EERAdata Wiki - User contributions [en]

WS1UC3

2020-06-04T05:22:42Z

Karolinaj: /* Participants */

This page provides space for notes from workshop discussions of use case 3 during Day 2 of WS1.

== Interactive elements ==
The discussions can also benefit from considering the EERAdata storyboard and/or slido comments. See [[WS1#Interactive_elements]]

== Lessons learned during WS1 Day1 ==

# What is the take-home message for you?
## there is not an unique method to define metadata

# What do you suggest doing tomorrow?
## review different types of DBs trying to find a common line among them
## facilitate an open discussion about our own experience in the field

# Have you seen today best practices from other communities outside of your use-case?

== Notes from the morning session ==
The morning session is dedicated to database discussions with the aim to select 3-5 databases from below's list of databases for further examination. The [[UC3#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Participants ===

* Tim Austin (JRC)
* Ihssen Holger (EERA)
* Theodoros Dimepoulos (AIT)
* Karl Berger (AIT)
* Manfred Paier (AIT)
* Constantin V. Beck (HVL)
* Mehran Ziaabadi (HVL)
* Karolina Jąderko-Skubis (GIG)
* Francesco Buonocore (ENEA)
* Massimo Celino (ENEA)

=== Participants expertises ===

* The AIT group is working mainly in the field of PV, both from the point of view materials (low toxicity, usability, ...) and from the point of view of systems and module (engineering, efficiency, quality, ...). AIT is leading the development of the EERAdata platform, for this reason it is joining the session to discuss the use case needs.

* JRC is managing a large DB about structural materials. They pay a lot of attention to FAIR principle:
** access: not all the information in the DB are open. This helped private companies to provide and reuse data.
** interoperability: standardization procedures in collaboration with CEN.
** Reusability: this is related to quality issues. Reviewers or commettees are often involved in the definition of the quality level.

* Holger: he is working for a new project where data plays a fundamental role. It's about Materials Accelerated Platform (MAP). MAP has four components: modeling, robotics, experimental characterizations, artificial intelligence. There are already some working platforms in Europe and Canada, for example in the field of reduction of CO2. Other MAPs are about thermoelectricity, concrete and batteries (BIGMAP project in Germany).

* GIG has expertise in deep water protection but in general on environmental engineering

* HVL is here with expertises in COMET project (Constantin) and materials solution for wind (Mehran)
* ENEA has expertise in Computational Materials Science

=== Draft list of databases ===

{| class="wikitable"
|-
! Name of database !! Description !! Reasoning of choice
|-
| [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD] || Data coming from molecular modeling || It belongs to an HPC European Centre of Excellence
|-
| [http://www.matweb.com/ MATWEB] || MatWeb is a searchable database of engineering materials.The database includes thermoplastic and thermoset polymers, metals and alloys, ceramics, wood, fibers, stone, lubricants, inorganic salts, and other engineering materials. The database includes more than 100000 material data sheets || Highly recognizable and popular database directly related to materials. Most data sheets of materials are provided by manufacturers / industry suppliers.
|-
| [http://www.urbanmineplatform.eu/homepage Urban Mine Platform] || The ProSUM project has developed the open-access Urban Mine Platform (UMP). This dedicated web portal is populated by a centralised database containing all readily available data on market inputs, stocks in use and hibernated, compositions and waste flows of electrical and electronic equipment (EEE), vehicles and batteries (BATT) for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || Full access to the required data and information. Easy search. A rich set of metadata.
|-
| [https://odin.jrc.ec.europa.eu/alcor MatDB] || The European Commission JRC [https://odin.jrc.ec.europa.eu ODIN Portal] hosts a number of scientific databases, one of which is [https://odin.jrc.ec.europa.eu/alcor MatDB], which is a database application designed to store mechanical test data coming from tests performed in accordance with mechanical testing standards. The metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. provenance), material (i.e. production, heat treatment, microstructure, etc), specimen, test condition, documents and test result. The access management model supports both open access and restricted access. With a view to FAIR compliance, the database supports data citation (using the [https://datacite.org DataCite] framework) and interoperability standards for test data (hosted at [http://uri.cen.eu/cen CEN]). || MatDB supports various features aligned to the FAIR data principles, including data citation e.g. [https://doi.org/10.5290/2900001 Ruiz, A (2018): Nanoindentation (single cycle) test data for Gr. 91 material at 23 °C and maximum indenter force of 1.00332 mN, version 1.0, European Commission JRC] (for findability and access), interoperability standards for mechanical test data and quality assurance wokflows.
|-
| FactSage Browser Thermochemical Data || ||
|-
| NIST X-ray Photoelectron Spectroscopy (XPS) Database || ||
|-
| [http://www.aflow.org/ AFLOWLIB] || AflowLIB (Automatic Flow LIB) is a software framework for high-throughput calculation of crystal structure properties of alloys, intermetallics and inorganic compounds. || It is a rich database.
|-
| [http://oqmd.org/ OQMD] || The Open Quantum Materials Database (OQMD) is a high-throughput database currently consisting of nearly 300,000 density functional theory (DFT) total energy calculations of compounds from the Inorganic Crystal Structure Database (ICSD) and decorations of commonly occurring crystal structures. || It is a rich database.
|-
| [https://refractiveindex.info/ Database of refractive indices] || Complex refractive index of inorganic and organic materials ||
|-
|-
| [https://materialsproject.org/ Materials Project] || The Materials Project provides open web-based access to computed information on known and predicted materials as well as powerful analysis tools to inspire and design novel materials.||
|-
| [https://omdb.mathub.io/ Organic Materials Database] || The organic materials database is an open access electronic structure database for 3-dimensional organic crystals, developed and hosted at the Nordic Institute for Theoretical Physics – Nordita. It provides tools for search queries based on data-mining and machine learning techniques. ||
|-
| [http://crystallography.net/cod/ Crystallography Open Database] || Open-access database of crystal structures of organic, inorganic and metal–organic compounds and minerals. || It is a widely used and rich database for structural information on materials.
|-
| [https://ec.europa.eu/jrc/en/pvgis Photovoltaic Geographical Information System (PVGIS)] ||
JRC Ispra: Photovoltaic Geographical Information System (PVGIS) providing free and open access to:
* PV potential for different technologies and configurations of grid connected and stand alone systems.
* Solar radiation and temperature, as monthly averages or daily profiles.
* Full time series of hourly values of both solar radiation and PV performance.
* Typical Meteorological Year data for nine climatic variables.
* Maps, by country or region, of solar resource and PV potential ready to print.
* PVMAPS software includes all the estimation models used in PVGIS
||
|-
| [http://ckan.pearlpv-cost.eu EU COST Action Pearl PV (CA16235) Photovoltaic Geographical Information System (PVGIS)]
|| Established to publish and upload data of monitored installed PV systems and to quantitatively evaluate the long-term performance and reliability of these PV systems in Europe and elsewhere ||
|}

