EERAdata Wiki - User contributions [en]

UC1

2020-05-23T17:30:39Z

2A04:2747:11DE:1E00:9017:64FD:8AA2:EDD9: /* Metadata assessments */

== Buildings efficiency ==

=== General description of use case ===
With 40% of total energy consumption, buildings are major consumers of energy causing 36% of the total CO2 emissions. Thereby, the building sector has a large untapped potential for the reduction of CO2 emissions by optimizing in construction and management. The EU has issued a Directive on the Energy Performance of Buildings (EPBD) as the main EU policy instrument to improve in this regard (Directive 2002/91/EC). The directive involves a framework for assessing the energy performance of buildings through Energy Performance Certificates (EPCs) that need to include reference values, such as current legal standards. Hence, the relationship between buildings and energy, impacts a wide spectrum from strategic to operational concerns, including energy efficiency investment decisions, buildings energy performance management, energy efficiency policies, smart buildings, and energy disaggregation. This makes data on energy efficiency in buildings crucial for the discussion and the decision-making in many practical contexts by households, academicians, or policymakers. Moreover, a wide variety of information is needed, starting from the existing building stock to solutions in ventilation and air conditioning, socio-demographic information, cultural perception of thermal comfort to climatic and weather information. To some extent, this data is available; however, databases are unorganized and not interlinked. A comprehensive collection of European buildings and urban stock data has been identified by the [https://www.effesus.eu/wp-content/uploads/2016/01/D-1.1_European-building-and-urban-stock-data-collection.pdf EFFESUS project], serving as a starting point for the use case.

A specific part of energy consumption in residential buildings is due to the use of household appliances. Time series of corresponding demand profiles on this scale are typically not open, but constitute business assets of utilities. A wealth of information on such data is produced due to the massive rollout of smart meters across Europe. Access to this data raises important concerns regarding privacy issues (Véliz and Grunewald 2018). Thus, legal restrictions as well as commercial interests have to be accounted for. Finally, analyzing this information by e.g. geolocation or social strata is key to mitigate energy poverty making the energy transition inclusive for all.

To this end, the use case on buildings efficiency has three main goals: 1) identifying the available metadata on buildings efficiency and constructing a metadata repository of available data, 2) assessing the level of FAIRness and openness of the available data with the contribution of experts from the field in the planned workshops, and 3) contributing to the FAIRification and opening of the available data respecting privacy concerns. In doing so, it will utilize existing databases such as IEEE,[https://www.masea-ensan.de/ Masea], [https://openei.org/wiki/Main_Page OpenEI], [https://www.designation.eu/en/open-data-platform-for-energy-efficiency-in-buildings/ Open Data Platform for Energy Efficiency in Buildings], the [http://trynthink.github.io/buildingsdatasets/ United States Department of Energy databases], the [https://ec.europa.eu/energy/en/topics/energy-efficiency/energy-performance-of-buildings/eubuildings European Buildings Stock Observatory] and the databases developed by the [https://www.entranze.eu/ ENTRANZE] and the [http://www.exceedproject.eu/ ExcEED] project. While these databases provide information relevant for, e.g. for the retrofitting of houses, databases specifically targeting electric demand due to household appliances are rare. The few examples include [https://open-power-system-data.org/ Open Power System Data], [https://www.vs.inf.ethz.ch/res/show.html?what=eco-data ECO] ,[https://sourceforge.net/projects/greend/ GREEND], [http://redd.csail.mit.edu/ REDD], [http://jack-kelly.com/data/ UK-DALE], [https://oehu.org/ OEHU], and home consumption data provided by [https://data.gov.uk/dataset/1b41eb5c-4b7a-4f60-ae0f-3a78c73953bf/energy-consumption-for-selected-bristol-buildings-from-smart-meters-by-half-hour local British communities]. Data regarding energy poverty are collected at the [https://www.energypoverty.eu/ EU Energy Poverty Observatory].

