EERAdata Wiki - User contributions [en]

WS1UC2

2020-06-08T09:23:39Z

Rezaa: /* Interactive elements */

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

== Interactive elements ==
The discussions benefited from EERAdata storyboard and/or slido comments. See [[WS1#Interactive_elements]]

== Notes from the morning session ==
The morning session was dedicated to database discussions with the aim to select 3-5 databases from below's list of databases for further examination.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of EERAdata Team Partners ===
* [https://hvl.no/en/ HVL]
* [https://www.ait.ac.at/en/ AIT]
* [https://www.gig.eu/en/ GIG]
* [https://www.ieu.edu.tr/en/ IUE]

=== Draft list of databases ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]
* [https://openei.org/wiki/Data/ OpenEI]
* [https://www.smard.de/en/ SMARD]
* [https://data.worldbank.org/topic/energy-and-mining/ WorldBank]
* [https://www.nrel.gov/analysis/energy-data-books.html/ NREL]

=== Discussion on the choice of databases: ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their metadata ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-08T09:22:51Z

Rezaa: /* Notes from the morning session */

This page provides space for notes from workshop discussions of use case 2 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]]

== Notes from the morning session ==
The morning session was dedicated to database discussions with the aim to select 3-5 databases from below's list of databases for further examination.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of EERAdata Team Partners ===
* [https://hvl.no/en/ HVL]
* [https://www.ait.ac.at/en/ AIT]
* [https://www.gig.eu/en/ GIG]
* [https://www.ieu.edu.tr/en/ IUE]

=== Draft list of databases ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]
* [https://openei.org/wiki/Data/ OpenEI]
* [https://www.smard.de/en/ SMARD]
* [https://data.worldbank.org/topic/energy-and-mining/ WorldBank]
* [https://www.nrel.gov/analysis/energy-data-books.html/ NREL]

=== Discussion on the choice of databases: ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their metadata ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T09:37:20Z

Rezaa: /* List of Team Members */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of EERAdata Team Partners ===
* [https://hvl.no/en/ HVL]
* [https://www.ait.ac.at/en/ AIT]
* [https://www.gig.eu/en/ GIG]
* [https://www.ieu.edu.tr/en/ IUE]

=== Draft list of databases ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]
* [https://openei.org/wiki/Data/ OpenEI]
* [https://www.smard.de/en/ SMARD]
* [https://data.worldbank.org/topic/energy-and-mining/ WorldBank]
* [https://www.nrel.gov/analysis/energy-data-books.html/ NREL]

=== Discussion on the choice of databases: ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their metadata ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T09:36:17Z

Rezaa: /* List of Team Members */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* [https://hvl.no/en/ HVL]
* [https://www.ait.ac.at/en/ AIT]
* [https://www.gig.eu/en/ GIG]
* [https://www.ieu.edu.tr/en/ IUE]

=== Draft list of databases ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]
* [https://openei.org/wiki/Data/ OpenEI]
* [https://www.smard.de/en/ SMARD]
* [https://data.worldbank.org/topic/energy-and-mining/ WorldBank]
* [https://www.nrel.gov/analysis/energy-data-books.html/ NREL]

=== Discussion on the choice of databases: ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their metadata ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T09:33:16Z

Rezaa: /* Discussion on the choice of databases: */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]
* [https://openei.org/wiki/Data/ OpenEI]
* [https://www.smard.de/en/ SMARD]
* [https://data.worldbank.org/topic/energy-and-mining/ WorldBank]
* [https://www.nrel.gov/analysis/energy-data-books.html/ NREL]

=== Discussion on the choice of databases: ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their metadata ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T09:33:04Z

Rezaa: /* Draft list of databases */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* [https://open-power-system-data.org/ OPSD]
* [https://www.eia.gov/ EIA]
* [https://www.pse.pl/web/pse-eng/data/ PSE]
* [https://www.entsoe.eu/ ENTSO-E]
* [https://openei.org/wiki/Data/ OpenEI]
* [https://www.smard.de/en/ SMARD]
* [https://data.worldbank.org/topic/energy-and-mining/ WorldBank]
* [https://www.nrel.gov/analysis/energy-data-books.html/ NREL]

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their metadata ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T09:25:58Z

Rezaa: /* Draft list of databases */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

* [https://www.buildup.eu/en/explore/links/iea-building-energy-efficiency-policies-beep-database Beep Database (Policy)]
* [https://entranze.enerdata.net/ BuildingRating]

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their metadata ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T08:50:52Z

Rezaa: /* What to report back to the plenary on Day 3? */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their metadata ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T08:46:13Z

Rezaa: /* Extra Sources for FAIR Indices */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===
The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data 3, doi:10.1038/sdata.2016.18)

http://www.snf.ch/SiteCollectionDocuments/FAIR_principles_translation_SNSF_logo.pdf

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T08:45:35Z

Rezaa: /* Notes from the afternoon session */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

=== Extra Sources for FAIR Indices===

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T08:44:43Z

Rezaa: /* What to report back to the plenary on Day 3? */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)
** Collaborate with other UC teams and also experts outside the EERAdata project

WS1UC2

2020-06-04T08:42:26Z

Rezaa: /* What to report back to the plenary on Day 3? */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding metadata for power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)

WS1UC2

2020-06-04T08:37:10Z

Rezaa: /* What to report back to the plenary on Day 3? */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding current power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with the FAIR Maturity Evaluation Service (rd-alliance)

WS1UC2

2020-06-04T08:35:15Z

Rezaa: /* List of participants */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== List of participants ===

* Demet Suna (AIT)
* Aleksandra Zgórska (GIG)
* Reza Arghandeh (HVL)
* Carsten Hoyer-Klick (DLR)
* Christopher Burger-Scheidlin (AIT)
* Veronica Lupi (Bocconi)

=== List of Team Members ===
* HVL
* AIT
* GIG
* IUE

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding current power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for the distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in the power distribution areas including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with an online FAIR toolset (from Andreas)

* '''Other issues'''

WS1UC2

2020-06-03T13:09:43Z

Rezaa: /* What to report back to the plenary on Day 3? */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding current power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in power distribution area including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with an online FAIR toolset (from Andreas)

* '''Other issues'''

WS1UC2

2020-06-03T13:05:54Z

Rezaa: /* Notes from the afternoon session */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).

* Table 2 is filled
* UC2 group discussion notes are summarized to report to the rest of the team as follows.

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding current power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in power distribution area including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with an online FAIR toolset ()

* '''Other issues'''

WS1UC2

2020-06-03T13:04:45Z

Rezaa: /* Notes from the afternoon session */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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).
* Table 2 is filled
* group discussion notes are summarized as follows.

== What to report back to the plenary on Day 3? ==

* '''Databases selected (names and short reasoning)'''
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* '''Main insights from discussions'''
** Based on our discussion regarding current power transmission and distribution networks, there is need to address following challenges: 
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in power distribution area including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.
** It is not clear for us how to interpret and measure following indices (they seem confusing): 
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* '''Suggested next steps'''
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with an online FAIR toolset ()

* '''Other issues'''

WS1UC2

2020-06-03T12:51:38Z

Rezaa: /* What to report back to the plenary on Day 3? */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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)
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* Main insights from discussions
**Based on our discussion regarding current power transmission and distribution networks, there is need to address following challenges:
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there are very limited open access data for distribution power systems. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in power distribution area including DSOs, electricity retailers, energy management companies, etc. Even if the legal issues be resolved, still collecting, archiving, and sanitizing the data need huge resources.

**It is not clear for us how to interpret and measure following indices (they seem confusing):
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* Suggested next steps
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with an online FAIR toolset ()

* Other issues

WS1UC2

2020-06-03T12:49:27Z

Rezaa: /* What to report back to the plenary on Day 3? */

This page provides space for notes from workshop discussions of use case 2 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]]

== 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 [[UC2#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Draft list of databases ===
* OPSD
* EIA
* OpenEI
* PSE
* NREL
* ENTSO-E
* SMARD
* WorldBank

=== Discussion on the choice of databases: ===
* OPSD
* EIA
* PSE
* ENTSO-E

== 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 [[UC2#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)
** OPSD (It is a good example of FAIR and open database with proper metadata)
** PSE (It is a rich national database with open access)
** EIA (It is a rich national database with open access)
** ENTSO-e (It is a major source for European power networks data which is open access)

* Main insights from discussions
**Based on our discussion regarding current power transmission and distribution networks, there is need to address following challenges:
*** Lack of standardization for metadata taxonomy and common vocabulary (related to I2)
*** Ambiguity on licensing issues for various types of energy data (related to R1.1)
*** Lack of unique identifier for energy data (related to F1)
*** In general, there very limited open access data for distribution power system. The huge gap is due to the privacy and confidentiality of the data that includes personal information about electricity customers and household owners. Also, there are many players in power distribution area including DSOs, electricity retailers, energy management companies, etc. So, collecting, archiving, and sanitizing the data need huge resources.