=== Discussion on the choice of databases: ===

* We should select DB covering different lenght scales (from microscopic to devices) and different applications (PV, WIND, others..).

* DBs should be select allowing interoperability among them, for example a DB on crystallography could be used with another that provides band structures and related properties.

* Valeria suggests to have a look to Critical Raw Materials [https://ec.europa.eu/growth/sectors/raw-materials/specific-interest/critical_en CRM]

* NOMAD is a very interesting DB but it is only about Computational Materials Science at the atomic scale. It is mainly focussed on ab-initio calculations. However there is an interesting ongoing activities in FAIRification. However some very popular computational DBs are already included in NOMAD

* MATWEB needs registration and it has a premium service. That's from engineers to engineers. Metadata are not rich.

* URBAN MINE PLATFORM has rich metadata, however dowload is not that easy. No registration is needed. Metadata information can be found [https://prosum.geology.cz/records/5a16be32-4660-46c3-b2c5-037a0a010854?detail=full&language=eng here]

== Notes from the afternoon session ==
The afternoon session is dedicated to discussing metadata for the selected databases. The aim of the afternoon session is to fill out [[UC3#Metadata_assessments|table 2 of the wiki page for the use case]] and to decide what to report back from the use case to the plenary session the next day (again, see the WIKI template for a suggested structure). Thus, at the end of the day, the WIKI page for the use case is complete.

* [[UC3#Metadata_assessments|table 2 of the wiki page for the use case]]

=== Details of FAIR criteria assessments ===
* MatDB
** F1. (meta)data are assigned a globally unique and eternally persistent identifier - ''yes, either a DataCite DOI or a (resolvable) database technical key'';
** F2. data are described with rich metadata - ''yes because the MatDB source entity extends to fields about the organisation, projects, data creators, etc.'';
** F3. (meta)data are registered or indexed in a searchable resource - ''yes, initially at DataCite, with records propagating to other metadata repositories such as the EU Open Data Portal, OpenAIRE and the JRC Data Catalogue'';
** F4. metadata specify the data identifier - ''yes in the circumstance that data are enabled for citation'';
** 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 - ;
** 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 - ;
** R1. meta(data) have a plurality of accurate and relevant attributes - ''yes in the circumstance that data are enabled for citation because the metadata are compliant with the DataCite v.4 metadata schema'';
** R1.1. (meta)data are released with a clear and accessible data usage license - ''yes in the circumstance that data are enabled for citation because the DataCite v.4 metadata schema includes a 'rights' field'';
** R1.2. (meta)data are associated with their provenance - ''yes because the MatDB source entity includes fields about the organisation, projects, data creators, etc.'';
** R1.3. (meta)data meet domain-relevant community standards - ''yes in the circumstance that data are enabled for citation because the DataCite v.4 metadata schema is aligned to Dublin Core''.

== What to report back to the plenary on Day 3? ==
* Databases selected (names and short reasoning)

* Main insights from discussions:
** Metadata are tightly linked with the expertise in the field.
** there is not a unique definition of metadata: bibliography metadata (Tim) or everything is metadata (NOMAD) ??
** There are no standards
** Tim was pointing out that interoperability is really an issue
** The data that are available are increasing every day. This implies cost issues both to manage them and to analyze them. What can be done for this? Quality ?? political indications ?? standards ??

* Suggested next steps
** To have a deeper look at the metadata of the chosen DBs
** To figure out if there are links with other use cases
** To know EERA JPs activities to understand if materials are considered and which are the metadata of their interest