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC1]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC1]].
|| What FAIR/O target was decided?
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| 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 belows summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of [[WS1UC1]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC1

2020-05-23T17:29:57Z

2A04:2747:11DE:1E00:9017:64FD:8AA2:EDD9: /* List of selected databases */

== Buildings efficiency ==

=== General description of use case ===
With 40% of total energy consumption, buildings are major consumers of energy causing 36% of the total CO2 emissions. Thereby, the building sector has a large untapped potential for the reduction of CO2 emissions by optimizing in construction and management. The EU has issued a Directive on the Energy Performance of Buildings (EPBD) as the main EU policy instrument to improve in this regard (Directive 2002/91/EC). The directive involves a framework for assessing the energy performance of buildings through Energy Performance Certificates (EPCs) that need to include reference values, such as current legal standards. Hence, the relationship between buildings and energy, impacts a wide spectrum from strategic to operational concerns, including energy efficiency investment decisions, buildings energy performance management, energy efficiency policies, smart buildings, and energy disaggregation. This makes data on energy efficiency in buildings crucial for the discussion and the decision-making in many practical contexts by households, academicians, or policymakers. Moreover, a wide variety of information is needed, starting from the existing building stock to solutions in ventilation and air conditioning, socio-demographic information, cultural perception of thermal comfort to climatic and weather information. To some extent, this data is available; however, databases are unorganized and not interlinked. A comprehensive collection of European buildings and urban stock data has been identified by the [https://www.effesus.eu/wp-content/uploads/2016/01/D-1.1_European-building-and-urban-stock-data-collection.pdf EFFESUS project], serving as a starting point for the use case.

A specific part of energy consumption in residential buildings is due to the use of household appliances. Time series of corresponding demand profiles on this scale are typically not open, but constitute business assets of utilities. A wealth of information on such data is produced due to the massive rollout of smart meters across Europe. Access to this data raises important concerns regarding privacy issues (Véliz and Grunewald 2018). Thus, legal restrictions as well as commercial interests have to be accounted for. Finally, analyzing this information by e.g. geolocation or social strata is key to mitigate energy poverty making the energy transition inclusive for all.

To this end, the use case on buildings efficiency has three main goals: 1) identifying the available metadata on buildings efficiency and constructing a metadata repository of available data, 2) assessing the level of FAIRness and openness of the available data with the contribution of experts from the field in the planned workshops, and 3) contributing to the FAIRification and opening of the available data respecting privacy concerns. In doing so, it will utilize existing databases such as IEEE,[https://www.masea-ensan.de/ Masea], [https://openei.org/wiki/Main_Page OpenEI], [https://www.designation.eu/en/open-data-platform-for-energy-efficiency-in-buildings/ Open Data Platform for Energy Efficiency in Buildings], the [http://trynthink.github.io/buildingsdatasets/ United States Department of Energy databases], the [https://ec.europa.eu/energy/en/topics/energy-efficiency/energy-performance-of-buildings/eubuildings European Buildings Stock Observatory] and the databases developed by the [https://www.entranze.eu/ ENTRANZE] and the [http://www.exceedproject.eu/ ExcEED] project. While these databases provide information relevant for, e.g. for the retrofitting of houses, databases specifically targeting electric demand due to household appliances are rare. The few examples include [https://open-power-system-data.org/ Open Power System Data], [https://www.vs.inf.ethz.ch/res/show.html?what=eco-data ECO] ,[https://sourceforge.net/projects/greend/ GREEND], [http://redd.csail.mit.edu/ REDD], [http://jack-kelly.com/data/ UK-DALE], [https://oehu.org/ OEHU], and home consumption data provided by [https://data.gov.uk/dataset/1b41eb5c-4b7a-4f60-ae0f-3a78c73953bf/energy-consumption-for-selected-bristol-buildings-from-smart-meters-by-half-hour local British communities]. Data regarding energy poverty are collected at the [https://www.energypoverty.eu/ EU Energy Poverty Observatory].