**It is not clear for us how to interpret and measure following indices (they seem confusing):
*** R1.2. (meta)data are associated with detailed provenance,
*** 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;

* Suggested next steps
** Compare the selected databases regarding their ontologies (e.g. compare SMARD, ENTSO-e, and PSE)
** Reassess selected databases with an online FAIR toolset ()

* Other issues

WS1UC2

2020-06-03T12:39:25Z

Rezaa: /* What to report back to the plenary on Day 3? */

WS1UC2

2020-06-03T12:37:29Z

Rezaa: /* What to report back to the plenary on Day 3? */

WS1UC2

2020-06-03T12:36:13Z

Rezaa: /* What to report back to the plenary on Day 3? */

WS1UC2

2020-06-03T12:25:12Z

Rezaa: /* What to report back to the plenary on Day 3? */

UC2

2020-06-03T12:23:20Z

Rezaa: /* List of selected databases */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== List of selected databases ==
The team selected eight datasets before the workshop. During the first workshop (see notes from Day 2), the four databases were selected to further 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: Improve R1.1, clarify licensing issue regarding different data origins. Notice that OPSD is not owner of the data.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance. Improve R1.1, clarify licensing issue regarding different data origins.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable. It needs to clarify licensing issue regarding different data origins.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD]
|| Administrative 100%, Descriptive 100%, Structural 100%
|| Rich
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| Taxonomy
|| xml, plain text, RDF, xml, csv, json, jupyter, etc.
|-
| [https://www.eia.gov/ EIA]
|| Administrative 80%, Descriptive 100%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| Taxonomy
|| xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Administrative 80%, Descriptive 90%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| Taxonomy
|| xls, csv, pdf, etc.
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Medium-Low
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| csv, xlsx, xml, xml zip, graphs and charts
|-
|}

UC2

2020-06-03T12:21:56Z

Rezaa: /* List of selected databases */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: Improve R1.1, clarify licensing issue regarding different data origins. Notice that OPSD is not owner of the data.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance. Improve R1.1, clarify licensing issue regarding different data origins.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable. It needs to clarify licensing issue regarding different data origins.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD]
|| Administrative 100%, Descriptive 100%, Structural 100%
|| Rich
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| Taxonomy
|| xml, plain text, RDF, xml, csv, json, jupyter, etc.
|-
| [https://www.eia.gov/ EIA]
|| Administrative 80%, Descriptive 100%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| Taxonomy
|| xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Administrative 80%, Descriptive 90%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| Taxonomy
|| xls, csv, pdf, etc.
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Medium-Low
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| csv, xlsx, xml, xml zip, graphs and charts
|-
|}

WS1UC2

2020-06-03T12:13:34Z

Rezaa: /* Discussion on the choice of databases: */

WS1

2020-06-03T12:12:12Z

Rezaa: /* Gaps identified across use cases */

The first workshop of EERAdata is organized as an online webinar and hackathon from June, 2-4, 2020.

== Objective ==
* Learn about FAIR and open data practices in the energy and other research communities;
* Choose selected databases to be investigated in use cases. Discuss and summarize the reasons for selection.
* Analyze the state of FAIR/O principles for the selected database (with the help of the questionnaire and FAIR/O assessment tools).
* Evaluate the state of FAIR/O principles for the metadata of selected databases.
* Suggest general principles for the design of metadata (use-case- and domain-specific),
* Discuss top-level metadata adhering to FAIR/O principles (use-case- and domain-specific),
* Learn about the FAIRification of Data Management Plans (DMP).

== Read aheads ==

'''Obligatory:'''
* M. D. Wilkinson et al., “The FAIR Guiding Principles for scientific data management and stewardship,” Scientific Data, vol. 3, p. 160018, Mar. 2016. https://doi.org/10.1038/sdata.2016.18
* B. Mons et al., “Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud,” Information Services & Use, vol. 37, no. 1, pp. 49–56, Jan. 2017. https://doi.org/10.3233/ISU-170824
* EOSC HLEG (2018). Final report and recommendations of the Commission 2nd High Level Expert Group on the European Open Science Cloud (EOSC). Prompting an EOSC in practice. Available online: https://publications.europa.eu/en/publication-detail/-/publication/5253a1af-ee10-11e8-b690-01aa75ed71a1 (accessed: 18.07.2019).

'''Suggested read on the history of metadata:'''
Metadata - Shaping Knowledge from Antiquity to the Semantic Web by Richard Gartner, https://www.springer.com/gp/book/9783319408910

== Join and collaborate interactively! ==
The workshop is a hackathon! EERAdata is evolving jointly only! Join the discussions and work together online:
* [[Main_Page#Getting_started_with_EERAdata_wiki|EERAdata WIKI]]
* [[WS1#EERAdata_story_board|EERAdata storyboard]]
* [https://github.com/valeria6856/EERAdata EERAdata@github]
* [https://www.researchgate.net/project/Towards-a-FAIR-and-open-data-ecosystem-in-the-low-carbon-energy-research-community EERAdata@ResearchGate]
* Post your questions and comments on slido: https://app.sli.do/event/wrz7iwdh - OR go to [https://www.sli.do/ slido.com] and enter the event code: 23069

=== EERAdata story board ===
'''Objective:''' collect views from participants regarding energy data, energy metadata, FAIR/O problems etc. to support discussions, identification of gaps & needs (WP2) and elements to design the platform (WP3).

'''Questions:'''
* Q#1: What is your user story regarding FAIR/O energy data?
* Q#2: What is your user story regarding metadata?

Template to answer: As a <stakeholder>, I want <goal> so that <reason>.

'''How to post a story?'''
# Click on the link: https://padlet.com/janaschwanitz/aciywzt9fs1h70m2
# Click on plus at the right bottom to add a story.
# Choose as title depending on the question one wants to answer. Choose for Q#1: FAIR/O data, or for Q#2: metadata. In the example above, the title “metadata” was chosen.
# Type your sentence to let us know where the gaps and hopes are: The template is: As a <stakeholder>, I want <goal> so that <reason>.

'''Example:''' As a data-driven energy researcher, I want utopia - i.e. one-stop access to all relevant metadata -, so that I can browse available data, check where they are from and whether I can trust them when reusing.

'''How to comment a story?'''
* One can rate stories by clicking on a number of stars.
* One can comment stories as well as comments with words.
* It is anonymous commenting and adding of stories, as long as one does not login into one's personal profile at padlet.com.

=== EERAdata wiki - How to? ===
The easiest way is you simply start writing and editing. You can '''install an easy editor''' by doing what is described in the picture to the right.
[[File:Install easy editor.png|thumb|How to install an easy editor]]

Consult the [https://www.mediawiki.org/wiki/Special:MyLanguage/Help:Contents User's Guide] for information on using the wiki software.
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:Configuration_settings Configuration settings list]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:FAQ MediaWiki FAQ]
* [https://lists.wikimedia.org/mailman/listinfo/mediawiki-announce MediaWiki release mailing list]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Localisation#Translation_resources Localise MediaWiki for your language]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:Combating_spam Learn how to combat spam on your wiki]

=== EERAdata on github ===
Link here and share your thoughts and issues! Note, work in progress.
* [https://github.com/valeria6856/EERAdata EERAdata@github]

=== EERAdata @ Research Gate ===
Link here and share your thoughts and issues! Note, work in progress.
* [https://www.researchgate.net/project/Towards-a-FAIR-and-open-data-ecosystem-in-the-low-carbon-energy-research-community EERAdata@ResearchGate]

=== Just have fun! ===
==== Metadata memory game ====
'''Read before playing:'''

This is a little memory game where players need to '''identify triples''', that is three tiles that belong to one data set. All of them relate to low carbon energy. Some tiles have the form of a picture, others show metadata descriptions (in various formats) and some are even sound files. So, the game is to have fun, while learning about metadata. Try out if you can find all triples. Note if you have opened 3 tiles and they do not match, all will automatically close. Just as you know it from a real-life memory game.
[http://eeradata.webfactional.com/memory/memory.html '''Link''']

== Agenda Day 1 ==
Builds on read aheads. Online talks and discussions. Space for interaction with participants after each presentation. Moderated discussion of collected comments.

{| class="wikitable"
|-
! Time slot !! Topic
|-
| 10.00-10.20 || '''Welcome and introduction''' with workshop goals and procedures: “EERAdata - Towards Utopia for low carbon energy research”, Valeria Jana Schwanitz, HVL & PI EERAdata. Link: [http://eeradata.webfactional.com/WS1/EERAdata_WS1.pdf]
|-
| 10.20-12.15 || '''Online lectures''':
* “The EOSC Nordic: machine-actionable FAIR maturity evaluations & the FAIRification of data repositories” - Andreas Jaunsen, Nordforsk & EOSC-Nordic. Link: [http://eeradata.webfactional.com/WS1/EOSC-Nordic_FAIR_data_presentation_2_June_2020.pdf]
* “OpenAIRE: Open Access Infrastructure for Research in Europe”, Ilaria Fava, OpenAIRE. Link: [http://eeradata.webfactional.com/WS1/20200602_OpenAIRE-EERAdata.pdf]
A short break of 15 min -
* “Community-driven metadata and ontologies for Materials Science and their key role in artificial-intelligence tools”, Luca Ghiringhelli, FHI Berlin. Link: [http://eeradata.webfactional.com/WS1/Ghiringhelli_FAIRmetadata_EERAdata.pdf]
* “Metadata practices from IRP Wind”, Anna Maria Sempreviva, DTU. Link: [http://eeradata.webfactional.com/WS1/EERAdata_Sempreviva.pdf]
|-
| 12.15-13.00 || ''Lunch Break''. Play the EERAdata game “Utopia and metadata”. Or any time.
|-
| 13.00-14.00 || '''Online lectures''':
* “Humanities and data: for a community-driven path towards FAIRness”, Elena Giglia, UNITO.
* “RISIS - An e-Infrastructure for the STI-Policy research community”, Thomas Scherngell, AIT. Link: [http://eeradata.webfactional.com/WS1/RISIS2_eera_data.pdf]
|-
| 14.00-14.30 || ''Break'' - Game “Utopia and metadata”. Or any time.
|-
| 14.30-16.00 || '''Discussion''' to compile a to-do list for work in use cases on the second day. Serves as a guiding and aligning process. Lead by WP2, August Wierling/Valeria, HVL.
|}