* Other issues

UC3

2020-06-03T14:08:59Z

Karolinaj: /* Metadata assessments */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| NOMAD || Data coming from molecular modeling, with a particular focus on ab-initio calculations || It belongs to an HPC European Centre of Excellence. There are ongoing projects to improve matadata || ||
|-
| [https://odin.jrc.ec.europa.eu/alcor MATDB] || The European Commission JRC [https://odin.jrc.ec.europa.eu ODIN Portal] hosts a number of scientific databases, one of which is [https://odin.jrc.ec.europa.eu/alcor MatDB], which is a database application designed to store mechanical test data coming from tests performed in accordance with mechanical testing standards. The metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. provenance), material (i.e. production, heat treatment, microstructure, etc), specimen, test condition, documents and test result. The access management model supports both open access and restricted access. With a view to FAIR compliance, the database supports data citation (using the [https://datacite.org DataCite] framework) and interoperability standards for test data (hosted at [http://uri.cen.eu/cen CEN]). || || MatDB supports various features aligned to the FAIR data principles, including data citation e.g. [https://doi.org/10.5290/2900001 Ruiz, A (2018): Nanoindentation (single cycle) test data for Gr. 91 material at 23 °C and maximum indenter force of 1.00332 mN, version 1.0, European Commission JRC] (for findability and access), interoperability standards for mechanical test data and quality assurance workflows for reuse.
||
|-
| [http://www.urbanmineplatform.eu/homepage Urban Mine Platform] || This Urban Mine Platform provides all readily available data on products put on the market, stocks, composition and waste flows for electrical and electronic equipment (EEE), vehicles and batteries for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || The Platform provides full access to the required data and information. A rich set of metadata. Includes a centralised database containing all readily available data. It is an open dataset that almost meets FAIR criteria. || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || R1.1. improving the related area in order to obtain a clear and accessible licence to use the data. F.4 and A.2. - the lack of a clear answer suggests a need to improve information in this area. For consideration F1: (Meta) data are assigned globally unique and persistent identifiers – there is just URL, could be DOI?
|-
| [https://ec.europa.eu/jrc/en/pvgis Photovoltaic Geographical Information System (PVGIS)] || Open-access database of crystal structures of organic, inorganic and metal–organic compounds and minerals. || It is a widely used and rich database for structural information on materials. || ||
|-
| [http://crystallography.net/cod/ Crystallography Open Database] || JRC Ispra: Photovoltaic Geographical Information System (PVGIS) providing free and open access to:
* PV potential for different technologies and configurations of grid connected and stand alone systems.
* Solar radiation and temperature, as monthly averages or daily profiles.
* Full time series of hourly values of both solar radiation and PV performance.
* Typical Meteorological Year data for nine climatic variables.
* Maps, by country or region, of solar resource and PV potential ready to print.
* PVMAPS software includes all the estimation models used in PVGIS
|| || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is a combination of the the test result + material (i.e. production, composition, heat treatment, microstructure, etc.) + specimen + test condition + documents entities, the source (i.e. bibliographic and provenance) entity corresponds to the metadata. || Approximately twenty metadata fields exist, noting that not all are mandatory. || F1 + F2 + F4 + F4 - YES; A1 + A2 - YES; I.1 + I.2 + I.3 - PARTIALLY; R1 + R1.3 + R1.1 + R1.2 - YES, details at [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1UC3#Notes_from_the_afternoon_session WS1UC3 - Notes from afternoon session ] || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Descriptive, structural, provenance of data||Extensive metadata||F 100%, A 80%, I 80%, R 80 %|| Onthology || Metadata stored as json
|-
| [http://www.urbanmineplatform.eu/homepage Urban Mine Platform] || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Taxonomy || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Single 7-digit identifier assigned to the data. A full history of data additions and changes is provided (with dates, commiters, modified files, etc) || Example || Data comply with the FAIR criteria. The Interoperability cannot be fully evaluated. || Example || RDF file
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T14:07:47Z

Karolinaj: /* List of selected databases */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| NOMAD || Data coming from molecular modeling, with a particular focus on ab-initio calculations || It belongs to an HPC European Centre of Excellence. There are ongoing projects to improve matadata || ||
|-
| [https://odin.jrc.ec.europa.eu/alcor MATDB] || The European Commission JRC [https://odin.jrc.ec.europa.eu ODIN Portal] hosts a number of scientific databases, one of which is [https://odin.jrc.ec.europa.eu/alcor MatDB], which is a database application designed to store mechanical test data coming from tests performed in accordance with mechanical testing standards. The metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. provenance), material (i.e. production, heat treatment, microstructure, etc), specimen, test condition, documents and test result. The access management model supports both open access and restricted access. With a view to FAIR compliance, the database supports data citation (using the [https://datacite.org DataCite] framework) and interoperability standards for test data (hosted at [http://uri.cen.eu/cen CEN]). || || MatDB supports various features aligned to the FAIR data principles, including data citation e.g. [https://doi.org/10.5290/2900001 Ruiz, A (2018): Nanoindentation (single cycle) test data for Gr. 91 material at 23 °C and maximum indenter force of 1.00332 mN, version 1.0, European Commission JRC] (for findability and access), interoperability standards for mechanical test data and quality assurance workflows for reuse.
||
|-
| [http://www.urbanmineplatform.eu/homepage Urban Mine Platform] || This Urban Mine Platform provides all readily available data on products put on the market, stocks, composition and waste flows for electrical and electronic equipment (EEE), vehicles and batteries for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || The Platform provides full access to the required data and information. A rich set of metadata. Includes a centralised database containing all readily available data. It is an open dataset that almost meets FAIR criteria. || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || R1.1. improving the related area in order to obtain a clear and accessible licence to use the data. F.4 and A.2. - the lack of a clear answer suggests a need to improve information in this area. For consideration F1: (Meta) data are assigned globally unique and persistent identifiers – there is just URL, could be DOI?
|-
| [https://ec.europa.eu/jrc/en/pvgis Photovoltaic Geographical Information System (PVGIS)] || Open-access database of crystal structures of organic, inorganic and metal–organic compounds and minerals. || It is a widely used and rich database for structural information on materials. || ||
|-
| [http://crystallography.net/cod/ Crystallography Open Database] || JRC Ispra: Photovoltaic Geographical Information System (PVGIS) providing free and open access to:
* PV potential for different technologies and configurations of grid connected and stand alone systems.
* Solar radiation and temperature, as monthly averages or daily profiles.
* Full time series of hourly values of both solar radiation and PV performance.
* Typical Meteorological Year data for nine climatic variables.
* Maps, by country or region, of solar resource and PV potential ready to print.
* PVMAPS software includes all the estimation models used in PVGIS
|| || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is a combination of the the test result + material (i.e. production, composition, heat treatment, microstructure, etc.) + specimen + test condition + documents entities, the source (i.e. bibliographic and provenance) entity corresponds to the metadata. || Approximately twenty metadata fields exist, noting that not all are mandatory. || F1 + F2 + F4 + F4 - YES; A1 + A2 - YES; I.1 + I.2 + I.3 - PARTIALLY; R1 + R1.3 + R1.1 + R1.2 - YES, details at [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1UC3#Notes_from_the_afternoon_session WS1UC3 - Notes from afternoon session ] || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Descriptive, structural, provenance of data||Extensive metadata||F 100%, A 80%, I 80%, R 80 %|| Onthology || Metadata stored as json
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Taxonomy || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Single 7-digit identifier assigned to the data. A full history of data additions and changes is provided (with dates, commiters, modified files, etc) || Example || Data comply with the FAIR criteria. The Interoperability cannot be fully evaluated. || Example || RDF file
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T14:06:36Z

