th [https://fair-impact.eu/events/synchronisation-force-events/synchronisation-force-1st-workshop-november-2022 Synchronisation Force 1st Workshop]: Concluding

Tools

2022-11-10T10:19:52Z

Valerias: /* Tools to validate structured data */

== Tools to validate structured data ==
* [https://csvlint.io/ csv lint] and [https://csvlint.io/schemas corresponding example schema]
* [http://ttl.summerofcode.be/ IDLab Turtle Validator]
* [http://linter.structured-data.org/ Structured Data linter]
* [http://rdftools.surroundaustralia.com/validate Validate RDF Data by SURROUND AUSTRALIA]
* [https://pypi.org/project/csvcubed/ csvcubed]

Tools

2022-11-10T08:08:33Z

Valerias:

Tools

2022-11-09T09:26:07Z

Valerias: /* Tools to validate structured data */

Tools

2022-11-09T08:40:54Z

Valerias: /* Tools to validate structured data */

== Tools to validate structured data ==
* [http://ttl.summerofcode.be/ IDLab Turtle Validator]
* [http://linter.structured-data.org/ Structured Data linter]

Tools

2022-11-09T08:38:21Z

Valerias: /* Tools to validate structured data */

== Tools to validate structured data ==
* [http://linter.structured-data.org/ Structured Data linter]

Tools

2022-11-09T08:34:25Z

Valerias: Created page with "== Tools to validate structured data =="

== Tools to validate structured data ==

CSVW for energy datasets

2022-11-07T19:24:28Z

Valerias: /* Worked example: Power plant information */

This page collects examples of improving the FAIRness of datasets using the csv extension csvw. Most importantly, csv on the web offers a possibility to tie together metadata and data, starting from a well-known and widely
used data format. The standard offers a rich framework to annotate existing csv documents with additional information and transform them into other forms of structured data exchange formats such as JSON(-ld) and RDF. At the same time, csv on the web is user-friendly offering a flexible mechanism from minimal FAIR extensions to elaborated context building for the data to be shared. CSV on the web is a W3C recommendation in coherence with ...

=== FAIR principles ===

The example illustrates how csv on the web contributes to realize the FAIR principles

To be Findable:

F1. (meta)data are assigned a globally unique and eternally persistent identifier.

F2. data are described with rich metadata.

F3. (meta)data are registered or indexed in a searchable resource.

F4. metadata specify the data identifier.

To be Accessible:

A1 (meta)data are retrievable by their identifier using a standardized communications protocol.

A1.1 the protocol is open, free, and universally implementable.

A1.2 the protocol allows for an authentication and authorization procedure, where necessary.

A2 metadata are accessible, even when the data are no longer available.

To be Interoperable:

I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.

I2. (meta)data use vocabularies that follow FAIR principles.

I3. (meta)data include qualified references to other (meta)data.

To be Re-usable:

R1. (meta)data have a plurality of accurate and relevant attributes.

R1.1. (meta)data are released with a clear and accessible data usage license.

R1.2. (meta)data are associated with their provenance.

R1.3. (meta)data meet domain-relevant community standards.

=== Worked example: citizen-led initiatives ===

We start with a csv file whose contents are shown in this table:

{| class="wikitable"
! name || status || year of foundation || national identifier || street address || city || postal code || C/O || lat || lon || website || activity || national industrial sector classification || purpose (original language) || purpose (translation) || date of removal || country code || legal form
|-
| Kvarkenvinden 1 || active || 1998-01-27 || 769602-8096 || Norra Obbolavägen 89 || Umeå || 904 22 || || 63.80667 || 20.27364 || http://kvarkenvinden.se || wind onshore || 35.110 || Föreningen har till ändamål att främja sina medlemmars ekonomiska intressen och dess miljöintresse genom att utöva driftsansvar över vindkraftverk i syfte att tillhandahålla vindenergi för medlemmarnas konsumtion. All genom föreningen genererad vindenergi ägs av medlemmarna. || The purpose of the association is to promote the financial interests of its members and its environmental interests by exercising operational responsibility for wind turbines in order to provide wind energy for the members' consumption. All wind energy generated by the association is owned by the members. || || SWE || C61P
|-
| Ollebacken vind ekonomiska förening || active || 2008-01-08 || 769618-1010 || SIKÅS NORRA BYVÄGEN 180 || Hammerdal || 833 49 || || 63.67432 || 15.06297 || https://www.ollebackenvind.se || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarans ekonomiska intressen genom att i egen regi producera miljö vänlig energi. || The purpose of the association is to promote the members' financial interests by producing environmentally friendly energy on their own. || || SWE || C61P
|-
| Jamtkulingen ekonomiska förening || active || 2009-01-20 || 769619-7420 || Södra Strandvägen 19 A || Frösön || 832 44 || Sven Erik Eriksson || 63.17622 || 14.61152 || http://www.jamtkulingen.se/ || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen genom att i egen regi producera miljövänlig energi. || The purpose of the association is to promote the members' financial interests by producing environmentally friendly energy on their own. || || SWE || C61P
|-
| Hällingarna Vind || active || 2005-08-02 || 769612-8318 || OLLEBACKEN 130 || Hammerdal || 833 49 || || 63.59838 || 15.05107 || || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen genom att i egen regi producera miljövänlig engeri. Medlemmarna deltar i verksamheten som konsumenter. || The purpose of the association is to promote the members' financial interests by producing environmentally friendly areas on their own. The members participate in the business as consumers. || || SWE || C61P
|-
| Offerdalsvind Ekonomiska förening || active || 2000-08-31 || 769606-0719 || BERGE 718, || Offerdal || 835 97 || || 63.46154 || 14.09483 || http://www.offerdalsvind.se || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen genom att i egen regi producera miljövänlig energi. Medlemmarna deltar i verksamheten som konsumenter. || The purpose of the association is to promote the members' financial interests by producing environmentally friendly areas on their own. The members participate in the business as consumers. || || SWE || C61P
|-
| Trärike vindkraft ekonomisk förening || liquidation || 1996-08-07 || 769601-6331 || VIKINGAVÄGEN 36 || Sundsvall || 857 41 || || 62.40317 || 17.26335 || http://www.trarikevindkraft.se/index.htm || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intresse genom att förse medlemmarna med egen vindkraft- producerad el och även främja medlemmarnas miljöintresse och vindkraftens utveckling. Föreningen skall bygga upp ett kapital som säkrar uppbyggnad, drift, underhåll och demontering av föreningens vindkraftverk. || The purpose of the association is to promote the members 'financial interest by providing the members with their own wind-powered electricity and also promoting the members' environmental interest and the development of wind power. The association will build up a capital that ensures the construction, operation, maintenance and dismantling of the association's wind turbines. || || SWE || C61P
|-
| Dala Vindkraft Ekonomisk förening || active || 2006-02-18 || 769613-8911 || RIKSVÄGEN 15 || Rättvik || 795 32 || || 60.88933 || 15.11092 || http://dalavind.se/vindandelar-foreningar/dala-vindkraft-ekonomisk-forening/medlemsinformation || wind onshore, E-trade || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen, samt deras miljöintresse, genom att tillhandahålla medlemmarna egen vindkraftsproducerad elkraft. || The purpose of the association is to promote the members' financial interests, as well as their environmental interests, by providing the members with their own wind-powered electricity. || || SWE || C61P
|-
| Vindela || active || 2004-08-17 || 769611-2411 || BOX 4 || Malung || 782 21 || || 60.6834 || 13.71603 || http://dalavind.se/vindandelar-foreningar/vindela/ || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen genom att i egen regi producera miljövänlig elkraft. || The purpose of the association is to promote the members' financial interests by producing environmentally friendly electricity on their own. || || SWE || C61P
|-
| Äppelbovind || active || 2000-09-25 || 769606-1485 || BOX 4 || Malung || 782 21 || || 60.6834 || 13.71603 || http://dalavind.se/vindandelar-foreningar/appelbovind/kontakt/ || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen genom att i egen regi producera miljövänlig elkraft. || The purpose of the association is to promote the members' financial interests by producing environmentally friendly electricity on their own. || || SWE || C61P
|-
| Fjällbergsvind ekonomisk förening || liquidation || 2005-09-13 || 769613-0587 || Djupuddsvägen 35 || Grängesberg || 772 40 || || 60.08136 || 14.98449 || http://dalavind.se/vindandelar-foreningar/fjallbergs-vind-ekonomiskforening || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen genom att tillhandahålla medlemmarna egen vindkrafts- producerad elkraft. || The purpose of the association is to promote the members' financial interests by providing the members with their own wind power produced electricity. || || SWE || C61P
|-
| Kyrkvinden ekonomiska förening || active || 2005-05-09 || 769613-0025 || GIMOGATAN 6 B 3TR || Uppsala || 752 20 || || 59.8687 || 17.6083 || https://www.kyrkvinden.se || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen genom att förmedla och i egen regi eller genom samarbetspartner producera miljövänlig elkraft. || The purpose of the association is to promote the members' financial interests by conveying, on their own account or through partners, environmentally friendly electricity || || SWE || C61P
|-
| Ljusterö Vind ekonomiska förening || active || 2008-04-02 || 769618-5961 || LJUSTERÖ TORG || Ljusterö || 184 95 || || 59.52403 || 18.60869 || http://www.ljusterovind.se/ || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarnas ekonomiska intressen genom att i egen regi producera miljövänlig energi samt annan därmed förenlig verksamhet. Medlemmarna deltar i verksamheten som konsumenter. || The purpose of the association is to promote the members' financial interests by producing environmentally friendly energy and other related activities on their own behalf. The members participate in the business as consumers. || || SWE || C61P
|-
| Windy ekonomisk förening || active || 2000-12-11 || 769606-4802 || SVARTEDALSBACKEN 9 || Lerum || 443 39 || Mattias Skjöldebrandt || 57.76418 || 12.26767 || http://windy-vindkraft.se/ || wind onshore || 35.110 || Föreningen har till ändamål att främja medlemmarna ekonomiska intressen genom att tillhandahålla medlemmarna egen vindkraft- producerad el, därigenom också främjande medlemmarnas intresse för miljö och energihushållning samt bedriva därmed förenlig verksamhet. || The purpose of the association is to promote the members 'financial interests by providing the members with their own electricity produced by wind power, thereby also promoting the members' interest in the environment and energy management, and conducting compatible activities therewith. || || SWE || C61P
|}