=== Notes from Day 1 ===
==== Welcome and Introduction ====
* Introduction by Valeria:
** What is the project EERAdata about
** In the energy system the data revolution speeds up
** Data on:
*** Wheather patterns
** more and more application are becomign available
*** digital twins: steering nuclear plants just from the scree
** Buildings get energy passports
** era of digital reporting and compliance arises
** Importance of linking across different formats and topics
**time spent as aresearcher: Large amount of time spent on data sorting, formatting, searching, etc
* Valeria invites everyone again to write down their story connected to energy data on the EERAdata storyboard (see Link on Main page WIKI)
** This will be valuable in moving forward with the ideas for the EERAdata project
*Valerias personal starting point regarding EERAData:
** Work in towards enabling FAIR and open data for the low carbon energy research community
* We hope to add what we learn in this 3 days to the EERA WIKI
** guidance platform for low carbon energy researchers
* at the end we hope we come to a set of meta data standards for energy data
* what could be the utopia for energy data researcher:
** emagine lookign for citizen led initiatives in PV
** search for keyworkds on a website -> and recieve a list of datasets related to this topic
** for all those datasets:
*** see amount of initiatives available
*** when where they updated the last time
*** links provided to access the data
*** are the certified as FAIR/O and who is certifying institution
*** refine search with specific filter options
*** information on the quality/ data collection and processing methodology
*** option for simple data analysis operations
*** -> get an overview over richness of data
** -> we are still very far away from this utopia
* Goals of this Workshop:
** listen to various best practices
** day 2: discuss the provided examples
** day 3: presentation of findings from day 2 discussions
** day 3 afternoon: Data management plans (DMPs)

==== The EOSC Nordic: machine-actionable FAIR maturity evaluations & the FAIRification of data repositories ====
* '''notes incoplete, will be added later'''
**What is the EOSC:
*** goal:
**** enable reserachers to access data across domains and disciplines as easy as possible
**** locating the relevant data
*** vision:
**** all european data shoud be available to research
**** does not mean that all data is stored centrally, but that all databases are interconnected
* WP 4 members: include all nordic countries
* How can we improve datasets:
** source code:
***
* recommendations:
* evaluations:
** why do we evaluate repositories?
*** what is the level of FAIRness?
*** about 10 datasets per repository
*** FAIR score
*** Positive highlights:
****
*** FAIR score of all evaluated datasets:
**** majority at 0.10 out of 1
* coming tasks:
**
**
* question from Valeria: would it be possible to use their scoring system to assess one of the EERAdata datasets?
** Answer:

==== OpenAIRE: Open Access Infrastructure for Research in Europe ====
* Introduction into OPENAIRE:
** 2007 pilot publications
**
* Openaire is bridging the 2 worlds where science is performed and published
* In practice:
** services that monitor, assess and accelerate open science
** facilitate research communities adoption of open science
* who is openaire:
** 50 partners all over europe
** experts in open science in every EU member states
** regional coordinators
** topical coordinators working on policies for open science
** openaire is an infrastucture
** last phase of openaire: citizen science
*** openaire end in 12/2020
** 4 regions: North-, east-, west-, south europe
** large diferences in needs from country to country
*** -> find best solutions to develop open science for each country
** connections to open science community in North america, Japan, ...
* openaire has published set of guidelines in cooperation with international network:
* provided services:
** providing policy advice
** training and support
** open science infrastructure
** How to achieve FAIRness in sharing resreach data?
** guidelines on how to provide open access to publications, not only data
* How we support:
** Helpdesk: questions, FAQ
**
**
* Openaire provides guides for:
** researchers
** content providers
** funders
* Webinars:
* outreach:
** 230 webinars
** 22 NOADS are involved in EOSC WGs
* explore portal:
** search interface for all content available through Openaire
*** 40M publications: shows most crucial metadata
** EERADATA record:
*** for now, no information, as no data has been collected from repositories yet
* Openaire connect project:
** gateway for reserach communities
** allows research communities to build a gateway that collects different data relevant to your research community
* COVID-19 research community:
** ca 3200 research datasets
** 113 relates projects
* OpenAIRE provide:
** allows connection of repositories to openAIRE
* Zenodo: repository developed by openaire that allows institutions to publish their reserach output
* AGROS: machines readable data repository

* comment from Andreas Jaunsen: today, research projects spent roughly 80% of their research time on data gathereing/ processing
**-> open access aims to reduce this by only having to precess the data once

* Carsten Hoyer comments:
** create a metadata catalogue
** link the provenance information of data
*** -> track who has done what with the data

* Question from August:
* Rich metadata: search specifically for the research question for one on paper? How could this be achieved?
** openaire explore: works as normal search engine -> high "noise" (unwanted search results)

* incentives for researchers to provide rich metadata?
** Use of commen ontology allows for more refined serach results

==== Community-driven metadata and ontologies for Materials Science and their key role in artificial-intelligence tools ====
* Key message:
**
* FAIR: Findable, Accessible, Interoperable, Reusable
** Findable:
*** Uniqueness of the date
** accessible:
*** URL, accessible vi API
** Interoperability:
** reusability: Metadata should be as desciptive as possible
* NOMAD-FAIRDI Workshop:
** Shared metadata and data formats for big-data driven material science
* Data object:
** Metadata:
*** Unique identifier, Structure of the data, Method
*** should contain information of teh full provenance of the data:
**** where does it come from? Another database? A calculation? etc?
*** '''Definition:'''
* NOMAD Respository structure:
** Nomad Repository
** Conversion Layer
** The archive
*** Three access points:
****
* Computational material sciences:
**
* Ontology:
*
* Questions:
** what happens to metadate when you physically go from one structure to a combined structure? How do you combine the metadate of the two initial structures?
***
** from EERAData perspective: in material for low carbon energy use case, what could be valuable contribution of EERAData to reserach community?
*** Ontologies are driven by the use cases.
*** summarizing: Excersizing a fine grain use case such as solar PV. Linking different levels of metadata. Further develop metadata at the use case level. How to link across use cases?

==== Metadata practices from IRP Wind ====
* Starting point was the inability to find information
* This presentation is about research data
* digital objects can be assets due to competitive advantages that the digital objects provides
* Interpretion of FAIR: F A and I data results in R data
** Reusable data multiplies the value of the data
* '''"Data should be as opeb as possible but as closed as neccessary"'''
* Issue: How to make data findable but safe
** Misstrust/ fear that own data might be missused/ one looses the competitive advantage
* Issue: Data findability
** Datasets are organized in different ways
**
* IRP Metadate and taxonomies:
** Base metadate as defined by Dublin core standards
** Additional non-Dublin Core taxonomies
* Creating a taxonomy:
** Expert elicitation: Group of experts creates a taxonomy which is then reviewed by wider reserach community
** Author keywords: Map keywords used by authors along similarities in meaning, frequency of usage
*** Pros: Allows tracking of trends
*** Cons: Mix of disciplines, models, etc; Many errors and ambiguities; single generic words with a broad range of possible interpretations.
* Virtual libraries:
** Two aspects: Seach engine (metadata) and Data storage (data)
*** Linked databases allow being searched centrally, but data is stored decentrally
* conclusion:
** Purpose of a web data portal is to (1) connect safely data owners and users and (2) inform on availability of Data, not neccessarily provide direct access to data

* Discussion:
** How to create and maintain metadata? How to allow dynamic updates of data? How to deal with language issues (non-native speaketors, translation,...)?
** Third option to create taxonomies: Use machines or algorithms to link the different taxonomy development approaches?
** General metadata standards exist, what is needed are domain specific metadata
** Two seperate categrories: Metadata and vocabolaries

==== Humanities and data: for a community-driven path towards FAIRness ====
* Humanities are often a bit neglected in the data community
* Who is ALLEA?
*Who is Co-operas?
** implementation network
** goal: taking care of the whole cycle of humanities reserach from data gathering to publishing
* Data management life cycle:
** Identification
** Planning
** Gathering
** maintaining, processing
** dissimination
* FAIR Data in humanities?
** currently, the FAIR principles will persist in shaping the data landscape in humanities
*'''"There is risk and value in being a first mover, but there is more risk in being a follower"'''
* Is data still a dirty word in the SSH?
** In the humanities, we all use Data, even if we are not aware of it
** Data in humanities is more prone to interpretation than in STEM disciplines -> harder to grasp
* What is data in the humanities:
** Never "raw" data
** Data is always an expression of the method
** there is always a choice
** There is always an interpretation
** there is always a dicussion
* Data pillars:
** Data are so divers that it is impossible to converge on a common definition
*** to define data, go as deep as possible into reserach practices
* risk of oversimplification
* preliminary issues of FAIRness:
** In which step and how should FAIR principles be applied?
** what language?
** Lack of skills among researchers
** registry of existing tools
** need to preserve specifities of how we do research in the humanities
** services and tools need to be sustainable
* Findability:
** metadate needs to be seperated from data
** maintain richness of metadata
**
* difficulties in humanities:
** data in humanities are linked to cultural, political aspects
* Nest steps:
** Data stewardship wizard for SSH
* '''Accessible does not equate to open'''
* interoperability:
** data is often so closely tailored to a specific project, that interoperability in impossible
* reusability:
** Copyright is still an issue
** need of legal advice
** In the end, reuse is the final aim of FAIRness
** reusability is also a measure of the impact of your data
* mindshift:
** currently everything is closed, except for a few daring frontrunners
** in future, everything should be open, except for a few absolutely neccessary cases.

