UC1 - Revision history

Ezildac: /* List of selected databases */

2020-06-04T08:39:54Z

List of selected databases

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	\| [8] [https://entranze.enerdata.net/ ENTRANZE database and web tool] \|\| The data mapper displays indicators and analysis on EU residential and non-residential building stock. It is a support to policy makers 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		\| [8] [https://entranze.enerdata.net/ ENTRANZE database and web tool] \|\| The data mapper displays indicators and analysis on EU residential and non-residential building stock. It is a support to policy makers 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
	\|\| EU-27 + Croatia; quite accessible; various EU ~~project~~ used ~~for~~ Data sources\|\| F1: yes; F2: Yes; F3:Yes; A1: Yes; I1: Yes; R1.2: Yes\|\| F4 and A2 in addition		\|\| EU-27 + Croatia; quite accessible; various EU projects are used as Data sources\|\| F1: yes; F2: Yes; F3:Yes; A1: Yes; I1: Yes; R1.2: Yes\|\| F4 and A2 in addition
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	\| [9] [https://eeg.tuwien.ac.at/commonenergy_economic_assessment_tool/#page=input_group1&reload=false CommONEergy _Economic Assessment Tool] \|\| The tool allows users (managers and owners of the shopping centre) to enter (input) relevant information on these buildings, providing: quick information on energy consumption, estimate of energy saving and CO2 emission reduction potential, economic benefits of retrofitting. The database includes information on EU-28 and Norway. \|\| The database includes data on a significant category of buildings, that is, commercial buildings \|\| F1: Yes, F2: No, F3: No, F4: No A1: Yes, A1.1: No, A1.2: No, A2: No I1: No, I2: Yes, I3: No R1: No, R1.1: No, R1.2: No, R1.3: No\|\| F2: No --> Yes I1: No --> Yes R1.3: No --> Yes		\| [9] [https://eeg.tuwien.ac.at/commonenergy_economic_assessment_tool/#page=input_group1&reload=false CommONEergy _Economic Assessment Tool] \|\| The tool allows users (managers and owners of the shopping centre) to enter (input) relevant information on these buildings, providing: quick information on energy consumption, estimate of energy saving and CO2 emission reduction potential, economic benefits of retrofitting. The database includes information on EU-28 and Norway. \|\| The database includes data on a significant category of buildings, that is, commercial buildings \|\| F1: Yes, F2: No, F3: No, F4: No A1: Yes, A1.1: No, A1.2: No, A2: No I1: No, I2: Yes, I3: No R1: No, R1.1: No, R1.2: No, R1.3: No\|\| F2: No --> Yes I1: No --> Yes R1.3: No --> Yes

Ezildac: /* List of selected databases */

2020-06-04T08:38:29Z

List of selected databases

← Older revision		Revision as of 08:38, 4 June 2020
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	\| [7] [https://dashboard.exceedproject.eu/ ExCEED - European Energy Efficient building district Database] \|\| The ExcEED platform is designed to integrate measurements from meters, Building Management Systems, head end systems, databases and other data providers. The platform transforms user’s monitored data into knowledge using energy performance indicators and air quality surveys.		\| [7] [https://dashboard.exceedproject.eu/ ExCEED - European Energy Efficient building district Database] \|\| The ExcEED platform is designed to integrate measurements from meters, Building Management Systems, head end systems, databases and other data providers. The platform transforms user’s monitored data into knowledge using energy performance indicators and air quality surveys.
	It provides a front-end dashboard with integrated tools: geo-clustered, statistical and knowledge analysis of building data; benchmarking function to analyse building interaction (energy, IEQ).		It provides a front-end dashboard with integrated tools: geo-clustered, statistical and knowledge analysis of building data; benchmarking function to analyse building interaction (energy, IEQ).
	Information coming from building monitoring systems can be divided in two levels: Private data, thus data uploaded by the user and visible only by himself; Public, aggregated, geo-cluster tool (which displays data on the aggregate level) still enables data comparison with other buildings in the platform.		Information coming from building monitoring systems can be divided into two levels: Private data, thus data uploaded by the user and visible only by himself; Public, aggregated, geo-cluster tool (which displays data on the aggregate level) still enables data comparison with other buildings in the platform.
	The database is a combination of metadata and measured data, with complex KPI algorithms. The measured data can be imported from a number of data sources including utility meters (usually provided by data collectors/aggregators), grid data (e.g. electricity market data from market operators), monitoring data stored in csv files		The database is a combination of metadata and measured data, with complex KPI algorithms. The measured data can be imported from a number of data sources including utility meters (usually provided by data collectors/aggregators), grid data (e.g. electricity market data from market operators), monitoring data stored in csv files
	\|\| The ExcEED cloud-based platform supports a portfolio of data integration mechanisms and ensures that all data uploaded is seamlessly incorporated with industry-standard communication interfaces. Exceed allows ~~and~~ online analysis against continuously updated datasets from many EU MS (28). Interoperability with data from meters is assured. The platform is still alive (managed by EURAC) and FAIR principles can be improved.\|\| F1:Yes; F2:Yes; F3: Yes; A1.1:Yes; A1.2:Yes; I1:Yes; I3:Yes; R1.2: Yes\|\| Full FAIR level can be achieved, maybe		\|\| The ExcEED cloud-based platform supports a portfolio of data integration mechanisms and ensures that all data uploaded is seamlessly incorporated with industry-standard communication interfaces. Exceed allows an online analysis against continuously updated datasets from many EU MS (28). Interoperability with data from meters is assured. The platform is still alive (managed by EURAC) and FAIR principles can be improved.\|\| F1:Yes; F2:Yes; F3: Yes; A1.1:Yes; A1.2:Yes; I1:Yes; I3:Yes; R1.2: Yes\|\| Full FAIR level can be achieved, maybe
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	\| [8] [https://entranze.enerdata.net/ ENTRANZE database and web tool] \|\| The data mapper displays indicators and analysis on EU residential and non-residential building stock. It is a support to policy makers 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		\| [8] [https://entranze.enerdata.net/ ENTRANZE database and web tool] \|\| The data mapper displays indicators and analysis on EU residential and non-residential building stock. It is a support to policy makers 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: /* WS1 Minutes of the Work Group of Use Case 1 (3 June 2020) */