The csv file contains information on the name of the initiatives, its legal status, its year of foundation, its national identifier, its street address, the city it is located in, the corresponding postal code, a possible C/O information, a latitude geo-information of the location (lat), a longitude geo-information of the location (lon), the website of the initiatives, some information for activities, a national industrial sector classification, a purpose statement in original language, the same purpose statement translated to English, the date of removal, the country code, and its legal form.
To relate metadata information to this information in the csv file, we create a second file containing this metadata. The file format for this metadata information file is json. Let us assume that the csv file itself has the filename "SWE_initiatives_sample.csv". According to the csv on the web standard, the metadata file should have the filename "SWE_initiatives_sample.csv-metadata.json". A minimal form of the metadata file contains the following information
<nowiki>
{
"@context": "http://www.w3.org/ns/csvw",
"url": "SWE_initiatives_sample.csv"
}
</nowiki>
The '''@context''' information links to the language conventions of the csvw standard, the '''url''' information states the filename of the csv file. This minimal file can be extended to contain more specific metadata. All entries are encoded in the form of property specifications and corresponding values.

==== General information about the csv file ====
In a first step, we include general information about the csv file. We start with a code snippet for specifics such as title, description, and creator
<nowiki>
{
"@context": "http://www.w3.org/ns/csvw",
"url": "SWE_initiatives_sample.csv"
"dc:title": "Example - list of citizen-led initiatives in Sweden",
"dc:description": "List of citizen-led initiatives in Sweden, example dataset to be used for illustrating the use of csv on the web",
"dc:creator": {
"schema:name": "August Wierling",
"schema:url": "https://orcid.org/0000-0002-7443-7593",
"schema:contactPoint": { "email": "augustw@hvl.no}
}
</nowiki>
As in the example above, property specifications can be terms from popular metadata vocabularies. E.g. the [https://www.dublincore.org/specifications/dublin-core/dces/ Dublin Core], [https://schema.org/ schema.org], or [https://www.w3.org/TR/vocab-dcat-2/ DCAT] vocabulary can be used. All of these vocabularies can be used independently or together. In the above example, metadata terms from the Dublin core vocabulary are mixed with terms from schema.org. The title of the csv file, and its description are stated using the Dublin core terms. The information inside of the dc:creator term contains information which in turn is specified using the schema.org vocabulary. Information about the creator is given in more detail specifying a human-readable name of the creator, a url of the creator (here: his orcid number), and contact point details such as the email. The contact point information can be extended using also a telephone or a fax number. We continue with a more extensive list of details about the file as a whole