==== RISIS - An e-Infrastructure for the STI-Policy research community ====
* RISIS:
** within social sciences
** strong connection to economics
** Measuring innovation: long tradition of using quantitative indicators and qualitative models
** started in 2014
** focuss on linking R&I datasets
** harmonizing of Organization names (Organization are main objects of study in this project)
* Datasets:
** firm innovation capabilities
** R&D output databases
** Public research and higher education
** Database on policy learning
* need to adapt to new developments within research communities
* RISIS Knowmak tool:
** openly and freely present indicators in R&I gathered from RISIS datasets
* RISIS dataset portal
** Check metadata of available datasets
** choose relevant datasets
** fill out data access aplication form
** application will be assessed by external reviewers
** if approved, acces is granted

* Discussion:
** How do you integrate your datasets with other datasets (e.g. business registers, national industry sector classifications)
*** bussiness registers often not open, but need purchasing, hence integration often not possible
*** external classifications (e.g. industry sector classifications) are often included, but a inetrnal ontology was also developed
** Are the metadata desciptions machien readable? Or only available as PDF?
*** Yes they are also available as machine readable formats, but PDF as qualitative version is imprtant for external presentation

==== Discussion/ to-do list for work in use cases ====
* Questions:
** What is the take home message for you?
**

* Use case 1:
** main goal is the re-usability
** we need to assess the databases that were chosen previously
** best preactices: EOSC,

* Use Case 2:
** Main issue in this use case is privacy/ sensitivity
** '''security comes first'''
** Tradeoff between unsiversal metadata language and domain specific language

* Use case 3:
** Linguistics is a problem
** As soon as we change the application of material/ material data, we change/need to change the metadata
** Find similarities of already existing metadata

* Use case 4:
** big challange regarding the linguistic problem
*** Diferent language
*** Different interpretation of same terms
** Pick low hanging databases that are far away from FAIR principles

* EERAData is probably more about asking the right questions than providing the right answers, there are already a lot of answers out there
* Interests of HVL:
** Assess FAIRness of our own COMETS database
** Assess how EERAdata adheres to new EU funding requirements

* Outcome of first and second workshop is hopefully some drafts for low carbon energy metadata standards, which can be reviewed by experts

* EERAdata platform responsibles will join in on all use case discussions on second WS day
* '''"Ontology is a formal represenation of the knowledge of a community on a specific purpose"'''

== Agenda Day 2 ==
=== News of the day before ===

Not energy, but an inspiring connection: Perhaps unexpected, or perhaps even not: DNA helps to puzzle pieces of Qumran role. DNA taken from animal skins that were used to write on ...
[[File:Selection 186.png|thumb|Perhaps unexpected, or perhaps even not: DNA helps to puzzle pieces of Qumran role. DNA taken from animal skins that were used to write on ...]]

=== METADATA - DISCUSSIONS in use cases, parallel sessions ===
Work in use cases on databases and metadata, led by use case leaders. Suggested outline:

* '''10-12 Discuss and update preliminary state of FAIR/O for the use case.''' Use the prepared draft of databases to check compliance with FAIR principles (tools: WP3 questionnaire and others). Compare the assessment results for each database. Observe and discuss agreements and differences across the evaluation tools. Generate the overall picture for FAIR/O compliance for the use case to pin down the state of art. Let’s see if we come to the same result as in our initial assessment for the application (traffic lights). Continuously make notes to report later on results. Select a responsible person. Objective: select 3-5 databases per use case. Discuss which databases to select. One to cover use-case specific challenges; and one with cross-use case relevance, and one a low hanging fruit for which it would be relatively easy to improve the current FAIR/O status.
* 13-15 Joint brainstorming to discuss FAIR/O state of the metadata for the selected use cases. Evaluate: What is the current description of metadata? How extensive are they? Is only administrative information provided? Or richer context description? What frameworks for metadata are used: taxonomy? thesaurus? ontology? How is the metadata information technically implemented: plain text file? xml? rdf? ... Identify use case specific issues with metadata - What are the gaps? What is perceived as a hard nut to crack? Pay special attention to the metadata of the databases and fill out the table provided WP2. Continuously make notes to report results the next day! Select a responsible person!
* 15-17 Joint recording of lessons learned. Create and/or update the WIKI for the use case with literature, gaps, best practices, FAIR/O discussion, metadata discussion, suggested next steps, .... Get your head around what to report next day! Plan for 20 min. See the links to WIKI page templates below (Notes from Day 2).

=== Gaps identified across use cases ===

{| class="wikitable"
|-
! Use case 1 !! Use case 2 !! Use case 3 !! Use case 4
|-
| [[UC1|Buildings efficiency]] || [[UC2|Power transmission & distribution networks]] || [[UC3|Material solutions for low carbon energy]] || [[UC4|Low carbon energy and energy efficiency policies]]
|-
|
[[File:UC1 logo.jpg|thumb]]
||
[[File:UC 2 logo.jpg|thumb]]
||
[[File:UC 3 logo.jpg|thumb]]
||
[[File:UC 4 logo.jpg|thumb]]
|-
|
* qualitative nature of data limiting interoperability
* data availability issues for time-series
* multiplicity and scattered nature of data sources (households, industries, utility companies, municipalities)

||
* Lack of standardization for metadata taxonomy and common vocabulary
* Ambiguity on licensing issues for various types of energy data
* Lack of unique identifier for energy data in most databases
||
* microscopic use cases resembling the existing one about PV
* link between microscopic and macroscopic materials (e.g., turbine blades)
* metadata for applications of materials
* linking to other fields
||
* metadata for images
* language and terminology (e.g., records instead of data)
|}

Note: This schedule is a suggestion. Adjust and organize breaks as needed.

=== Notes from Day 2 ===
* Use case 1 - Summary: [[UC1]], Detailed notes: [[WS1UC1]]
* Use case 2 - Summary: [[UC2]], Detailed notes: [[WS1UC2]]
* Use case 3 - Summary: [[UC3]], Detailed notes: [[WS1UC3]]
* Use case 4 - Summary: [[UC4]], Detailed notes: [[WS1UC4]]

== Agenda Day 3 ==
Reporting experience from use case applications. Prepare the next workshop on workflows and metadata. Introduction and discussion of data management plans.

{| class="wikitable"
|-
! Time slot !! Topic
|-
| 10-12.30 || '''Discussion''' lead by WP2. Report from use case experiences (by use case leaders). Wrap up.
|-
| 12.30-13.30 || ''Lunch break''
|-
| 13.30-15.00 || '''Data Management Plans'''
* Presentation “Introduction to DMP and best practices” by Trond Kvamme, NSD
* Presentation on machine-actionable DMPs by Tomasz Miksa, TU Vienna
* Discussion of EERAdata DMP draft (August, HVL)
* Short break of 15 min
|-
| 15.15-16.00 || '''Wrap up''' of workshop with feedback from invited experts.
|}

=== Notes from Day 3 ===
* Bulleted list item

UC2

2020-06-03T12:05:40Z

Rezaa: /* Metadata assessments */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: Improve R1.1, clarify licensing issue regarding different data origins. Notice that OPSD is not owner of the data.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance. Improve R1.1, clarify licensing issue regarding different data origins.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable. It needs to clarify licensing issue regarding different data origins.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD]
|| Administrative 100%, Descriptive 100%, Structural 100%
|| Rich
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| Taxonomy
|| xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA]
|| Administrative 80%, Descriptive 100%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| Taxonomy
|| xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Administrative 80%, Descriptive 90%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| Taxonomy
|| xls, csv, pdf, etc.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Medium-Low
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| csv, xlsx, xml, xml zip, graphs and charts
|-
|}

UC2

2020-06-03T12:04:41Z

Rezaa: /* Metadata assessments */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: Improve R1.1, clarify licensing issue regarding different data origins. Notice that OPSD is not owner of the data.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance. Improve R1.1, clarify licensing issue regarding different data origins.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable. It needs to clarify licensing issue regarding different data origins.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD]
|| Administrative 100%, Descriptive 100%, Structural 100%
|| Rich
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA]
|| Administrative 80%, Descriptive 100%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Administrative 80%, Descriptive 90%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Medium-Low
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| csv, xlsx, xml, xml zip, graphs and charts
|-
|}

UC2

2020-06-03T12:02:12Z

Rezaa: /* Metadata assessments */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: Improve R1.1, clarify licensing issue regarding different data origins. Notice that OPSD is not owner of the data.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance. Improve R1.1, clarify licensing issue regarding different data origins.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable. It needs to clarify licensing issue regarding different data origins.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD]
|| Administrative 100%, Descriptive 100%, Structural 100%
|| Rich
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA]
|| Administrative 80%, Descriptive 100%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Administrative 80%, Descriptive 90%, Structural 100%
|| Medium
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Medium-Low
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| csv, xlsx, xml, xml zip, graphs and charts
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T11:52:47Z