Karolinaj: /* List of selected databases */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| NOMAD || Data coming from molecular modeling, with a particular focus on ab-initio calculations || It belongs to an HPC European Centre of Excellence. There are ongoing projects to improve matadata || ||
|-
| MATDB || The European Commission JRC [https://odin.jrc.ec.europa.eu ODIN Portal] hosts a number of scientific databases, one of which is [https://odin.jrc.ec.europa.eu/alcor MatDB], which is a database application designed to store mechanical test data coming from tests performed in accordance with mechanical testing standards. The metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. provenance), material (i.e. production, heat treatment, microstructure, etc), specimen, test condition, documents and test result. The access management model supports both open access and restricted access. With a view to FAIR compliance, the database supports data citation (using the [https://datacite.org DataCite] framework) and interoperability standards for test data (hosted at [http://uri.cen.eu/cen CEN]). || || MatDB supports various features aligned to the FAIR data principles, including data citation e.g. [https://doi.org/10.5290/2900001 Ruiz, A (2018): Nanoindentation (single cycle) test data for Gr. 91 material at 23 °C and maximum indenter force of 1.00332 mN, version 1.0, European Commission JRC] (for findability and access), interoperability standards for mechanical test data and quality assurance wokflows.
||
|-
| [http://www.urbanmineplatform.eu/homepage Urban Mine Platform] || This Urban Mine Platform provides all readily available data on products put on the market, stocks, composition and waste flows for electrical and electronic equipment (EEE), vehicles and batteries for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || The Platform provides full access to the required data and information. A rich set of metadata. Includes a centralised database containing all readily available data. It is an open dataset that almost meets FAIR criteria. || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || R1.1. improving the related area in order to obtain a clear and accessible licence to use the data. F.4 and A.2. - the lack of a clear answer suggests a need to improve information in this area. For consideration F1: (Meta) data are assigned globally unique and persistent identifiers – there is just UML, could be DOI?
|-
| [https://ec.europa.eu/jrc/en/pvgis Photovoltaic Geographical Information System (PVGIS)] || Open-access database of crystal structures of organic, inorganic and metal–organic compounds and minerals. || It is a widely used and rich database for structural information on materials. || ||
|-
| [http://crystallography.net/cod/ Crystallography Open Database] || JRC Ispra: Photovoltaic Geographical Information System (PVGIS) providing free and open access to:
* PV potential for different technologies and configurations of grid connected and stand alone systems.
* Solar radiation and temperature, as monthly averages or daily profiles.
* Full time series of hourly values of both solar radiation and PV performance.
* Typical Meteorological Year data for nine climatic variables.
* Maps, by country or region, of solar resource and PV potential ready to print.
* PVMAPS software includes all the estimation models used in PVGIS
|| || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is a combination of the the test result + material (i.e. production, composition, heat treatment, microstructure, etc.) + specimen + test condition + documents entities, the source (i.e. bibliographic and provenance) entity corresponds to the metadata. || Approximately twenty metadata fields exist, noting that not all are mandatory. || F1 + F2 + F4 + F4 - YES; A1 + A2 - YES; I.1 + I.2 + I.3 - PARTIALLY; R1 + R1.3 + R1.1 + R1.2 - YES, details at [http://eeradata.webfactional.com/mediawiki-1.30.0/index.php?title=WS1UC3#Notes_from_the_afternoon_session WS1UC3 - Notes from afternoon session ] || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Descriptive, structural, provenance of data||Extensive metadata||F 100%, A 80%, I 80%, R 80 %|| Onthology || Metadata stored as json
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Taxonomy || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Single 7-digit identifier assigned to the data. A full history of data additions and changes is provided (with dates, commiters, modified files, etc) || Example || Data comply with the FAIR criteria. The Interoperability cannot be fully evaluated. || Example || RDF file
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T13:40:18Z

Karolinaj: /* List of selected databases */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| NOMAD || || || ||
|-
| MATDB || || || ||
|-
| Urban Mine Platform || This Urban Mine Platform provides all readily available data on products put on the market, stocks, composition and waste flows for electrical and electronic equipment (EEE), vehicles and batteries for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || The Platform provides full access to the required data and information. A rich set of metadata. Includes a centralised database containing all readily available data. It is an open dataset that almost meets FAIR criteria. || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || R1.1. improving the related area in order to obtain a clear and accessible licence to use the data. F.4 and A.2. - the lack of a clear answer suggests a need to improve information in this area. For consideration F1: (Meta) data are assigned globally unique and persistent identifiers – there is just UML, could be DOI?
|-
| PVGIS || || || ||
|-
| Crystallography Open Database || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is a combination of the the test result + material (i.e. production, composition, heat treatment, microstructure, etc.) + specimen + test condition + documents entities, the source (i.e. bibliographic and provenance) and documents entities correspond to the metadata. || Approximately twenty metadata fields exist, noting that not all are mandatory. || F1 + F2 + F4 + F4 yes in the circumstance that the data are enabled for citation; A1 + A2 yes in the circumstance that the data are enabled for citation; I.1 + I.2 + I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1 + R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Descriptive, structural, provenance of data||Extensive metadata||F 100%, A 80%, I 80%, R 80 %|| Onthology || Metadata stored as json
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Taxonomy || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Single 7-digit identifier assigned to the data. A full history of data additions and changes is provided (with dates, commiters, modified files, etc) || Example || Data comply with the FAIR criteria. The Interoperability cannot be fully evaluated. || Example || RDF file
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T13:09:58Z