<nowiki>
"@context": "http://www.w3.org/ns/csvw",
"url": "SWE_initiatives_sample.csv",
"dc:title": "Example - list of citizen-led initiatives in Sweden",
"dc:description": "List of citizen-led initiatives in Sweden, example dataset to be used for illustrating the use of csv on the web",
"dc:date": "2022-10-07",
"dc:format": "text/csv",
"dc:language": "en-US",
"dc:publisher": {
"schema:name": "EERAdata project",
"schema:url": "https://cordis.europa.eu/project/id/883823",
"schema:contactPoint": {
"email": "info@eeradata.eu",
"url": "https://www.eeradata.eu"
}
}
"dc:rights": "https://creativecommons.org/licenses/by-sa/4.0/",
"dc:subject": "Energy communities, Sweden, Community energy, Energy cooperatives, Renewable Energy",
"dc:source": {
"schema:name": "ENBP Inventory \"Energy by people\" - First Europe-wide inventory on energy communities",
"schema:url": "https://doi.org/10.18710/2CPQHQ"
},
"dc:type": "dataset",
"dc:creator": {
"schema:name": "August Wierling",
"schema:url": "https://orcid.org/0000-0002-7443-7593",
"schema:contactPoint": { "email": "augustw@hvl.no}
},
"dc:coverage": "Sweden",
"dc:identifier": "https://eeradata-platform.eu/"
</nowiki>

The date follows [https://en.wikipedia.org/wiki/ISO_8601 ISO 8601]. The language is specified following [https://www.ietf.org/rfc/rfc4646.txt RFC 4646]. For the media type, [https://www.rfc-editor.org/rfc/rfc7111 RFC 7111 ] has being used as a specification. The type is taken according to the [https://www.dublincore.org/specifications/dublin-core/dcmi-type-vocabulary/ DCMI type vocabulary]. The [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/elements11/publisher/ dc:publisher] information has several details which are grouped into one object by curly brackets: the [https://www.eeradata.eu/ EERAdata] project as the name of the publisher, the corresponding CORDIS entry as a persistent identifier, and contact information in form of an email and a website. The entry for [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/elements11/rights/ dc:rights] contains the license information and points to a website provided by the [https://en.wikipedia.org/wiki/Creative_Commons creative commons organization]. It states that the csv file is licensed under [https://creativecommons.org/licenses/by-sa/4.0/ Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)]. As such, anybody is free to share and adapt the file. The [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/elements11/rights/ dc:subject] contains a list of keywords describing the contents of the csv file in more details. The subject information should be more extensive in a real example. Here, only a basic example is given. The [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/elements11/type/ dc:type] information declares the csv file information as a dataset according to the possible types listed by the [https://www.dublincore.org/specifications/dublin-core/type-element/ DCMI type element working draft]. The [https://www.dublincore.org/specifications/dublin-core/dcmi-terms/#http://purl.org/dc/elements/1.1/identifier dc:identifier] holds as DCMI describes it an unambiguous reference to the resource within a given context. Ideally, the resource is the final FAIRified object. Thus, it does apply to the json file created out of the original csv file and its json metadata document. Best practice is to assign a [https://en.wikipedia.org/wiki/Persistent_identifier persistent identifier].

Now, how does this contribute to make the original csv FAIR fair ?

==== Specifying information about table headers ====

This section describes how to specify further the entries in the various columns of the csv file. Note that the csv on the web standard allow to connect the metadata file in json to several csv files which share certain layout. For our puroposes here, we focus on a single table - the one illustrated above with the information on Swedish energy coooperatives. Before describing a full-fletched description for all the columns, we start with the first four columns from the left specifying the name of the initiative, its legal status, the year of foundation, and a national identifier. We start with a simple set of specifications before assigning more information to the columns. For more information, please also see the primer as well as the recommendation itself.