Rezaa: /* List of selected databases */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 50% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: Improve R1.1, clarify licensing issue regarding different data origins. Notice that OPSD is not owner of the data.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 50% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance. Improve R1.1, clarify licensing issue regarding different data origins.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable. It needs to clarify licensing issue regarding different data origins.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD]
|| Administrative 100%, Descriptive 100%, Structural 100%
|| Rich
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 100% - R1.2 100% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T11:48:19Z

Rezaa: /* Metadata assessments */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 100% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: It is OK.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD]
|| Administrative 100%, Descriptive 100%, Structural 100%
|| Rich
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 100% - R1.2 100% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' Taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T11:40:36Z

Rezaa: /* Metadata assessments */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 100% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: It is OK.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD]
|| Administrative 100%, Descriptive 100%, Structural 100%
|| Rich
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 100% - R1.2 100% - R1.3 100%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy
|| ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 100% - F4 70% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 100% - I3 70% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T11:31:56Z

Rezaa: /* Metadata assessments */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 100% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: It is OK.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD] || [refer to DC table in word file] Administrative 100%, Descriptive 100%, Structural 100% || Rich || F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 100% - F4 70% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 100% - I3 70% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T11:27:31Z

Rezaa: /* List of selected databases */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 100% - F4 100% / A1.1 100% - A1.2 20% - A2 100%/ I1 100% - I2 100% - I3 100% / R1.1 100% - R1.2 100% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles
* Findable: It is Ok.
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: It is OK.
* Reusability: It is OK.
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* Reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* Reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
* Findable: Improve F2: data should be better described with rich metadata and Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
* Accessibility: Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available.
* Interoperability: Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?). Also improve I2: There is a long list of databases under sitemap, this can be linked also explanations.
* Reusability: improve R1.1 and R1.2: it should contain more clear and accessible data usage license and associated provenance. regarding license, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable.
|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD] || [refer to DC table in word file] Administrative 70%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 100% - F4 70% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 100% - I3 70% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T10:12:05Z

Rezaa: /* List of selected databases */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 70%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles and
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 30% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Improve I2, e.g. to include qualified references to other (meta)data
* reusability: improve R1.2. it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 20% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 20% - F4 50% / A1.1 100% - A1.2 20% - A2 50% / I1 100% - I2 80% - I3 80% / R1.1 20% - R1.2 50% - R1.3 100%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
* Findable: Improve F1,F2,F3, e.g needs unique identifier and more searchable form.
* Accessibility: Improve A1.2 and A2, e.g. no information regarding if metadata are accessible even when the data are no longer available. Also, there is no authentication and authorization procedure, where necessary.
* Interoperability: Slightly improve I2 and I3. e.g to include qualified references to other (meta)data
* reusability: improve R1.1 and R1.2. e.g. the usage license is not clear, also it is not clear how (meta)data are associated with detailed provenance.
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
Improve F2: data should be better described with rich metadata
Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available
Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?)
R1.1 and R1.2: it should contain more clear and accessible data usage licence and associated provenance. regarding licence, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable.
I2: There is a long list of databases under sitemap, this can be linked also explanations.

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD] || [refer to DC table in word file] Administrative 70%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 100% - F4 70% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 100% - I3 70% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T09:30:27Z

Rezaa: /* List of selected databases */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 70%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles and
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 100% - F4 50% / A1.1 100% - A1.2 100% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
* Findable: Improve F1,F2,F4, e.g needs unique identifier
* Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available
* Interoperability: Improve I2 to include qualified references to other (meta)data
* reusability: improve R1.2. (meta)data are associated with detailed provenance.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 80% - F2 100% - F3 100% - F4 100% A1 100% - A1.1 100% - A1.2 50% - A2 100%- I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
Improve F2: data should be better described with rich metadata
Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available
Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?)
R1.1 and R1.2: it should contain more clear and accessible data usage licence and associated provenance. regarding licence, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable.
I2: There is a long list of databases under sitemap, this can be linked also explanations.

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD] || [refer to DC table in word file] Administrative 70%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 100% - F4 70% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 100% - I3 70% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T09:29:27Z

Rezaa: /* List of selected databases */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 70%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles and
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 100% - F4 50% / A1.1 100% - A1.2 100% - A2 50%/ I1 100% - I2 100% - I3 50% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?''
Findable: Improve F1,F2,F4, e.g needs unique identifier
Accessibility: Improve A2, e.g. no information regarding if metadata are accessible even when the data are no longer available
Interoperability: Improve I2 to include qualified references to other (meta)data
Interoperability: improve R1.2. (meta)data are associated with detailed provenance.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 80% - F2 100% - F3 100% - F4 100% A1 100% - A1.1 100% - A1.2 50% - A2 100%- I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
Improve F2: data should be better described with rich metadata
Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available
Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?)
R1.1 and R1.2: it should contain more clear and accessible data usage licence and associated provenance. regarding licence, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable.
I2: There is a long list of databases under sitemap, this can be linked also explanations.

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD] || [refer to DC table in word file] Administrative 70%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 100% - F4 70% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 100% - I3 70% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC2

2020-06-03T09:06:24Z

Rezaa: /* List of selected databases */

== Power transmission & distribution networks ==
=== General description of use case ===
The rapid growth of renewable energies and greater emphasis on improving grid sustainability and resilience will require changes in the ways that power transmission and distribution networks are operating. This grid of the future requires advances in transmission and distribution system management with algorithms to control and optimize how power is transmitted and distributed through the grid. However, the development of these algorithms is challenging due to the lack of high-fidelity, public, and large-scale data that realistically represent current and evolving grid properties. The proposed use case for an open-access repository of power systems models and data will enable more productive research collaborations. On a higher level, it improves the integration of renewable electricity onto the grid, which would help reduce reliance on carbon-emitting, fossil fuel generation. This use case goal is mimicking the characteristics of the actual electric grid without disclosing sensitive information.
Existing FAIRification and opening activities EERAdata builds on are a) Creating a library of publicly available test data from prominent power system related organizations such as IEEE, the United States Department of Energy, and the International Smart Grid Action Network (ISGAN). The Repository pulls together grid models and related test data from across the utility industry to improve community access. Relevant data could also be coming from the European Network of Transmission System Operators (ENTSO-E) as well as from the Open Power System Data Platform. b) Validate use cases and the associated data toward the proposed EERAdata FAIR/O ecosystem especially on the impact of renewable energy on the low carbon energy system transformation. Multiple scenarios for data validation will be taken into account.

== 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
|-
| [https://open-power-system-data.org OPSD]
|| The database is an outcome of the Open Energy Modelling Initiative that dates back to 2014. The aim is to construct an open platform for energy systems modelling data.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90%
|| ''What FAIR/O target was decided?'' Improve I2 for using vocabularies that follow FAIR principles and
|-
| [https://www.eia.gov/ EIA]
|| The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 50% - F2 50% - F3 100% - F4 50% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 100% - I3 70% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' Improve I2 for include qualified references to other (meta)data and improve R1.2. (meta)data are associated with detailed provenance.
|-
| [https://openei.org/wiki/Main_Page/ OpenEI]
|| OpenEI is developed and maintained by the National Renewable Energy Laboratory with funding and support from the U.S. Department of Energy since 2017. The platform is wiki based. Users can view, edit, and add data – and download data for free.
|| It is not an extensive dataset. It seems it is in Beta version. So, it doesn't meets FAIR criteria.
|| F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100%
|| ''What FAIR/O target was decided?'' It need major improvement in Accessibility and Interoperability.
|-
| [https://www.pse.pl/web/pse-eng/data PSE]
|| Energy sector database for Poland. The database.The scope and information presented in the database includes: Polish Power system operation; balancing market operation and reports map.
|| It is an extensive dataset that almost meets FAIR criteria.
|| F1 80% - F2 100% - F3 100% - F4 100% A1 100% - A1.1 100% - A1.2 50% - A2 100%- I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%.
|| ''What FAIR/O target was decided?'' Improve F2 data are described with rich metadata
|-
| [https://www.nrel.gov/grid/data-tools.html NREL]
|| NREL develops data and tools for the analysis of grid technologies and strategies, including renewable resource data sets and models of the electric power system..
|| It is an extensive dataset that meets FAIR criteria.
|| F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What FAIR/O target was decided?'' Accessibility: A1.2 the protocol allows for an authentication and authorization
|-

| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Central collection and publication of electricity generation, transportation and consumption data and information for the pan-European market. Main data categories are: Load, generation, transmission, balancing, outages, congestion management, system operations. It covers data from the starting year 2014 in hourly resolution.
|| One of the main data sources for this use case in respect of transmission capacities. Widely used by researchers working on different aspects of electricity market in Europe.
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| F1: Assign data set a globally unique and persistent identified (e.g. DOI).
Improve F2: data should be better described with rich metadata
Improve F3: downloaded data should include explicitly the identifier of the data (e.g. source)
Improve A2: not sure, no information regarding if metadata are accessible even when the data are no longer available
Improve I3: data should include qualified references to other data (which TSO or national authority are the main reference?)
R1.1 and R1.2: it should contain more clear and accessible data usage licence and associated provenance. regarding licence, there is only information in pdf. under “terms and conditions” it states not sub-licensable or transferrable.
I2: There is a long list of databases under sitemap, this can be linked also explanations.