Karolinaj: /* List of selected databases */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| Urban Mine Platform || This Urban Mine Platform provides all readily available data on products put on the market, stocks, composition and waste flows for electrical and electronic equipment (EEE), vehicles and batteries for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || The Platform provides full access to the required data and information. A rich set of metadata. Includes a centralised database containing all readily available data. It is an open dataset that almost meets FAIR criteria. || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is a combination of the the test result + material (i.e. production, composition, heat treatment, microstructure, etc.) + specimen + test condition + documents entities, the metadata corresponds to the source entity (i.e. bibliographic and provenance) and documents. || Approximately 20 metadata fields exist, noting that a subset are mandatory. || F1 + F2 + F4 + F4 yes in the circumstance that the data are enabled for citation; A1 + A2 yes in the circumstance that the data are enabled for citation; I.1+I.2+I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1+R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Descriptive, structural, provenance of data||Extensive metadata||F 100%, A 80%, I 80%, R 80 %|| Onthology || Metadata stored as json
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Taxonomy || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Example || Example || Example || Example || Example
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T13:08:33Z

Karolinaj: /* List of selected databases */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| Urban Mine Platform || This Urban Mine Platform provides all readily available data on products put on the market, stocks, composition and waste flows for electrical and electronic equipment (EEE), vehicles and batteries for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || The Platform provides full access to the required data and information. A rich set of metadata. Includes a centralised database containing all readily available data. It is an open dataset that almost meets FAIR criteria. || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is a combination of the the test result + material (i.e. production, composition, heat treatment, microstructure, etc.) + specimen + test condition + documents entities, the metadata corresponds to the source entity (i.e. bibliographic and provenance) and documents. || Approximately 20 metadata fields exist, noting that a subset are mandatory. || F1 + F2 + F4 + F4 yes in the circumstance that the data are enabled for citation; A1 + A2 yes in the circumstance that the data are enabled for citation; I.1+I.2+I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1+R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Descriptive, structural, provenance of data||Extensive metadata||F 100%, A 80%, I 80%, R 80 %|| Onthology || Metadata stored as json
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Taxonomy || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Example || Example || Example || Example || Example
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T13:04:37Z

Karolinaj: /* List of selected databases */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| Urban Mine Platform || This Urban Mine Platform provides all readily available data on products put on the market, stocks, composition and waste flows for electrical and electronic equipment (EEE), vehicles and batteries for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is a combination of the the test result + material (i.e. production, composition, heat treatment, microstructure, etc.) + specimen + test condition + documents entities, the metadata corresponds to the source entity (i.e. bibliographic and provenance) and documents. || Approximately 20 metadata fields exist, noting that a subset are mandatory. || F1 + F2 + F4 yes, F3 not; A1 + A2 yes, the latter as a consequence of the bibliographic metadata being hosted at the DataCite server; I.1+I.2+I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1+R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Descriptive, structural, provenance of data||Extensive metadata||F 100%,A 80%, I 80%, R 80 %|| Onthology || Metadata stored as json
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Taxonomy || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Example || Example || Example || Example || Example
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T12:58:22Z

Karolinaj: /* Metadata assessments */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is the test result, the accompanying metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. bibliographic and provenance), material (i.e. production, composition, heat treatment, microstructure, etc.), specimen, test condition and documents. || Extensive metadata for each of the mentioned entities. || F1+F2+F4 yes, F3 not; A1 yes, A2 N/A because data (test result entity) and metadata (all other entities) are tightly coupled; I.1+I.2+I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1+R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Example || Example || Example || Example || Example
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Taxonomy || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Example || Example || Example || Example || Example
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T12:55:28Z

Karolinaj: /* Metadata assessments */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is the test result, the accompanying metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. bibliographic and provenance), material (i.e. production, composition, heat treatment, microstructure, etc.), specimen, test condition and documents. || Extensive metadata for each of the mentioned entities. || F1+F2+F4 yes, F3 not; A1 yes, A2 N/A because data (test result entity) and metadata (all other entities) are tightly coupled; I.1+I.2+I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1+R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Example || Example || Example || Example || Example
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Findable: F.1.; F.2.; F.3. – YES. F.4. – N/A. Accessible: A.1.; A.1.1.; A.1.2. – YES; A.2. – N/A. Interoperable: I.1.; I.2.; I.3. – YES; Reusable: R.1.; R.1.1.; R.1.2.; R.1.3 – YES || Example || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Example || Example || Example || Example || Example
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T12:46:09Z

Karolinaj: /* Metadata assessments */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is the test result, the accompanying metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. bibliographic and provenance), material (i.e. production, composition, heat treatment, microstructure, etc.), specimen, test condition and documents. || Extensive metadata for each of the mentioned entities. || F1+F2+F4 yes, F3 not; A1 yes, A2 N/A because data (test result entity) and metadata (all other entities) are tightly coupled; I.1+I.2+I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1+R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Example || Example || Example || Example || Example
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Example || Example || XML file
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Example || Example || Example || Example || Example
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T12:42:55Z

Karolinaj: /* Metadata assessments */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is the test result, the accompanying metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. bibliographic and provenance), material (i.e. production, composition, heat treatment, microstructure, etc.), specimen, test condition and documents. || Extensive metadata for each of the mentioned entities. || F1+F2+F4 yes, F3 not; A1 yes, A2 N/A because data (test result entity) and metadata (all other entities) are tightly coupled; I.1+I.2+I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1+R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Example || Example || Example || Example || Example
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Extensive metadata is provided in form of basic metadata and full metadata || Example || Example || Example
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Example || Example || Example || Example || Example
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

UC3

2020-06-03T12:40:51Z

Karolinaj: /* Metadata assessments */

== Material solutions for low carbon energy ==
=== General description of use case ===
The European Union has prioritized materials as a Key Enabling Technology (KET) to enable the transition to a knowledge-based, low carbon, resource-efficient economy and has proposed a materials roadmap to address the technology agenda of the SET-Plan. With the imperative to change the energy technology mix to respond to the challenges of decarbonization and security of energy supply, the need for new materials and processing routes is overriding. New efficient and cost-competitive energy technologies are urgently needed. In this respect, materials research and control over materials resources are becoming increasingly important in the current global competition for industrial leadership in low carbon technologies. Two EERA Joint Programs (Nuclear Materials and AMPEA) are directly involved in materials research for energy applications and several other Joint Programs are interested in new materials to improve the efficiency of energy technologies. To speed-up the discovery of new materials for energy technologies, Innovation Challenge No. 6 of the Mission Innovation Initiative is devoted to the discovery of new materials. This Innovation Challenge aims at accelerating the innovation process for high performance, low-cost clean energy materials and automating the processes needed to integrate these materials into new technologies. The challenge is to combine advanced theoretical and applied physical chemistry/materials science data, as well as data on the life cycle of materials and material compounds with next-generation computing infrastructures, artificial intelligence, and robotics tools. The goal is to create a fully integrated approach.