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]]
|| Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx."
|| Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC1]].
|| What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page of [[WS1UC1]].
|| What FAIR/O target was decided?
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| 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 belows summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of the [[discussion page of WS1]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC1

2020-05-23T17:28:01Z

2A04:2747:11DE:1E00:9017:64FD:8AA2:EDD9: /* List of selected databases */

== Buildings efficiency ==

=== General description of use case ===
With 40% of total energy consumption, buildings are major consumers of energy causing 36% of the total CO2 emissions. Thereby, the building sector has a large untapped potential for the reduction of CO2 emissions by optimizing in construction and management. The EU has issued a Directive on the Energy Performance of Buildings (EPBD) as the main EU policy instrument to improve in this regard (Directive 2002/91/EC). The directive involves a framework for assessing the energy performance of buildings through Energy Performance Certificates (EPCs) that need to include reference values, such as current legal standards. Hence, the relationship between buildings and energy, impacts a wide spectrum from strategic to operational concerns, including energy efficiency investment decisions, buildings energy performance management, energy efficiency policies, smart buildings, and energy disaggregation. This makes data on energy efficiency in buildings crucial for the discussion and the decision-making in many practical contexts by households, academicians, or policymakers. Moreover, a wide variety of information is needed, starting from the existing building stock to solutions in ventilation and air conditioning, socio-demographic information, cultural perception of thermal comfort to climatic and weather information. To some extent, this data is available; however, databases are unorganized and not interlinked. A comprehensive collection of European buildings and urban stock data has been identified by the [https://www.effesus.eu/wp-content/uploads/2016/01/D-1.1_European-building-and-urban-stock-data-collection.pdf EFFESUS project], serving as a starting point for the use case.

A specific part of energy consumption in residential buildings is due to the use of household appliances. Time series of corresponding demand profiles on this scale are typically not open, but constitute business assets of utilities. A wealth of information on such data is produced due to the massive rollout of smart meters across Europe. Access to this data raises important concerns regarding privacy issues (Véliz and Grunewald 2018). Thus, legal restrictions as well as commercial interests have to be accounted for. Finally, analyzing this information by e.g. geolocation or social strata is key to mitigate energy poverty making the energy transition inclusive for all.

To this end, the use case on buildings efficiency has three main goals: 1) identifying the available metadata on buildings efficiency and constructing a metadata repository of available data, 2) assessing the level of FAIRness and openness of the available data with the contribution of experts from the field in the planned workshops, and 3) contributing to the FAIRification and opening of the available data respecting privacy concerns. In doing so, it will utilize existing databases such as IEEE,[https://www.masea-ensan.de/ Masea], [https://openei.org/wiki/Main_Page OpenEI], [https://www.designation.eu/en/open-data-platform-for-energy-efficiency-in-buildings/ Open Data Platform for Energy Efficiency in Buildings], the [http://trynthink.github.io/buildingsdatasets/ United States Department of Energy databases], the [https://ec.europa.eu/energy/en/topics/energy-efficiency/energy-performance-of-buildings/eubuildings European Buildings Stock Observatory] and the databases developed by the [https://www.entranze.eu/ ENTRANZE] and the [http://www.exceedproject.eu/ ExcEED] project. While these databases provide information relevant for, e.g. for the retrofitting of houses, databases specifically targeting electric demand due to household appliances are rare. The few examples include [https://open-power-system-data.org/ Open Power System Data], [https://www.vs.inf.ethz.ch/res/show.html?what=eco-data ECO] ,[https://sourceforge.net/projects/greend/ GREEND], [http://redd.csail.mit.edu/ REDD], [http://jack-kelly.com/data/ UK-DALE], [https://oehu.org/ OEHU], and home consumption data provided by [https://data.gov.uk/dataset/1b41eb5c-4b7a-4f60-ae0f-3a78c73953bf/energy-consumption-for-selected-bristol-buildings-from-smart-meters-by-half-hour local British communities]. Data regarding energy poverty are collected at the [https://www.energypoverty.eu/ EU Energy Poverty Observatory].