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Electricity market information platform of German Federal Network Agency Bundesnetzagentur (BnetzA). It presents the most important electricity market data for Germany containing electricity market data such as electricity generation, consumption, import and export, market balancing and power plants in different periods of time (i.e. power plants data between 2015-2025 in hourly resolution, generation in 15 min.).
|| Germany is one of the pioneer countries in terms of energy data transparency. Energy researchers addresses databases from German Federal Network Agencies as a good example for openness and transparency.
|| F1 100% - F2 100% - F3 100% - F4 100%
A1.1 100% - A1.2 100% - A2 100%
I1 100% - I2 80% - I3 100%
R1.1 100% - R1.2 100% - R1.3 90%
|| Improve I2 for using vocabularies that follow FAIR principles

|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|}

== 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
|-
| [https://open-power-system-data.org/ OPSD] || [refer to DC table in word file] Administrative 70%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 80% - F4 100% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 80% - I3 100% / R1.1 100% - R1.2 50% - R1.3 90% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, json, jupyter
|-
| [https://www.eia.gov/ EIA] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 100% - F2 100% - F3 100% - F4 70% / A1.1 100% - A1.2 100% - A2 100%/ I1 100% - I2 100% - I3 70% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://openei.org/ OpenEI] || Administrative 80%, descriptive 100%, structural 100% || Medium || F1 50% - F2 70% - F3 70% - F4 50% / A1.1 100% - A1.2 50% - A2 50%/ I1 50% - I2 50% - I3 100% / R1.1 100% - R1.2 50% - R1.3 100% || ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xml, plain text, RDF, etc.'' xml, csv, text, PDF
|-
| [https://www.pse.pl/web/pse-eng/data PSE] || Administrative 80%, descriptive 100%, structural 100% || Rich || F1 80% - F2 100% - F3 100% - F4 100% - A1 100% - A1.1 100% - A1.2 50% - A2 100% - I1 100% - I2 100% - I3 80% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As xls, csv, pdf, etc.''
|-
| [https://www.nrel.gov/grid/data-tools.htmla NREL] || Administrative 100%, descriptive 100%, structural 80% || Rich || F1 100% - F2 100% - F3 80% - F4 100% - A1.1 100% - A1.2 100% - A2 100% - I1 80% - I2 80% - I3 100% - R1.1 100% - R1.2 100% - R1.3 80%
|| ''What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology?'' taxonomy || ''How are metadata implemented? As ??????xls, jpg, pdf, graphs, charts, ect.''
|-
| [https://transparency.entsoe.eu/ ENTSO-E Transparency Platform]
|| Administrative 50%, descriptive 50%, structural 50%
|| Metadata is partly described, some of basic metadata are missing or not clear to identify
|| F1 50 % - F2 50% - F3 20% - F4 100% A1.1 100% - A1.2 100% - A2 50% I1 100% - I2 80% - I3 100% R1.1 50% - R1.2 50% - R1.3 90%
|| Taxonomy
|| Csv, xlsx, xml, xml zip, graphs and charts

|-
| [https://www.smard.de/en/ SMARD (Strommarktdaten)]
|| Administrative 80%, descriptive 100%, structural 100%
|| Rich and basic metadata is available
|| F1 100% - F2 100% - F3 100% - F4 100% A1.1 100% - A1.2 100% - A2 100% I1 100% - I2 80% - I3 100% R1.1 100% - R1.2 100% - R1.3 90%
|| Taxonomy || csv, xls, xml

|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

WS1UC2

2020-06-03T08:52:20Z

Rezaa: /* Discussion on the choice of databases: */

WS1UC2

2020-06-03T07:58:55Z

Rezaa: /* Draft list of databases */

Talk:UC2

2020-06-03T07:55:50Z

Rezaa: Created page with "List of selected databases for the first step: OPSD EIA OpenEI PSE NREL ENTSO-E SMARD WorldBank We select four of them."

List of selected databases for the first step:

OPSD
EIA
OpenEI
PSE
NREL
ENTSO-E
SMARD
WorldBank

We select four of them.

WS1

2020-06-03T07:49:36Z

Rezaa: /* Gaps identified across use cases */

The first workshop of EERAdata is organized as an online webinar and hackathon from June, 2-4, 2020.

== Objective ==
* Learn about FAIR and open data practices in the energy and other research communities;
* Choose selected databases to be investigated in use cases. Discuss and summarize the reasons for selection.
* Analyze the state of FAIR/O principles for the selected database (with the help of the questionnaire and FAIR/O assessment tools).
* Evaluate the state of FAIR/O principles for the metadata of selected databases.
* Suggest general principles for the design of metadata (use-case- and domain-specific),
* Discuss top-level metadata adhering to FAIR/O principles (use-case- and domain-specific),
* Learn about the FAIRification of Data Management Plans (DMP).

== Read aheads ==

'''Obligatory:'''
* M. D. Wilkinson et al., “The FAIR Guiding Principles for scientific data management and stewardship,” Scientific Data, vol. 3, p. 160018, Mar. 2016. https://doi.org/10.1038/sdata.2016.18
* B. Mons et al., “Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud,” Information Services & Use, vol. 37, no. 1, pp. 49–56, Jan. 2017. https://doi.org/10.3233/ISU-170824
* EOSC HLEG (2018). Final report and recommendations of the Commission 2nd High Level Expert Group on the European Open Science Cloud (EOSC). Prompting an EOSC in practice. Available online: https://publications.europa.eu/en/publication-detail/-/publication/5253a1af-ee10-11e8-b690-01aa75ed71a1 (accessed: 18.07.2019).

'''Suggested read on the history of metadata:'''
Metadata - Shaping Knowledge from Antiquity to the Semantic Web by Richard Gartner, https://www.springer.com/gp/book/9783319408910

== Join and collaborate interactively! ==
The workshop is a hackathon! EERAdata is evolving jointly only! Join the discussions and work together online:
* [[Main_Page#Getting_started_with_EERAdata_wiki|EERAdata WIKI]]
* [[WS1#EERAdata_story_board|EERAdata storyboard]]
* [https://github.com/valeria6856/EERAdata EERAdata@github]
* [https://www.researchgate.net/project/Towards-a-FAIR-and-open-data-ecosystem-in-the-low-carbon-energy-research-community EERAdata@ResearchGate]
* Post your questions and comments on slido: https://app.sli.do/event/wrz7iwdh - OR go to [https://www.sli.do/ slido.com] and enter the event code: 23069

=== EERAdata story board ===
'''Objective:''' collect views from participants regarding energy data, energy metadata, FAIR/O problems etc. to support discussions, identification of gaps & needs (WP2) and elements to design the platform (WP3).

'''Questions:'''
* Q#1: What is your user story regarding FAIR/O energy data?
* Q#2: What is your user story regarding metadata?

Template to answer: As a <stakeholder>, I want <goal> so that <reason>.

'''How to post a story?'''
# Click on the link: https://padlet.com/janaschwanitz/aciywzt9fs1h70m2
# Click on plus at the right bottom to add a story.
# Choose as title depending on the question one wants to answer. Choose for Q#1: FAIR/O data, or for Q#2: metadata. In the example above, the title “metadata” was chosen.
# Type your sentence to let us know where the gaps and hopes are: The template is: As a <stakeholder>, I want <goal> so that <reason>.

'''Example:''' As a data-driven energy researcher, I want utopia - i.e. one-stop access to all relevant metadata -, so that I can browse available data, check where they are from and whether I can trust them when reusing.

'''How to comment a story?'''
* One can rate stories by clicking on a number of stars.
* One can comment stories as well as comments with words.
* It is anonymous commenting and adding of stories, as long as one does not login into one's personal profile at padlet.com.

=== EERAdata wiki - How to? ===
The easiest way is you simply start writing and editing. You can '''install an easy editor''' by doing what is described in the picture to the right.
[[File:Install easy editor.png|thumb|How to install an easy editor]]

Consult the [https://www.mediawiki.org/wiki/Special:MyLanguage/Help:Contents User's Guide] for information on using the wiki software.
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:Configuration_settings Configuration settings list]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:FAQ MediaWiki FAQ]
* [https://lists.wikimedia.org/mailman/listinfo/mediawiki-announce MediaWiki release mailing list]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Localisation#Translation_resources Localise MediaWiki for your language]
* [https://www.mediawiki.org/wiki/Special:MyLanguage/Manual:Combating_spam Learn how to combat spam on your wiki]

=== EERAdata on github ===
Link here and share your thoughts and issues! Note, work in progress.
* [https://github.com/valeria6856/EERAdata EERAdata@github]

=== EERAdata @ Research Gate ===
Link here and share your thoughts and issues! Note, work in progress.
* [https://www.researchgate.net/project/Towards-a-FAIR-and-open-data-ecosystem-in-the-low-carbon-energy-research-community EERAdata@ResearchGate]

=== Just have fun! ===
==== Metadata memory game ====
'''Read before playing:'''

This is a little memory game where players need to '''identify triples''', that is three tiles that belong to one data set. All of them relate to low carbon energy. Some tiles have the form of a picture, others show metadata descriptions (in various formats) and some are even sound files. So, the game is to have fun, while learning about metadata. Try out if you can find all triples. Note if you have opened 3 tiles and they do not match, all will automatically close. Just as you know it from a real-life memory game.
[http://eeradata.webfactional.com/memory/memory.html '''Link''']

== Agenda Day 1 ==
Builds on read aheads. Online talks and discussions. Space for interaction with participants after each presentation. Moderated discussion of collected comments.