Materials research is characterized by strong multidisciplinary research in which both, converging technologies and cooperation, should be exploited to speed up application-oriented research activities. This is not always the case due to the extremely different technological fields where materials are employed (in the energy sector and beyond). Indeed, each technological field has often developed its own terminology, experimental set-ups, research procedures, and, consequently, its own standards in data management. Therefore, it can be argued that in the field of materials for energy data the state of the art is the following: Openness is low to medium, re-usability is low to medium, and barriers are high. Finally, actions put in place are rare (low to medium). The availability of an open data infrastructure covering as many research fields as possible could increase opportunities to develop new research programs, defragment the materials for energy communities, avoid the duplication of research activities, speed-up the discovery of materials, and increase the understanding of how energy systems could better benefit from existing and new materials. Many databases are already available but a large amount of data is currently produced in laboratories, not organized to be shared. Moreover, databases do not follow common formats preventing inter-operability and re-usability. In view of the intended automatization, it is important that access to databases is machine-actionable. Finally, due to the strong connection with industries, questions of open data access need to be explored and new business models need to be developed.

== Database of interest ==

List of databases related to WP6
* JRC: structural materials, raw materials and nanomaterials for health, https://data.jrc.ec.europa.eu/ , Contact point: Tim Austin
* NOMAD, European Centre of Excellence, https://nomad-coe.eu/ Contact point: Luca Ghiringhelli
* Urban Mine Platform (waste from electronics, vehicles, batteries etc) http://www.urbanmineplatform.eu/homepage
* ProQuest, https://www.proquest.com/
* MatWeb, http://www.matweb.com/
* AZOmaterials, https://www.azom.com/
* Crystallography Open Database, http://www.crystallography.net/cod/
* ChemSpider, http://www.chemspider.com/
* MaterialDistrict (match-making platform), https://materialdistrict.com/
* Open Materials Database, http://openmaterialsdb.se/
* phase diagrams http://www.crct.polymtl.ca/fact/documentation/
* xps https://srdata.nist.gov/xps/main_search_menu.aspx
* Automatic Flow for Materials Discovery (AFLOWLIB) http://www.aflowlib.org/
* Open Quantum Materials Database (OQMD), http://oqmd.org/
* Computational 2D Materials Database (C2DB) http://c2db.fysik.dtu.dk/
* MATDAT, https://www.matdat.com/
* Materials Connexion, https://www.materialconnexion.com/
* Materials web , https://www.materialsweb.org/

== Networks ==

* EMIRI (The Energy Materials Industrial Research Initivative), Simon Perraud
* EUMAT (European Technology Platform for Advanced Materials), Amaya Igartua
* EMMC ASBL (European Materials Modeling Council), Nadja Adamovic & Gerhard Goldbeck
* MARVEL , Nicola Marzari or Giovanni Pizzi (GoFAIR)
* Materials Genome (USA), Stefano Curtarolo (Duke)
* NOMAD (GoFAIR)

* EERA JPs
** AMPEA
** Nuclear Materials
** Photovoltaics
** Energy Storage
** Fuel Cells and Hydrogen
** Wind

== METADATA ==

* Findable: unique names, human-readable descriptions
* Accessible: URL, accessible via API
* Interoperable: typed, extensible schema → ontologies
* Reusable: hierarchical schema → data-analytics

An ontology is
{| class="wikitable"
|-
| a formal machine || readable
|-
| representation || concepts, properties, relations, functions,
|-
| constraints, || axioms are explicitly defined
|-
| of the knowledge || domain specific
|-
| of a community || consensual
|-
| for a purpose || (competency) question driven
|}

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC3]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC3]].
|| What FAIR/O target was decided?
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|-
| DB1 || || || ||
|}

== Metadata assessments ==
Databases above were assessed with respect to their current meta practices. The table below summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC3]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| MATDB || Noting that the primary data object is the test result, the accompanying metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. bibliographic and provenance), material (i.e. production, composition, heat treatment, microstructure, etc.), specimen, test condition and documents. || Extensive metadata for each of the mentioned entities. || F1+F2+F4 yes, F3 not; A1 yes, A2 N/A because data (test result entity) and metadata (all other entities) are tightly coupled; I.1+I.2+I.3 met partially because the interoperability standards are presently under development (with definitions hosted at http://uri.cen.eu/cen) and not all mechanical test types are yet covered; R1+R1.3 are met in the circumstance tests performed in accordance with protocols i.e. procedural testing standards, R1.1 yes where data sets are enabled for citation, R1.2 yes || Thesaurus and procedural standards || XML, PDF, MS Excel
|-
| NOMAD || Example || Example || Example || Example || Example
|-
| Urban Mine Platform || Metadata includes: administrative (e.g. contact info), descriptive (e.g. use limitation, data quality statement), provenance (e.g. resource), structural and others like file identifier, descriptive keywords etc. || Example || Example || Example || Example
|-
| PVGIS || Example || Example || Example || Example || Example
|-
| Crystallography Open DB || Example || Example || Example || Example || Example
|}

== GOFAIR implementation projects ==

* [https://www.go-fair.org/implementation-networks/overview/nomad/ NOMAD]
* [https://www.go-fair.org/implementation-networks/overview/materials-cloud/ Materials Cloud]

== Conferences ==

==== [https://th.fhi-berlin.mpg.de/meetings/fairdi2020/index.php?n=Meeting.Home Virtual Conference on A FAIR Data Infrastructure For Materials Genomics 3 - 5 June, 2020] ====
* The focus of the conference is to describe the new horizons that can be reached by a FAIR data infrastructure for materials genomics. This conference is organized by the association FAIR-DI e.V.
* Notable groups participating we should link with: [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD Center of Excellence], [https://th.fhi-berlin.mpg.de/groups/bdafms/ BIG-DATA ANALYTICS FOR MATERIALS SCIENCE]
* Existing metadata or other standards we should have in mind and link with: [https://fairdi.eu/ FAIR-DI e.V]; [https://www.optimade.org/ OPTIMADE Consortium].