<nowiki>
"tableSchema": {
"columns": [{
"titles": "name",
"dc:description": "Name of the initiative",
"datatype": "string",
"required": true
},{
"titles": "status",
"dc:description": "Legal status",
"datatype": {
"base": "string",
"format": "active|inactive|liquidation"
},
"required": true
},{
"titles": "year of foundation",
"dc:description": "Year of foundation of the initiative",
"datatype": "date"
},{
"titles": "national identifier",
"datatype": {
"propertyURL": "https://www.wikidata.org/wiki/Property:P6460",
"dc:title": "National identifier for Sweden",
"dc:description": "National identifier for Sweden",
"base": "string",
"format": "\d{6}-\d{4}"
}
</nowiki>

The general property for specific table attributes is ''tableSchema''. Details on the columns is specified by ''columns''. Per column, a title, a description and details about the datatype are fixed. For example, the first column has the title name and the dc:description entry gives further information on what name actually means. The datatype for all entries in the first column is string. For possible further pre-defined datatypes, see the [https://www.w3.org/TR/2015/REC-tabular-metadata-20151217/#fig-datatypes Metadata Vocabulary for Tabular Data]. The specification of true for ''required'' leads to an error message if the corresponding entry in the csv file is empty.
In the entry for the second column, the ''format'' properties list allowed entries for the values in the second column. If there is any entry other than active, inactive or liquidation, an error will be reported. The entries of the third column have the datatype date, so entries must comply with the [https://en.wikipedia.org/wiki/ISO_8601 ISO 8601] standard YYYY-MM-DD. Finally, the [https://www.wikidata.org/wiki/Property:P6460 national identifier for organizations in Sweden] is listed in the fourth column. It consists of 6 digits, followed by a dash, followed by another 4 digits. The ''format'' statements allows to specifies patterns of such type with the help of regular expressions as shown in the example. Indeed, the ''propertyURL'' ties each entry to the [https://www.wikidata.org/wiki/Property:P6460 wikidata entry P6460] and in that way defines that all entries are Swedish organizational numbers.

The next three columns contain street information and relate to the schema.org vocabulary to specify a street address, the name of the municipality and the postal code of the initiative. The corresponding entries for the metadata file are

<nowiki>
{
"titles": "Street address",
"dc:description": "Street address of the initiative",
"datatype": "string",
"propertyURL": "schema:streetAddress"
},{
"titles": "city",
"dc:description": "Municipality where the initiative is located",
"datatype": "string",
"propertyURL": "schema:streetLocality"
},{
"titles": "postal code",
"dc:description": "Postal code of the location of the initiative",
"datatype": "string",
"propertyURL": "schema:postalCode"
}
</nowiki>
Note that for the case of Sweden, the ''format'' property can further be used to define allowed patterns for street addresses and postal codes. The location of the headquarter of the initiative is reported also in terms of geo-coordinates in the csv file. The column entitled lat contains information on latitudes, while the column entitled lon holds longitudes. Here, schema.org provides also a possibility to link to standards

<nowiki>
{
"titles": "lat",
"dc:description": "geo location of headquarter of initiative, latitude, WGS84",
"datatype": {
"base": "number",
"minimum": "-90",
"maximum": "90"
},
"propertyURL": "schema:latitude"
}, {
"titles": "lon",
"dc:description": "geo location of headquarter of initiative, longitude, WGS84",
"datatype": {
"base": "number",
"minimum": "-180",
"maximum": "180"
},
"propertyURL": "schema:longitude"
}
</nowiki>

As can be seen form the example, CSVW allows to restrict values for a range of possibilities. Latitudes range between -90 and 90, latitudes between -180 and 180. Using the schema.org definition makes it implicitly clear, that the [https://en.wikipedia.org/wiki/World_Geodetic_System#WGS84 WGS84] standard is used to describe geo locations.