{| class="wikitable"
|-
! Time slot !! Topic
|-
| 10.00-10.20 || '''Welcome and introduction''' with workshop goals and procedures: “EERAdata - Towards Utopia for low carbon energy research”, Valeria Jana Schwanitz, HVL & PI EERAdata. Link: [http://eeradata.webfactional.com/WS1/EERAdata_WS1.pdf]
|-
| 10.20-12.15 || '''Online lectures''':
* “The EOSC Nordic: machine-actionable FAIR maturity evaluations & the FAIRification of data repositories” - Andreas Jaunsen, Nordforsk & EOSC-Nordic. Link: [http://eeradata.webfactional.com/WS1/EOSC-Nordic_FAIR_data_presentation_2_June_2020.pdf]
* “OpenAIRE: Open Access Infrastructure for Research in Europe”, Ilaria Fava, OpenAIRE. Link: [http://eeradata.webfactional.com/WS1/20200602_OpenAIRE-EERAdata.pdf]
A short break of 15 min -
* “Community-driven metadata and ontologies for Materials Science and their key role in artificial-intelligence tools”, Luca Ghiringhelli, FHI Berlin. Link: [http://eeradata.webfactional.com/WS1/Ghiringhelli_FAIRmetadata_EERAdata.pdf]
* “Metadata practices from IRP Wind”, Anna Maria Sempreviva, DTU. Link: [http://eeradata.webfactional.com/WS1/EERAdata_Sempreviva.pdf]
|-
| 12.15-13.00 || ''Lunch Break''. Play the EERAdata game “Utopia and metadata”. Or any time.
|-
| 13.00-14.00 || '''Online lectures''':
* “Humanities and data: for a community-driven path towards FAIRness”, Elena Giglia, UNITO.
* “RISIS - An e-Infrastructure for the STI-Policy research community”, Thomas Scherngell, AIT. Link: [http://eeradata.webfactional.com/WS1/RISIS2_eera_data.pdf]
|-
| 14.00-14.30 || ''Break'' - Game “Utopia and metadata”. Or any time.
|-
| 14.30-16.00 || '''Discussion''' to compile a to-do list for work in use cases on the second day. Serves as a guiding and aligning process. Lead by WP2, August Wierling/Valeria, HVL.
|}

=== Notes from Day 1 ===
==== Welcome and Introduction ====
* Introduction by Valeria:
** What is the project EERAdata about
** In the energy system the data revolution speeds up
** Data on:
*** Wheather patterns
** more and more application are becomign available
*** digital twins: steering nuclear plants just from the scree
** Buildings get energy passports
** era of digital reporting and compliance arises
** Importance of linking across different formats and topics
**time spent as aresearcher: Large amount of time spent on data sorting, formatting, searching, etc
* Valeria invites everyone again to write down their story connected to energy data on the EERAdata storyboard (see Link on Main page WIKI)
** This will be valuable in moving forward with the ideas for the EERAdata project
*Valerias personal starting point regarding EERAData:
** Work in towards enabling FAIR and open data for the low carbon energy research community
* We hope to add what we learn in this 3 days to the EERA WIKI
** guidance platform for low carbon energy researchers
* at the end we hope we come to a set of meta data standards for energy data
* what could be the utopia for energy data researcher:
** emagine lookign for citizen led initiatives in PV
** search for keyworkds on a website -> and recieve a list of datasets related to this topic
** for all those datasets:
*** see amount of initiatives available
*** when where they updated the last time
*** links provided to access the data
*** are the certified as FAIR/O and who is certifying institution
*** refine search with specific filter options
*** information on the quality/ data collection and processing methodology
*** option for simple data analysis operations
*** -> get an overview over richness of data
** -> we are still very far away from this utopia
* Goals of this Workshop:
** listen to various best practices
** day 2: discuss the provided examples
** day 3: presentation of findings from day 2 discussions
** day 3 afternoon: Data management plans (DMPs)

==== The EOSC Nordic: machine-actionable FAIR maturity evaluations & the FAIRification of data repositories ====
* '''notes incoplete, will be added later'''
**What is the EOSC:
*** goal:
**** enable reserachers to access data across domains and disciplines as easy as possible
**** locating the relevant data
*** vision:
**** all european data shoud be available to research
**** does not mean that all data is stored centrally, but that all databases are interconnected
* WP 4 members: include all nordic countries
* How can we improve datasets:
** source code:
***
* recommendations:
* evaluations:
** why do we evaluate repositories?
*** what is the level of FAIRness?
*** about 10 datasets per repository
*** FAIR score
*** Positive highlights:
****
*** FAIR score of all evaluated datasets:
**** majority at 0.10 out of 1
* coming tasks:
**
**
* question from Valeria: would it be possible to use their scoring system to assess one of the EERAdata datasets?
** Answer:

==== OpenAIRE: Open Access Infrastructure for Research in Europe ====
* Introduction into OPENAIRE:
** 2007 pilot publications
**
* Openaire is bridging the 2 worlds where science is performed and published
* In practice:
** services that monitor, assess and accelerate open science
** facilitate research communities adoption of open science
* who is openaire:
** 50 partners all over europe
** experts in open science in every EU member states
** regional coordinators
** topical coordinators working on policies for open science
** openaire is an infrastucture
** last phase of openaire: citizen science
*** openaire end in 12/2020
** 4 regions: North-, east-, west-, south europe
** large diferences in needs from country to country
*** -> find best solutions to develop open science for each country
** connections to open science community in North america, Japan, ...
* openaire has published set of guidelines in cooperation with international network:
* provided services:
** providing policy advice
** training and support
** open science infrastructure
** How to achieve FAIRness in sharing resreach data?
** guidelines on how to provide open access to publications, not only data
* How we support:
** Helpdesk: questions, FAQ
**
**
* Openaire provides guides for:
** researchers
** content providers
** funders
* Webinars:
* outreach:
** 230 webinars
** 22 NOADS are involved in EOSC WGs
* explore portal:
** search interface for all content available through Openaire
*** 40M publications: shows most crucial metadata
** EERADATA record:
*** for now, no information, as no data has been collected from repositories yet
* Openaire connect project:
** gateway for reserach communities
** allows research communities to build a gateway that collects different data relevant to your research community
* COVID-19 research community:
** ca 3200 research datasets
** 113 relates projects
* OpenAIRE provide:
** allows connection of repositories to openAIRE
* Zenodo: repository developed by openaire that allows institutions to publish their reserach output
* AGROS: machines readable data repository

* comment from Andreas Jaunsen: today, research projects spent roughly 80% of their research time on data gathereing/ processing
**-> open access aims to reduce this by only having to precess the data once

* Carsten Hoyer comments:
** create a metadata catalogue
** link the provenance information of data
*** -> track who has done what with the data

* Question from August:
* Rich metadata: search specifically for the research question for one on paper? How could this be achieved?
** openaire explore: works as normal search engine -> high "noise" (unwanted search results)

* incentives for researchers to provide rich metadata?
** Use of commen ontology allows for more refined serach results

==== Community-driven metadata and ontologies for Materials Science and their key role in artificial-intelligence tools ====
* Key message:
**
* FAIR: Findable, Accessible, Interoperable, Reusable
** Findable:
*** Uniqueness of the date
** accessible:
*** URL, accessible vi API
** Interoperability:
** reusability: Metadata should be as desciptive as possible
* NOMAD-FAIRDI Workshop:
** Shared metadata and data formats for big-data driven material science
* Data object:
** Metadata:
*** Unique identifier, Structure of the data, Method
*** should contain information of teh full provenance of the data:
**** where does it come from? Another database? A calculation? etc?
*** '''Definition:'''
* NOMAD Respository structure:
** Nomad Repository
** Conversion Layer
** The archive
*** Three access points:
****
* Computational material sciences:
**
* Ontology:
*
* Questions:
** what happens to metadate when you physically go from one structure to a combined structure? How do you combine the metadate of the two initial structures?
***
** from EERAData perspective: in material for low carbon energy use case, what could be valuable contribution of EERAData to reserach community?
*** Ontologies are driven by the use cases.
*** summarizing: Excersizing a fine grain use case such as solar PV. Linking different levels of metadata. Further develop metadata at the use case level. How to link across use cases?

==== Metadata practices from IRP Wind ====
* Starting point was the inability to find information
* This presentation is about research data
* digital objects can be assets due to competitive advantages that the digital objects provides
* Interpretion of FAIR: F A and I data results in R data
** Reusable data multiplies the value of the data
* '''"Data should be as opeb as possible but as closed as neccessary"'''
* Issue: How to make data findable but safe
** Misstrust/ fear that own data might be missused/ one looses the competitive advantage
* Issue: Data findability
** Datasets are organized in different ways
**
* IRP Metadate and taxonomies:
** Base metadate as defined by Dublin core standards
** Additional non-Dublin Core taxonomies
* Creating a taxonomy:
** Expert elicitation: Group of experts creates a taxonomy which is then reviewed by wider reserach community
** Author keywords: Map keywords used by authors along similarities in meaning, frequency of usage
*** Pros: Allows tracking of trends
*** Cons: Mix of disciplines, models, etc; Many errors and ambiguities; single generic words with a broad range of possible interpretations.
* Virtual libraries:
** Two aspects: Seach engine (metadata) and Data storage (data)
*** Linked databases allow being searched centrally, but data is stored decentrally
* conclusion:
** Purpose of a web data portal is to (1) connect safely data owners and users and (2) inform on availability of Data, not neccessarily provide direct access to data

* Discussion:
** How to create and maintain metadata? How to allow dynamic updates of data? How to deal with language issues (non-native speaketors, translation,...)?
** Third option to create taxonomies: Use machines or algorithms to link the different taxonomy development approaches?
** General metadata standards exist, what is needed are domain specific metadata
** Two seperate categrories: Metadata and vocabolaries