== Literature ==

* Data-Driven Materials Science: Status, Challenges, and Perspectives. Lauri Himanen, Amber Geurts, Adam Stuart Foster, and Patrick Rinke. Adv Sci 2019.
* [https://www.nature.com/articles/s41524-017-0048-5 Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats]. Luca M. Ghiringhelli, Christian Carbogno, Sergey Levchenko, Fawzi Mohamed, Georg Huhs, Martin Lüders, Micael Oliveira & Matthias Scheffler. npj Computational Materials volume 3, Article number: 46 (2017).
* FAIR from GOFAIR website: [https://www.go-fair.org/fair-principles/ GOFAIR]
* FAIRification process from GOFAIR website: [https://www.go-fair.org/fair-principles/fairification-process/ GOFAIR]
* Wang, S. (2016) Green practices are gendered: Exploring gender inequality caused by sustainable consumption policies in Taiwan; Energy Research & Social Science, 18, 88-95. [[https://doi.org/10.1016/j.erss.2016.03.005]]. ''Abstract:'' In the context of climate change, governments and international organizations often promote a “sustainable lifestyle.” However, this approach has been criticized for underestimating the complexity of everyday life and therefore being inapplicable to households and consumers. In addition, procedures for promoting sustainable consumption seldom incorporate domestic workers’ opinions and often increase women’s housework loads. This article employs a practice-based approach to examine the “Energy-Saving, Carbon Reduction” movement, a series of sustainable consumption policies that have been advocated by the Taiwanese government since 2008. The goal of the movement is to encourage an eco-friendly lifestyle. On the basis of empirical data collected through ethnographic interviews, this article argues that existing policies unexpectedly increase women’s burdens and exacerbate gender inequality.
* Ly, L. T. et al. (2015) Compliance monitoring in business processes: Functionalities, application, and tool-support, Information Systems 54, 209-234, [https://www.sciencedirect.com/science/article/pii/S0306437915000459?via%3Dihub]. ''Abstract'': In recent years, monitoring the compliance of business processes with relevant regulations, constraints, and rules during runtime has evolved as major concern in literature and practice. Monitoring not only refers to continuously observing possible compliance violations, but also includes the ability to provide fine-grained feedback and to predict possible compliance violations in the future. The body of literature on business process compliance is large and approaches specifically addressing process monitoring are hard to identify. Moreover, proper means for the systematic comparison of these approaches are missing. Hence, it is unclear which approaches are suitable for particular scenarios. The goal of this paper is to define a framework for Compliance Monitoring Functionalities (CMF) that enables the systematic comparison of existing and new approaches for monitoring compliance rules over business processes during runtime. To define the scope of the framework, at first, related areas are identified and discussed. The CMFs are harvested based on a systematic literature review and five selected case studies. The appropriateness of the selection of CMFs is demonstrated in two ways: (a) a systematic comparison with pattern-based compliance approaches and (b) a classification of existing compliance monitoring approaches using the CMFs. Moreover, the application of the CMFs is showcased using three existing tools that are applied to two realistic data sets. Overall, the CMF framework provides powerful means to position existing and future compliance monitoring approaches.

WS1UC3

2020-06-03T11:18:12Z

Karolinaj: /* Draft list of databases */

This page provides space for notes from workshop discussions of use case 3 during Day 2 of WS1.

== Interactive elements ==
The discussions can also benefit from considering the EERAdata storyboard and/or slido comments. See [[WS1#Interactive_elements]]

== Lessons learned during WS1 Day1 ==

# What is the take-home message for you?
# What do you suggest doing tomorrow?
# Have you seen today best practices from other communities outside of your use-case?

== Notes from the morning session ==
The morning session is dedicated to database discussions with the aim to select 3-5 databases from below's list of databases for further examination. The [[UC3#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

* Participants: Tim Austin (JRC), Ihssen Holger (EERA), Theodoros Dimepoulos (AIT), Karl Berger (AIT), Manfred Paier (AIT), Constantin V. Beck (HVL), Mehran Ziaabadi (HVL), Karolina Jadeiko-Skubes (GIG), Francesco Buonocore (ENEA), MAssimo Celino (ENEA)

* Valeria suggests to have a look to Critical Raw MAterials [https://ec.europa.eu/growth/sectors/raw-materials/specific-interest/critical_en CRM]

* NOMAD is a very interesting DB but it is only about Computational MAterials Science, focussed on ab-initio calculations. However there is an interesting ongoing activities in FAIRification.

* We should select DB covering differet lenght scales (from microscopic to devices) and different applications (PV, others..).

* DBs should select allowing interoperability among them, for example a DB on crystallography could be used with another that provides band structures and related properties.

* The AIT group is working mainly in the field of PV, both from the point of view materials (low toxicity, usability, ...) and from the point of view of systems and module (engineering, efficiency, quality, ...)

* JRC is managing a large DB about structural materials. They pay a lot of attention to FAIR principle:
** access: not all the information in the DB are open. This helped private company to provide and reuse data
** interoperability: standardization procedures in collaboration with CEN.
** Reusability: this is related to quality issue. Reviewers or commettees are involved in the definition of the quality level.

* Holger: he is working for a new project where data plays a fundamental role. It's about Materials Accelerated Platform (MAP). MAP has 4 sections: modeling, robotics, experimental characterizations, artificial intelligence. There are already some working in Europe and Canada, for example in the field of reductino of CO2. Other MAPs are about thermoelectricity, concrete and batteries (BIGMAP project in Germany).