The next column contains a link to the web presence of the initiative. A minimal way to specify this would be again with the help of schema.org as

<nowiki>
{
"titles": "website",
"dc:description": "Link to the web presence of the initiative",
"propertyURL": "schema:url"
}
</nowiki>

The column entitled activity contains information about the activity of the initiative. From the general point of view, activities of citizen-led initiatives can be quite broad ranging from electricity and heat generation by different means to distribution activities and energy efficient measures. Again, the task is to find a resource on the web which allows expressing that all entries in this column are
activities. The makesOffer property provided by schema.org is a possibility to state this. According to its [https://schema.org/makesOffer definition], makesOffer describes 'A pointer to products or services offered by the organization or person.' The specification of the column reads

<nowiki>
{
"titles": "activity",
"dc:description": "Describes activitites by citizen-led energy initiatives",
"propertyURL": "schema:makesOffer"
}
</nowiki>

Note, that here it is suggested to use a controlled vocabulary from which of the different activities are sourced from.
More details will be discussed elsewhere.

The next column contains information specifying the national industrial sector classification which provides information about the type of activities the initiative is engaged with based on a classification of economic activities published by Statistics Sweden, see [https://www.scb.se/en/documentation/classifications-and-standards/swedish-standard-industrial-classification-sni/ here]. Note, that this information overlaps to some extent with the information offered in the activities column. However, the details which can be expressed in a domain-specific controlled vocabulary are usually much greater than the rather general classification scheme covering the whole national industry sector. On the other hand, initiatives may engage with activities, which are captured in the general scheme but are not contained in a domain-specific vocabulary. The Swedish Standard Industrial Classification is based on the EU’s recommended standards, NACE Rev.2. SNI 2007.
It allows however for more detailed specifications. The official codes for activity groups are designated as two digits separated by a dot from three digits. The example here is code 35.110 which encodes 'Production of electricity'.
Similar to the example discussed above, the format of the entry can be specified with the format statement

<nowiki>
{
"titles": "national industrial sector classification",
"datatype": {
"@type": "https://www.wikidata.org/wiki/Q2976602",
"dc:title": "Swedish Standard Industrial Classification",
"dc:description": "Swedish Standard Industrial Classification for activities by the citizen-led initiative",
"base": "string",
"format": "\d{2}\.\d{3}"
}
</nowiki>
While wikidata offers resources for the [NACE classification codes] and the [https://www.wikidata.org/wiki/Q100269151 Belgium classification code], no resource is available for the Swedish case. As a minimum, wikidata allows a resource for economic classification schemes, in general, using the resource [https://www.wikidata.org/wiki/Q2976602 wikidata:Q2976602]
or [https://www.wikidata.org/wiki/Q27048688 wikidata:Q27048688]. For describing that all values in a column are of a particular type, the csv on the web offers the statement @type. An alternative is offered here by DBpedia, which has a resource [https://dbpedia.org/page/Category:Industry_classifications dbr:International_Standard_Industrial_Classification] exactly providing what is given in the column of the csv file. Thus, the type can be specified as "@type": "dbr:International_Standard_Industrial_Classification".

The next two column describe the purpose statement of the initiative, both in the native language, i.e. Swedish, and in English. Following [https://www.w3.org/TR/tabular-data-primer/#column-language Example 96] from the Primer, this is specified with the lang property. According to [https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes ISO 639-1], the corresponding value for Swedish is sv. The fact that the entry itself is a corporate purpose statement can be expressed using the wikidata resource [https://www.wikidata.org/wiki/Q2498417 Q2498417].

<nowiki>
{
"titles": "purpose (original language)",
"@type": "wikidata:Q2498417",
"dc:description": "Purpose statement of the initiative in Swedish",
"lang": "sv"
}
</nowiki>

Additional specifications in terms of type can be given to the columns on the year of foundation and the year of dissolution. Here, schema.org provides a definition and the corresponding entries such as

<nowiki>
"propertyURL": "schema:foundingDate",
"propertyURL": "schema:dissolutionDate",
</nowiki>

would serve as a means of specification.

Query information about specific countries, it is helpful to have specific country information in the table as well. For that purpose, a column is contained in the csv file which contains a country identifier. The entries are sourced from the [https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3 ISO 3166 alpha-3] codes. wikidata offers the identifier
[https://www.wikidata.org/wiki/Property:P298 P298] to express that the entries are country codes.

