WS1UC1 - Revision history

Mehmetefeb: /* Main insights from discussions */

2020-06-04T07:50:30Z

Main insights from discussions

← Older revision		Revision as of 07:50, 4 June 2020
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	* One of the major barriers is about uploading the data to an online platform. As consumers and energy managers do not volunteer to share their data, the databases remain restricted.		* One of the major barriers is about uploading the data to an online platform. As consumers and energy managers do not volunteer to share their data, the databases remain restricted.
	When the data is collected from different and high number of sources, consistency, and reliability issues are more likely.		* When the data is collected from different and high number of sources, consistency, and reliability issues are more likely.
	* Issues related to DC are not considered while creating the database. This is also a setback.		* Issues related to DC are not considered while creating the database. This is also a setback.
	* Privacy issues constitute a matter for the reusability of the data.		* Privacy issues constitute a matter for the reusability of the data.

Manfred: /* Notes from the morning session */

2020-06-04T07:49:32Z

Notes from the morning session

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	== Notes from the morning session ==		== 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. The workshop, in which 9 participants actively worked, has started with the introduction of participants and a guiding presentation by UC1 leader.		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. The workshop, in which 9 participants actively worked, has started with the introduction of participants and a guiding presentation by UC1 leader.

			'''Partipants list:'''
			...

	'''UC1 workshop aims:'''		'''UC1 workshop aims:'''
	* Discuss the related literature, gaps, best practices, FAIR/O- fairification, Metadata-DC and non-DC		* Discuss the related literature, gaps, best practices, FAIR/O- fairification, Metadata-DC and non-DC

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

2020-06-04T03:33:38Z

What to report back to the plenary on Day 3?

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 == What to report back to the plenary on Day 3? ==
-* Databases selected
+=== Databases selected ===
-.	EU Building Stock Observatory - extensive database, includes datasets from many sources, can be analyzed as a model for the platform to be developed by EERAdata
+# EU Building Stock Observatory - extensive database, includes datasets from many sources, can be analyzed as a model for the platform to be developed by EERAdata
-.	Global Buildings Performance Network (GBPN) - involves qualitative and quantitative data, good example, may be improved towards FAIRification
+=== Main insights from discussions ===
-.	Pan-European Thermal Atlas (Peta) v4 - rich metadata, technical info
+* One of the major barriers is about uploading the data to an online platform. As consumers and energy managers do not volunteer to share their data, the databases remain restricted.
-.	ExCEED - European Energy Efficient building district Database - 'living' database, updated with real data, possibility to collaborate with the creators of the database
+Suggested next steps:
+* Evaluate the data profiles of the selected databases in order to seek for recipes.
-.	Hotmaps - comprehensive database regarding buildings, %100 coverage for Europe, possibility to collaborate with the creators of the database
+* Define recipes to provide a database-specific implementation of the FAIRification.
+* Assess the metadata quality of the selected databases (TOOL STANDARD COMMUNITY).
-* Main insights from discussions
+* Accept the fact that “%100 FAIR is not really possible!”
-Based on the discussions in morning and afternoon sessions of UC1, the participants derived lessons learned from the selected databases.
+* Evaluate before and after for each selected databases
 For the next workshops, WS2 and WS3:
+* Interface design for the platform
-* interface design for the platform
+* Make more extensive use of online assessment tools
-* make more extensive use of online assessment tools
+* Establish the link between machine actionability and FAIRness of databases
-* establish the link between machine actionability and FAIRness of databases
+* Collaborate with other projects, communities, and researchers

Valerias: /* Notes from the afternoon session */

2020-06-04T03:28:18Z

Notes from the afternoon session

Valerias: /* ENTRANZE database and web tool = */

2020-06-04T03:25:47Z

ENTRANZE database and web tool =

← Older revision		Revision as of 03:25, 4 June 2020
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	Expert views are key to determine, assess, and analyze data and metadata. For this reason, participants from EURAC, which is a private research center, contributed a lot in the light of their views and experience in ExCEED database. They provide information about the aims and scope of ExCEED database. The objective of EXCEED is to transform data and metadata into information and knowledge for final users. To achieve this target, a big amount of data is required, and the data providers are needed to be convinced to provide data. Therefore, ExCEED is a good example of database selection in terms of choice of indicators and metadata.		Expert views are key to determine, assess, and analyze data and metadata. For this reason, participants from EURAC, which is a private research center, contributed a lot in the light of their views and experience in ExCEED database. They provide information about the aims and scope of ExCEED database. The objective of EXCEED is to transform data and metadata into information and knowledge for final users. To achieve this target, a big amount of data is required, and the data providers are needed to be convinced to provide data. Therefore, ExCEED is a good example of database selection in terms of choice of indicators and metadata.