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]] || Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx." || Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC1]]. || What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page
of [[WS1UC1]]. || What FAIR/O target was decided?
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| 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 belows summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of the [[discussion page of WS1]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

UC1

2020-05-23T17:26:50Z

2A04:2747:11DE:1E00:9017:64FD:8AA2:EDD9: /* List of selected databases */

== Buildings efficiency ==

=== General description of use case ===
With 40% of total energy consumption, buildings are major consumers of energy causing 36% of the total CO2 emissions. Thereby, the building sector has a large untapped potential for the reduction of CO2 emissions by optimizing in construction and management. The EU has issued a Directive on the Energy Performance of Buildings (EPBD) as the main EU policy instrument to improve in this regard (Directive 2002/91/EC). The directive involves a framework for assessing the energy performance of buildings through Energy Performance Certificates (EPCs) that need to include reference values, such as current legal standards. Hence, the relationship between buildings and energy, impacts a wide spectrum from strategic to operational concerns, including energy efficiency investment decisions, buildings energy performance management, energy efficiency policies, smart buildings, and energy disaggregation. This makes data on energy efficiency in buildings crucial for the discussion and the decision-making in many practical contexts by households, academicians, or policymakers. Moreover, a wide variety of information is needed, starting from the existing building stock to solutions in ventilation and air conditioning, socio-demographic information, cultural perception of thermal comfort to climatic and weather information. To some extent, this data is available; however, databases are unorganized and not interlinked. A comprehensive collection of European buildings and urban stock data has been identified by the [https://www.effesus.eu/wp-content/uploads/2016/01/D-1.1_European-building-and-urban-stock-data-collection.pdf EFFESUS project], serving as a starting point for the use case.

A specific part of energy consumption in residential buildings is due to the use of household appliances. Time series of corresponding demand profiles on this scale are typically not open, but constitute business assets of utilities. A wealth of information on such data is produced due to the massive rollout of smart meters across Europe. Access to this data raises important concerns regarding privacy issues (Véliz and Grunewald 2018). Thus, legal restrictions as well as commercial interests have to be accounted for. Finally, analyzing this information by e.g. geolocation or social strata is key to mitigate energy poverty making the energy transition inclusive for all.

To this end, the use case on buildings efficiency has three main goals: 1) identifying the available metadata on buildings efficiency and constructing a metadata repository of available data, 2) assessing the level of FAIRness and openness of the available data with the contribution of experts from the field in the planned workshops, and 3) contributing to the FAIRification and opening of the available data respecting privacy concerns. In doing so, it will utilize existing databases such as IEEE,[https://www.masea-ensan.de/ Masea], [https://openei.org/wiki/Main_Page OpenEI], [https://www.designation.eu/en/open-data-platform-for-energy-efficiency-in-buildings/ Open Data Platform for Energy Efficiency in Buildings], the [http://trynthink.github.io/buildingsdatasets/ United States Department of Energy databases], the [https://ec.europa.eu/energy/en/topics/energy-efficiency/energy-performance-of-buildings/eubuildings European Buildings Stock Observatory] and the databases developed by the [https://www.entranze.eu/ ENTRANZE] and the [http://www.exceedproject.eu/ ExcEED] project. While these databases provide information relevant for, e.g. for the retrofitting of houses, databases specifically targeting electric demand due to household appliances are rare. The few examples include [https://open-power-system-data.org/ Open Power System Data], [https://www.vs.inf.ethz.ch/res/show.html?what=eco-data ECO] ,[https://sourceforge.net/projects/greend/ GREEND], [http://redd.csail.mit.edu/ REDD], [http://jack-kelly.com/data/ UK-DALE], [https://oehu.org/ OEHU], and home consumption data provided by [https://data.gov.uk/dataset/1b41eb5c-4b7a-4f60-ae0f-3a78c73953bf/energy-consumption-for-selected-bristol-buildings-from-smart-meters-by-half-hour local British communities]. Data regarding energy poverty are collected at the [https://www.energypoverty.eu/ EU Energy Poverty Observatory].