==== Humanities and data: for a community-driven path towards FAIRness ====
* Humanities are often a bit neglected in the data community
* Who is ALLEA?
*Who is Co-operas?
** implementation network
** goal: taking care of the whole cycle of humanities reserach from data gathering to publishing
* Data management life cycle:
** Identification
** Planning
** Gathering
** maintaining, processing
** dissimination
* FAIR Data in humanities?
** currently, the FAIR principles will persist in shaping the data landscape in humanities
*'''"There is risk and value in being a first mover, but there is more risk in being a follower"'''
* Is data still a dirty word in the SSH?
** In the humanities, we all use Data, even if we are not aware of it
** Data in humanities is more prone to interpretation than in STEM disciplines -> harder to grasp
* What is data in the humanities:
** Never "raw" data
** Data is always an expression of the method
** there is always a choice
** There is always an interpretation
** there is always a dicussion
* Data pillars:
** Data are so divers that it is impossible to converge on a common definition
*** to define data, go as deep as possible into reserach practices
* risk of oversimplification
* preliminary issues of FAIRness:
** In which step and how should FAIR principles be applied?
** what language?
** Lack of skills among researchers
** registry of existing tools
** need to preserve specifities of how we do research in the humanities
** services and tools need to be sustainable
* Findability:
** metadate needs to be seperated from data
** maintain richness of metadata
**
* difficulties in humanities:
** data in humanities are linked to cultural, political aspects
* Nest steps:
** Data stewardship wizard for SSH
* '''Accessible does not equate to open'''
* interoperability:
** data is often so closely tailored to a specific project, that interoperability in impossible
* reusability:
** Copyright is still an issue
** need of legal advice
** In the end, reuse is the final aim of FAIRness
** reusability is also a measure of the impact of your data
* mindshift:
** currently everything is closed, except for a few daring frontrunners
** in future, everything should be open, except for a few absolutely neccessary cases.

==== RISIS - An e-Infrastructure for the STI-Policy research community ====
* RISIS:
** within social sciences
** strong connection to economics
** Measuring innovation: long tradition of using quantitative indicators and qualitative models
** started in 2014
** focuss on linking R&I datasets
** harmonizing of Organization names (Organization are main objects of study in this project)
* Datasets:
** firm innovation capabilities
** R&D output databases
** Public research and higher education
** Database on policy learning
* need to adapt to new developments within research communities
* RISIS Knowmak tool:
** openly and freely present indicators in R&I gathered from RISIS datasets
* RISIS dataset portal
** Check metadata of available datasets
** choose relevant datasets
** fill out data access aplication form
** application will be assessed by external reviewers
** if approved, acces is granted

* Discussion:
** How do you integrate your datasets with other datasets (e.g. business registers, national industry sector classifications)
*** bussiness registers often not open, but need purchasing, hence integration often not possible
*** external classifications (e.g. industry sector classifications) are often included, but a inetrnal ontology was also developed
** Are the metadata desciptions machien readable? Or only available as PDF?
*** Yes they are also available as machine readable formats, but PDF as qualitative version is imprtant for external presentation

==== Discussion/ to-do list for work in use cases ====
* Questions:
** What is the take home message for you?
**

* Use case 1:
** main goal is the re-usability
** we need to assess the databases that were chosen previously
** best preactices: EOSC,

* Use Case 2:
** Main issue in this use case is privacy/ sensitivity
** '''security comes first'''
** Tradeoff between unsiversal metadata language and domain specific language

* Use case 3:
** Linguistics is a problem
** As soon as we change the application of material/ material data, we change/need to change the metadata
** Find similarities of already existing metadata

* Use case 4:
** big challange regarding the linguistic problem
*** Diferent language
*** Different interpretation of same terms
** Pick low hanging databases that are far away from FAIR principles

* EERAData is probably more about asking the right questions than providing the right answers, there are already a lot of answers out there
* Interests of HVL:
** Assess FAIRness of our own COMETS database
** Assess how EERAdata adheres to new EU funding requirements

* Outcome of first and second workshop is hopefully some drafts for low carbon energy metadata standards, which can be reviewed by experts

* EERAdata platform responsibles will join in on all use case discussions on second WS day
* '''"Ontology is a formal represenation of the knowledge of a community on a specific purpose"'''

== Agenda Day 2 ==
=== News of the day before ===

Not energy, but an inspiring connection: Perhaps unexpected, or perhaps even not: DNA helps to puzzle pieces of Qumran role. DNA taken from animal skins that were used to write on ...
[[File:Selection 186.png|thumb|Perhaps unexpected, or perhaps even not: DNA helps to puzzle pieces of Qumran role. DNA taken from animal skins that were used to write on ...]]

=== METADATA - DISCUSSIONS in use cases, parallel sessions ===
Work in use cases on databases and metadata, led by use case leaders. Suggested outline:

* '''10-12 Discuss and update preliminary state of FAIR/O for the use case.''' Use the prepared draft of databases to check compliance with FAIR principles (tools: WP3 questionnaire and others). Compare the assessment results for each database. Observe and discuss agreements and differences across the evaluation tools. Generate the overall picture for FAIR/O compliance for the use case to pin down the state of art. Let’s see if we come to the same result as in our initial assessment for the application (traffic lights). Continuously make notes to report later on results. Select a responsible person. Objective: select 3-5 databases per use case. Discuss which databases to select. One to cover use-case specific challenges; and one with cross-use case relevance, and one a low hanging fruit for which it would be relatively easy to improve the current FAIR/O status.
* 13-15 Joint brainstorming to discuss FAIR/O state of the metadata for the selected use cases. Evaluate: What is the current description of metadata? How extensive are they? Is only administrative information provided? Or richer context description? What frameworks for metadata are used: taxonomy? thesaurus? ontology? How is the metadata information technically implemented: plain text file? xml? rdf? ... Identify use case specific issues with metadata - What are the gaps? What is perceived as a hard nut to crack? Pay special attention to the metadata of the databases and fill out the table provided WP2. Continuously make notes to report results the next day! Select a responsible person!
* 15-17 Joint recording of lessons learned. Create and/or update the WIKI for the use case with literature, gaps, best practices, FAIR/O discussion, metadata discussion, suggested next steps, .... Get your head around what to report next day! Plan for 20 min. See the links to WIKI page templates below (Notes from Day 2).

=== Gaps identified across use cases ===

{| class="wikitable"
|-
! Use case 1 !! Use case 2 !! Use case 3 !! Use case 4
|-
| [[UC1|Buildings efficiency]] || [[UC2|Power transmission & distribution networks]] || [[UC3|Material solutions for low carbon energy]] || [[UC4|Low carbon energy and energy efficiency policies]]
|-
|
[[File:UC1 logo.jpg|thumb]]
||
[[File:UC 2 logo.jpg|thumb]]
||
[[File:UC 3 logo.jpg|thumb]]
||
[[File:UC 4 logo.jpg|thumb]]
|-
|
* qualitative nature of data limiting interoperability
* data availability issues for time-series
* multiplicity and scattered nature of data sources (households, industries, utility companies, municipalities)

||
* heterogeneous nature of data limits interoperability
* data privacy and sensitivity
* multiplicity nature of data sources with various stakeholders
||
* microscopic use cases resembling the existing one about PV
* link between microscopic and macroscopic materials (e.g., turbine blades)
* metadata for applications of materials
* linking to other fields
||
* metadata for images
* language and terminology (e.g., records instead of data)
|}

Note: This schedule is a suggestion. Adjust and organize breaks as needed.

=== Notes from Day 2 ===
* Use case 1 - Summary: [[UC1]], Detailed notes: [[WS1UC1]]
* Use case 2 - Summary: [[UC2]], Detailed notes: [[WS1UC2]]
* Use case 3 - Summary: [[UC3]], Detailed notes: [[WS1UC3]]
* Use case 4 - Summary: [[UC4]], Detailed notes: [[WS1UC4]]

== Agenda Day 3 ==
Reporting experience from use case applications. Prepare the next workshop on workflows and metadata. Introduction and discussion of data management plans.

{| class="wikitable"
|-
! Time slot !! Topic
|-
| 10-12.30 || '''Discussion''' lead by WP2. Report from use case experiences (by use case leaders). Wrap up.
|-
| 12.30-13.30 || ''Lunch break''
|-
| 13.30-15.00 || '''Data Management Plans'''
* Presentation “Introduction to DMP and best practices” by Trond Kvamme, NSD
* Presentation on machine-actionable DMPs by Tomasz Miksa, TU Vienna
* Discussion of EERAdata DMP draft (August, HVL)
* Short break of 15 min
|-
| 15.15-16.00 || '''Wrap up''' of workshop with feedback from invited experts.
|}

=== Notes from Day 3 ===
* Bulleted list item

UC2

2020-05-29T14:44:24Z

Rezaa: /* List of selected databases */

UC2

2020-05-29T14:43:17Z

Rezaa: /* List of selected databases */

UC2

2020-05-29T14:41:50Z

Rezaa: /* List of selected databases */

UC2

2020-05-29T14:41:22Z

Rezaa: /* Metadata assessments */

UC2

2020-05-29T14:38:53Z

Rezaa: /* Metadata assessments */

UC2

2020-05-29T12:00:44Z

Rezaa: /* List of selected databases */

UC2

2020-05-29T11:52:56Z

Rezaa: /* List of selected databases */