	== ENTRANZE database and web tool ===		=== ENTRANZE database and web tool ===

	* '''Description of the database:''' The data mapper displays indicators and analysis on EU residential and non-residential building stock. It is a support to policymakers to achieve a fast and strong penetration of nZEB and RES-H/C within the existing national building stocks. It provides trends (dynamics) about technologies for better performance in the sector.		* '''Description of the database:''' The data mapper displays indicators and analysis on EU residential and non-residential building stock. It is a support to policymakers to achieve a fast and strong penetration of nZEB and RES-H/C within the existing national building stocks. It provides trends (dynamics) about technologies for better performance in the sector.

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

2020-06-04T03:25:18Z

Discussion on the choice of databases:

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	Based on the preliminary work performed by partners, each partner provided the following brief information about the databases analyzed:		Based on the preliminary work performed by partners, each partner provided the following brief information about the databases analyzed:

	==== Global Buildings Performance Network (GBPN) ====		=== Global Buildings Performance Network (GBPN) ===

	*'''Description of the database:''' The database (The Policy Comparative Tool) includes information on 25 building energy efficiency codes (BEECs) that are identified as the world's best practice policies for new residential and commercial buildings. The database involves scoring and comparison of the 25 building energy efficiency codes based on 14 criteria and their sub-criteria. Scoring and ranking are done for every criterion. The database also includes detailed information regarding each building energy efficiency code. The Global Buildings Performance Network (GBPN), founded in 2010 aims to contribute to knowledge and expertise regarding building energy performance and to enhance the building sector towards energy transition and climate change related goals. GBPN partners with a wide range of institutions including IEA, UNFCCC, UNEP-SBCI, The World Bank, SE4ALL Buildings Efficiency Accelerator, BPIE, and NREL.		*'''Description of the database:''' The database (The Policy Comparative Tool) includes information on 25 building energy efficiency codes (BEECs) that are identified as the world's best practice policies for new residential and commercial buildings. The database involves scoring and comparison of the 25 building energy efficiency codes based on 14 criteria and their sub-criteria. Scoring and ranking are done for every criterion. The database also includes detailed information regarding each building energy efficiency code. The Global Buildings Performance Network (GBPN), founded in 2010 aims to contribute to knowledge and expertise regarding building energy performance and to enhance the building sector towards energy transition and climate change related goals. GBPN partners with a wide range of institutions including IEA, UNFCCC, UNEP-SBCI, The World Bank, SE4ALL Buildings Efficiency Accelerator, BPIE, and NREL.

Valerias: /* Notes from the morning session */

2020-06-04T03:24:46Z

Notes from the morning session

← Older revision		Revision as of 03:24, 4 June 2020
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	* Openness—restrictions from commercial and security concerns		* Openness—restrictions from commercial and security concerns

	'''14 databases were preliminarily assessed and analyzed according to the following criteria:'''		'''Fourteen databases were preliminarily assessed and analyzed according to the following criteria:'''
	* Descriptive analysis of the selected databases		* Descriptive analysis of the selected databases
	* Classification of Metadata		* Classification of Metadata
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	** There are some tools to analyze these data and make the data anonymous. The anonymized data are available to everyone for analysis and benchmarking. But the problem is data is limited because people do not upload their data.		** There are some tools to analyze these data and make the data anonymous. The anonymized data are available to everyone for analysis and benchmarking. But the problem is data is limited because people do not upload their data.

	Expert views are key to determine, assess, and analyze data and metadata. For this reason, participants from EURAC, which is a private research center, contributed a lot in the light of their views and experience in ExCEED database. They provide information about the aims and scope of ExCEED database. The objective of EXCEED is to transform data and metadata into information and knowledge for final users. To achieve this target, a big amount of data is required, and the data providers are needed to be convinced to provide data. Therefore, ExCEED is a good example of database selection in terms of choice of indicators and metadata.		Expert views are key to determine, assess, and analyze data and metadata. For this reason, participants from EURAC, which is a private research center, contributed a lot in the light of their views and experience in ExCEED database. They provide information about the aims and scope of ExCEED database. The objective of EXCEED is to transform data and metadata into information and knowledge for final users. To achieve this target, a big amount of data is required, and the data providers are needed to be convinced to provide data. Therefore, ExCEED is a good example of database selection in terms of choice of indicators and metadata.