<nowiki>
{
"titles": "country code",
"propertyURL": "wikidata:P298",
"dc:description": "Country where is initiative is located in"
}
</nowiki>

The last column contains information about the legal form of the initiative. Instead of documenting the legal form as a string, the legal form is specified as a code sourced from the [https://www.gleif.org/en Global Legal Entity Identifier Foundation GLEIF]. [https://www.gleif.org/en/about-lei/code-lists/iso-20275-entity-legal-forms-code-list This page] contains links to the ISO 20275-backed entity legal forms code list. Again, wikidata offers the property [https://www.wikidata.org/wiki/Property:P1454 wikidata:P1454] to specify that the entries are information on legal form. The corresponding entry for the metadata file looks

<nowiki>
{
"titles": "legal form",
"propertyURL": "wikidata:P1454",
"dc:description": "Legal form of the initiative documented with codes taken from ISO 20275"
}
</nowiki>

=== Worked example: Power plant information ===

In a second part of this tutorial, we consider data about power plants. Here, a list of wind farms from Germany serve as an example. The data is originally again organized as a csv file containing information such as the name of the power plant, the type of the power plant, a classification of the energy product used as input in the power plant, the location in terms of latitude and longitude, the nameplate
capacity, the commissioning year, the decommissioning year, and information on the owner of the power plant. The table here shows six different wind farms with the associated information.

{| class="wikitable"
! name || type || using energy product || latitude || longitude || nameplate capacity [kW] || commissioning date || decommissioning date || owner
|-
| Langwedel dritte || onshore wind farm || RA310 || 53.013274 || 9.158455 || 3050 || 2017-12-29 || || Bürger Energie Bremen
|-
| WEA Kammerberg || onshore wind farm || RA310 || 48.387257 || 11.518869 || 3000 || 2015-11-03 || || Bürger Energie Genossenschaft Freisinger Land
|-
| Windpark Söhrewald / Niestetal || onshore wind farm || RA310 || 51.241938 || 9.518432 || 21525 || 2015-09-19 || || Bürger Energie Kassel & Söhre
|-
| Windpark Rohrberg || onshore wind farm || RA310 || 51.23638 || 9.710966 || 15000 || 2016-03-23 || || Bürger Energie Kassel & Söhre
|-
| Windpark Stiftswald || onshore wind farm || RA310 || 51.245691 || 9.658835 || 27000 || 2017-06-28 || || Bürger Energie Kassel & Söhre
|-
| Windpark Kreuzstein || onshore wind farm || RA310 || 51.274447 || 9.730573 || 24000 || 2019-01-01 || || Bürger Energie Kassel & Söhre
|}

As before, the csv file is supplemented by metadata using a json metadata file. Following the naming convention of ...

In a first step, we again consider metadata which relate to the csv as a whole such as a creator of the file, access rights for the entire file etc. The corresponding part of the metadata file may look like this

<nowiki>
"@context": "http://www.w3.org/ns/csvw",
"url": "DEU_powerPlants_sample.csv",
"dc:title": "Example - list of power plants in Germany",
"dc:description": "List of power plants in Germany owned by citizen-led initiatives, example dataset to be used for illustrating the use of csv on the web",
"dc:date": "2022-10-27",
"dc:format": "text/csv",
"dc:language": "en-US",
"dc:publisher": {
"schema:name": "EERAdata project",
"schema:url": "https://cordis.europa.eu/project/id/883823",
"schema:contactPoint": {
"email": "info@eeradata.eu",
"url": "https://www.eeradata.eu"
}
}
"dc:rights": "https://creativecommons.org/licenses/by-sa/4.0/",
"dc:subject": "Energy communities, Germany, Community energy, Energy cooperatives, Renewable Energy, power plants",
"dc:source": {
"schema:name": "ENBP Inventory \"Energy by people\" - First Europe-wide inventory on energy communities",
"schema:url": "https://doi.org/10.18710/2CPQHQ"
},
"dc:type": "dataset",
"dc:creator": {
"schema:name": "August Wierling",
"schema:url": "https://orcid.org/0000-0002-7443-7593",
"schema:contactPoint": { "email": "augustw@hvl.no}
},
"dc:coverage": "Germany",
"dc:identifier": "https://eeradata-platform.eu/"
</nowiki>