* Among the DB

=== Draft list of databases ===
* Add bulleted list item or table entry

{| class="wikitable"
|-
! Name of database !! Description !! Reasoning of choice
|-
| [https://metainfo.nomad-coe.eu/nomadmetainfo_public/archive.html NOMAD] || Data coming from molecular modeling || It belongs to an HPC European Centre of Excellence
|-
| [http://www.matweb.com/ MATWEB] || MatWeb is a searchable database of engineering materials.The database includes thermoplastic and thermoset polymers, metals and alloys, ceramics, wood, fibers, stone, lubricants, inorganic salts, and other engineering materials. The database includes more than 100000 material data sheets || Highly recognizable and popular database directly related to materials. Most data sheets of materials are provided by manufacturers / industry suppliers.
|-
| [http://www.urbanmineplatform.eu/homepage Urban Mine Platform] || The ProSUM project has developed the open-access Urban Mine Platform (UMP). This dedicated web portal is populated by a centralised database containing all readily available data on market inputs, stocks in use and hibernated, compositions and waste flows of electrical and electronic equipment (EEE), vehicles and batteries (BATT) for all EU 28 Member States plus Switzerland and Norway. The knowledge base is complemented with an extensive library of more than 800 source documents and databases. Platform provides the ability to view the metadata, methodologies, calculation steps and data constraints and limitations. || Full access to the required data and information. Easy search. A rich set of metadata.
|-
| [https://odin.jrc.ec.europa.eu/alcor MatDB] || The European Commission JRC [https://odin.jrc.ec.europa.eu ODIN Portal] hosts a number of scientific databases, one of which is [https://odin.jrc.ec.europa.eu/alcor MatDB], which is a database application designed to store mechanical test data coming from tests performed in accordance with mechanical testing standards. The metadata are organised into categories relevant to materials testing, so that there are main entities for source (i.e. provenance), material (i.e. production, heat treatment, microstructure, etc), specimen, test condition, documents and test result. The access management model supports both open access and restricted access. With a view to FAIR compliance, the database supports data citation (using the [https://datacite.org DataCite] framework) and interoperability standards for test data (hosted at [http://uri.cen.eu/cen CEN]). || MatDB supports various features aligned to the FAIR data principles, including data citation e.g. [https://doi.org/10.5290/2900001 Ruiz, A (2018): Nanoindentation (single cycle) test data for Gr. 91 material at 23 °C and maximum indenter force of 1.00332 mN, version 1.0, European Commission JRC] (for findability and access), interoperability standards for mechanical test data and quality assurance wokflows.
|-
| FactSage Browser Thermochemical Data || ||
|-
| NIST X-ray Photoelectron Spectroscopy (XPS) Database || ||
|-
| [http://www.aflow.org/ AFLOWLIB] || AflowLIB (Automatic Flow LIB) is a software framework for high-throughput calculation of crystal structure properties of alloys, intermetallics and inorganic compounds. || It is a rich database.||
|-
| [http://oqmd.org/ OQMD] || The Open Quantum Materials Database (OQMD) is a high-throughput database currently consisting of nearly 300,000 density functional theory (DFT) total energy calculations of compounds from the Inorganic Crystal Structure Database (ICSD) and decorations of commonly occurring crystal structures. || It is a rich database.||
|-
| [https://refractiveindex.info/ Database of refractive indices] || Complex refractive index of inorganic and organic materials ||
|-
|-
| [https://materialsproject.org/ Materials Project] || Platform for materials containing data of inorganic compounds, molecules and nanoporous materials. ||
|-
| [https://omdb.mathub.io/ Organic Materials Database] || The organic materials database is an open access electronic structure database for 3-dimensional organic crystals, developed and hosted at the Nordic Institute for Theoretical Physics – Nordita. It provides tools for search queries based on data-mining and machine learning techniques. ||
|-
| [http://crystallography.net/cod/ Crystallography Open Database] || Open-access database of crystal structures of organic, inorganic and metal–organic compounds and minerals. || It is a widely used and rich database for structural information on materials. ||
|-
| [https://ec.europa.eu/jrc/en/pvgis Photovoltaic Geographical Information System (PVGIS)] ||
JRC Ispra: Photovoltaic Geographical Information System (PVGIS) providing free and open access to:
* PV potential for different technologies and configurations of grid connected and stand alone systems.
* Solar radiation and temperature, as monthly averages or daily profiles.
* Full time series of hourly values of both solar radiation and PV performance.
* Typical Meteorological Year data for nine climatic variables.
* Maps, by country or region, of solar resource and PV potential ready to print.
* PVMAPS software includes all the estimation models used in PVGIS
||
|-
| [http://ckan.pearlpv-cost.eu EU COST Action Pearl PV (CA16235) Photovoltaic Geographical Information System (PVGIS)]
|| Established to publish and upload data of monitored installed PV systems and to quantitatively evaluate the long-term performance and reliability of these PV systems in Europe and elsewhere ||
|}

{| class="wikitable"
|-
! Name !! Description !! Link
|-
| Example || Example || Example
|-
| Example || Example || Example
|-
| Example || Example || Example
|-
| Example || Example || Example
|-
| Example || Example || Example
|}

=== Discussion on the choice of databases: ===
* Bulleted list item

== Notes from the afternoon session ==
The afternoon session is dedicated to discussing metadata for the selected databases. The aim of the afternoon session is to fill out [[UC3#Metadata_assessments|table 2 of the wiki page for the use case]] and to decide what to report back from the use case to the plenary session the next day (again, see the WIKI template for a suggested structure). Thus, at the end of the day, the WIKI page for the use case is complete.

* Bulleted list item

== What to report back to the plenary on Day 3? ==
* Databases selected (names and short reasoning)
* Main insights from discussions
* Suggested next steps
* Other issues

WS1UC3

2020-06-03T09:51:07Z

Karolinaj: /* Draft list of databases */

WS1UC3

2020-06-03T09:50:09Z

Karolinaj: /* Draft list of databases */

WS1UC3

2020-06-03T09:41:46Z

Karolinaj: /* Draft list of databases */

WS1UC3

2020-06-03T09:40:26Z

Karolinaj: /* Draft list of databases */