	== ENTRANZE database and web tool ===		== ENTRANZE database and web tool ===

Valerias: /* Notes from the morning session */

2020-06-04T03:24:21Z

Notes from the morning session

Show changes

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

2020-06-03T19:40:09Z

What to report back to the plenary on Day 3?

← Older revision		Revision as of 19:40, 3 June 2020
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	Evaluate before and after for each selected databases		Evaluate before and after for each selected databases

			For the next workshops, WS2 and WS3:

			* interface design for the platform
			* make more extensive use of online assessment tools
			* establish the link between machine actionability and FAIRness of databases
			* collaborate with other projects, communities and researchers

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

2020-06-03T19:33:06Z

What to report back to the plenary on Day 3?

← Older revision		Revision as of 19:33, 3 June 2020
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	* Databases selected		* Databases selected

	1. EU Building Stock Observatory		1. EU Building Stock Observatory - extensive database, includes datasets from many sources, can be analyzed as a model for the platform to be developed by EERAdata

	2. Global Buildings Performance Network (GBPN)		2. Global Buildings Performance Network (GBPN) - involves qualitative and quantitative data, good example, may be improved towards FAIRification

	3. Pan-European Thermal Atlas (Peta) v4		3. Pan-European Thermal Atlas (Peta) v4 - rich metadata, technical info

	4. ExCEED - European Energy Efficient building district Database		4. ExCEED - European Energy Efficient building district Database - 'living' database, updated with real data, possibility to collaborate with the creators of the database

	5. Hotmaps		5. Hotmaps - comprehensive database regarding buildings, %100 coverage for Europe, possibility to collaborate with the creators of the database

	* Main insights from discussions		* Main insights from discussions

← Older revision		Revision as of 03:28, 4 June 2020
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	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. Thus, at the end of the day, the WIKI page for the use case is complete.		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. Thus, at the end of the day, the WIKI page for the use case is complete.

	The afternoon session is dedicated to discuss metadata for the selected databases. The aim of the afternoon session is to fill out 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. Thus, at the end of the day, the WIKI page for the use case is complete.		=== Assessment of metadata for databases ===

	* Assessment of metadata for databases

	In total, 5 databases were decided for metadata assessment.		In total, 5 databases were decided for metadata assessment.

	~~[1.]~~ EU Building Stock Observatory		# EU Building Stock Observatory
	~~[2.]~~ Global Buildings Performance Network (GBPN)		# Global Buildings Performance Network (GBPN)
	~~[3.]~~ Pan-European Thermal Atlas (Peta) v4		# Pan-European Thermal Atlas (Peta) v4
	~~[4.]~~ ExCEED - European Energy Efficient building district Database		# ExCEED - European Energy Efficient building district Database
	~~[5.]~~ Hotmaps		# Hotmaps


	~~[1.]~~ EU Building Stock Observatory		=== EU Building Stock Observatory ===
	* Type of metadata provided: Provenance (sources), descriptive (axis and time series descriptions), partially provenance (only sources).		* Type of metadata provided: Provenance (sources), descriptive (axis and time series descriptions), partially provenance (only sources).
	* Extend of metadata provided: Descriptions, definitions, factsheet. However loosely attached to the data itself.		* Extend of metadata provided: Descriptions, definitions, factsheet. However loosely attached to the data itself.
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	* Technical implementation of metadata: Plain text and html		* Technical implementation of metadata: Plain text and html