As before, we continue by providing information about the contents of the columns in the csv file. We start with the name of the wind farm being listed in the first column. It can be referenced with schema:name which according to schema.org is a property assigning a 'name' to a 'thing'. Alternatively, here rdfs:label can be used for this purpose. The code snippet for describing the left most column would look like this:

<nowiki>
"tableSchema": {
"columns": [{
"titles": "name",
"dc:description": "Name of the power plant",
"datatype": "string",
"propertyURL": "schema:name"
}
]
}
</nowiki>

The second column contains information about the type of the power plant. There is a discussion comparing different resources for power plant types [https://eeradata-platform.eu/wiki/index.php?title=Example:_Standards_on_power_plants here]. Taking the results from this discussion, the wikidata resource [https://www.wikidata.org/wiki/Q50687555 wikidata:Q50687555] and/or the resource [http://openenergy-platform.org/ontology/oeo/OEO_00000311 oeo:OEO_00000311] offered the open energy ontology can be used to relate to. The corresponding entry to the metadata file may look this

<nowiki>
"titles": "type",
"dc:description": Type of the power plant",
"datatype": "string",
"@type": "oeo:OEO_00000311"
</nowiki>

The third column specifies more in detail the energy input to the power plant in terms of the [https://unstats.un.org/unsd/classifications/Family/Detail/2007 standard international energy product classicification]. A machine-actionable version of this classification is provided by [https://dd.eionet.europa.eu/vocabulary/eurostat/siec/view Eionet Data Dictionary]. The identifier RA310, which describes the "wind onshore" energy product, is located at this [http://dd.eionet.europa.eu/vocabulary/eurostat/siec/RA310 link]. More resources for vocabularies in the context of EU directives are
given [https://dd.eionet.europa.eu/vocabularies here]. Following Example 60 of the primer, the valueURL property can be used to automatically expand the entry from the 'using energy product' column into the corresponding resource, the

<nowiki>
"titles": "using energy product",
"dc:description": "Standard international energy product classification for the energy product used as input for the power plant",
"valueURL": "https://dd.eionet.europa.eu/vocabularyconcept/eurostat/siec/{using energy product}"
"propertyURL": "schema:identifier"
</nowiki>
There is no resource which actually allows to express that the entry is an identifier from the SIEC list. Instead, here a more general property is used. schema:identifier represents any kind of identifier for any kind of thing, so not specifying that it is an energy product.

For the geo information we have a similar way of expressing the metadata as in the example before

<nowiki>
{
"titles": "latitude",
"dc:description": "geo location of the position of a power plant, latitude, WGS84",
"datatype": {
"base": "number",
"minimum": "-90",
"maximum": "90"
},
"propertyURL": "schema:latitude"
}
</nowiki>

For the commissioning date, the entry looks like this

<nowiki>
"tableSchema": {
"columns": [{
"titles": "commissioning date",
"dc:description": "Commissioning date of the power plant",
"datatype": "date",
"propertyURL": "wikidata:P729"
}
]
}
</nowiki>
Here, the commissioning date is linked to the property wikidata:P729.

==== How to test the metadata document? ====

== Resources ==

* [https://www.w3.org/TR/tabular-data-primer/ CSV on the Web: A Primer]

* [https://www.stevenfirth.com/ Blog contributions by Steven Firth]

* [https://www.w3.org/TR/2015/REC-tabular-metadata-20151217/ Metadata Vocabulary for Tabular Data]

* [https://www.gov.uk/government/publications/recommended-open-standards-for-government/using-metadata-to-describe-csv-data Using metadata to describe CSV data]

* [https://www.w3.org/ns/csvw CSVW Namespace Vocabulary Terms]

* [https://medium.swirrl.com/how-to-publish-csv-on-the-web-csvw-4ea6cbb603b4 How to publish CSV-on-the-Web (CSVW)]

* [https://www.seachess.net/notes/dive-into-csvw/ Dive into CSV on the Web]

* [http://kerfors.blogspot.com/2015/04/csvw-for-tabular-clinical-trial-data.html CSVW for Tabular Clinical Trial Data and Metadata]