== List of selected databases ==
During the first workshop (see notes from Day 2), the following databases were selected to analyze and improve their compliance with FAIR and Open data principles:
{| class="wikitable"
|-
! Name of database !! Short description !! Reasoning of choice !! Current state of FAIR/O principles !! Target of FAIR/O to achieve within EERAdata
|-
| [[Link to database 1|Database 1]] || Write a short description, e.g., "Database 1 is about XXX, containing XXX data, covering the period xxx." || Summarize shortly the main reasons, why this DB was chosen. Link to the discussion page of [[WS1UC1]]. || What is the current FAIR/O state for this database. Summarize here. In case more space is needed, link to a section of the discussion page
of the use case for WS1[[WS1UC1]]. || What FAIR/O target was decided?
|-
| Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example
|-
| 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 belows summarizes the current state and issues identified during WS 1:
{| class="wikitable"
|-
! Name of database !! Type of metadata provided !! Extend of metadata provided !! Level of implementation of FAIR/O principles !! Frameworks for metadata used !! Technical implementation of metadata
|-
| [[Link to database 1|Database 1]] || Which types of metadata are covered? Administrative, descriptive, structural, provenance of data, etc.? || Summarize: Is it rich or basic metadata provided for each of the types? || Check the Wilkinson criteria for metadata and summarize here. In case more space is needed, link to a section of the [[discussion page of WS1]]. || What framework is used, e.g., controlled vocabulary, taxonomy, thesaurus, ontology? || How are metadata implemented? As xml, plain text, RDF, etc.
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|-
| Example || Example || Example || Example || Example || Example
|}

WS1UC1

2020-05-23T17:25:35Z

2A04:2747:11DE:1E00:9017:64FD:8AA2:EDD9: /* Notes from the afternoon session */

This page provides space for notes from workshop discussions of use case 1 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 [[UC1#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Draft list of databases ===
* Bulleted list item

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

== Notes from the afternoon session ==
The afternoon session is dedicated to discussing metadata for the selected databases. The aim of the afternoon session is to fill out [[UC1#Metadata_assessments|table 2 of the wiki page for the use case]] and to decide what to report back from the use case to the plenary session the next day (again, see the WIKI template for a suggested structure). Thus, at the end of the day, the WIKI page for the use case is complete.

* Bulleted list item

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

WS1UC1

2020-05-23T17:24:46Z

2A04:2747:11DE:1E00:9017:64FD:8AA2:EDD9:

This page provides space for notes from workshop discussions of use case 1 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 [[UC1#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Draft list of databases ===
* Bulleted list item

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

== Notes from the afternoon session ==
The afternoon session is dedicated to discussing metadata for the selected databases. The aim of the afternoon session is to fill out [[UC1#Metadata_assessments|table 2 of the template]] and to decide what to report back from the use case to the plenary session the next day (again, see the WIKI template for a suggested structure). Thus, at the end of the day, the WIKI page for the use case is complete.

* Bulleted list item

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

WS1UC1

2020-05-23T17:22:09Z

2A04:2747:11DE:1E00:9017:64FD:8AA2:EDD9: Created page with "This page provides space for notes from workshop discussions of use case 1 during Day 2 of WS1. == Notes from the morning session == The morning session is dedicated to dat..."

This page provides space for notes from workshop discussions of use case 1 during Day 2 of WS1.

== 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 [[UC1#List_of_selected_databases|first table of the WIKI page]] is filled out by noon.

=== Draft list of databases ===
* Bulleted list item

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

== Notes from the afternoon session ==
The afternoon session is dedicated to discussing metadata for the selected databases. The aim of the afternoon session is to fill out [[UC1#Metadata_assessments|table 2 of the template]] and to decide what to report back from the use case to the plenary session the next day (again, see the WIKI template for a suggested structure). Thus, at the end of the day, the WIKI page for the use case is complete.

* Bulleted list item

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