	~~[2.]~~ Global Buildings Performance Network (GBPN)		=== Global Buildings Performance Network (GBPN) ===
	* Type of metadata provided: Mostly descriptive, partially provenance (only sources) and administrative (copyright and ownership).		* Type of metadata provided: Mostly descriptive, partially provenance (only sources) and administrative (copyright and ownership).
	* Extend of metadata provided: For the graphs regarding comparison of variables for countries/BEECs or multiple variables, sources of data are always listed under the graph. There is also data regarding the descriptions of the BEECs, however, these are more of a plain-text descriptive format and contain almost no metadata. Other than these, there are no other metadata attached.		* Extend of metadata provided: For the graphs regarding the comparison of variables for countries/BEECs or multiple variables, sources of data are always listed under the graph. There is also data regarding the descriptions of the BEECs, however, these are more of a plain-text descriptive format and contain almost no metadata. Other than these, there are no other metadata attached.
	* Level of implementation of FAIR/O principles: F1: Yes, F2: Yes, F3: No, F4: No A1: No, A1.1: Yes, A1.2: Yes, A2: No I1: Yes, I2: Yes, I3: No R1: Yes, R1.1: No, R1.2: No, R1.3: No		* Level of implementation of FAIR/O principles: F1: Yes, F2: Yes, F3: No, F4: No A1: No, A1.1: Yes, A1.2: Yes, A2: No I1: Yes, I2: Yes, I3: No R1: Yes, R1.1: No, R1.2: No, R1.3: No
	* Frameworks for metadata used: Mainly controlled vocabulary		* Frameworks for metadata used: Mainly controlled vocabulary
	* Technical implementation of metadata: Plain text and html		* Technical implementation of metadata: Plain text and html

	~~[3.]~~ Pan-European Thermal Atlas (Peta) v4		=== Pan-European Thermal Atlas (Peta) v4 ===
	* Type of metadata provided: Mostly descriptive, sources (not totally sufficient to trace back to the source)		* Type of metadata provided: Mostly descriptive, sources (not totally sufficient to trace back to the source)
	* Extend of metadata provided: Metadata contains rich descriptive information and sources		* Extend of metadata provided: Metadata contains rich descriptive information and sources
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	* Technical implementation of metadata: html and plain text		* Technical implementation of metadata: html and plain text

	~~[4.]~~ ExCEED - European Energy Efficient building district Database		=== ExCEED - European Energy Efficient building district Database ===
	* Type of metadata provided: Provenance (Sources), descriptive, type, units , definition		* Type of metadata provided: Provenance (Sources), descriptive, type, units, definition
	* Extend of metadata provided: Metadata contains rich descriptive information and sources		* Extend of metadata provided: Metadata contains rich descriptive information and sources
	* Level of implementation of FAIR/O principles: F1: YES; F2: YES; F3: YES A1.1: YES; A1.2: YES; I1.: YES I3: YES R1.2: YES		* Level of implementation of FAIR/O principles: F1: YES; F2: YES; F3: YES A1.1: YES; A1.2: YES; I1.: YES I3: YES R1.2: YES
	* Frameworks for metadata used: Controlled vocabulary, and thesaurus		* Frameworks for metadata used: Controlled vocabulary and thesaurus
	* Technical implementation of metadata: html and plain text		* Technical implementation of metadata: html and plain text

	~~[5.]~~ Hotmaps		=== Hotmaps ===
			* Type of metadata provided: Descriptive (name, title, description, version, date, profile, keywords, license), sources (address and contributors), resources (description of data in more detail, temporal, schema, datatype), unique id
	* Type of metadata provided: Descriptive (name, title, description, version, date, profile, keywords, license), sources (~~adress~~ and contributors), resources (description of data in more detail, temporal, schema, datatype), unique id		* Extend of metadata provided: Detailed description of the dataset, how it was created, and sources. The level of detail is different for each dataset, a basic description exists for each one.
	* Extend of metadata provided: ~~Detailled~~ description of dataset, how it was created and sources. The level of detail is different for each dataset, basic description exists for each one.
	* Level of implementation of FAIR/O principles: F1: Yes, F2: Yes, F3: Yes, F4: No, A1: Yes, A1.1: Yes, A1.2: No, A2: Yes, I1: Yes, I2: Yes, I3: No, R1: Yes, R1.1: Yes, R1.2: Yes, R1.3: No		* Level of implementation of FAIR/O principles: F1: Yes, F2: Yes, F3: Yes, F4: No, A1: Yes, A1.1: Yes, A1.2: No, A2: Yes, I1: Yes, I2: Yes, I3: No, R1: Yes, R1.1: Yes, R1.2: Yes, R1.3: No
	* Frameworks for metadata used: Controlled Vocabulary		* Frameworks for metadata used: Controlled Vocabulary