2020-06-04T03:39:22Z

WS1 Minutes of the Work Group of Use Case 1 (3 June 2020)

Show changes

Muhittind: /* Metadata assessments */

2020-06-03T16:07:54Z

Metadata assessments

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	\| [3] [https://heatroadmap.eu/peta4/ Pan-European Thermal Atlas (Peta) v4] \|\| Mostly descriptive, sources (not totally sufficient to trace back to the source) \|\| Metadata contains rich descriptive information and sources \|\| F1: Yes, F2: Yes, F3: Yes, F4: No A1: Yes, A1.1: Yes, A1.2: No, A2: No I1: Yes, I2: Yes, I3: No R1: Yes, R1.1: No, R1.2: Yes, R1.3: No \|\| Controlled vocabulary, taxonomy, and thesaurus \|\| html and plain text		\| [3] [https://heatroadmap.eu/peta4/ Pan-European Thermal Atlas (Peta) v4] \|\| Mostly descriptive, sources (not totally sufficient to trace back to the source) \|\| Metadata contains rich descriptive information and sources \|\| F1: Yes, F2: Yes, F3: Yes, F4: No A1: Yes, A1.1: Yes, A1.2: No, A2: No I1: Yes, I2: Yes, I3: No R1: Yes, R1.1: No, R1.2: Yes, R1.3: No \|\| Controlled vocabulary, taxonomy, and thesaurus \|\| html and plain text
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	\| [4] [https://dashboard.exceedproject.eu/ ExCEED - European Energy Efficient building district Database] \|\| Provenance (Sources), descriptive, type, units , definition \|\| Metadata contains rich descriptive information and sources \|\| F1: YES; F2: YES; F3: YES A1.1: YES; A1.2: YES; I1.: YES I3: YES R1.2: YES \|\| Controlled vocabulary, and …. \|\| html and plain text		\| [4] [https://dashboard.exceedproject.eu/ ExCEED - European Energy Efficient building district Database] \|\| Provenance (Sources), descriptive, type, units , definition \|\| Metadata contains rich descriptive information and sources \|\| F1: YES; F2: YES; F3: YES A1.1: YES; A1.2: YES; I1.: YES I3: YES R1.2: YES \|\| Controlled vocabulary, and thesaurus \|\| html and plain text
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	\| [5] [https://www.hotmaps-project.eu/ Hotmaps] \|\| 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 \|\| 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. \|\| 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 \|\| Controlled Vicabulary ~~(?)~~ \|\| Machine-readable JSON, [https://gitlab.com/hotmaps/potential/potential_biomass/-/blob/master/datapackage.json ]		\| [5] [https://www.hotmaps-project.eu/ Hotmaps] \|\| 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 \|\| 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. \|\| 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 \|\| Controlled Vicabulary \|\| Machine-readable JSON, [https://gitlab.com/hotmaps/potential/potential_biomass/-/blob/master/datapackage.json ]
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	\|}		\|}

Mehmetefeb: /* Lessons Learned */

2020-06-03T14:16:29Z

Lessons Learned

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	* Usability could arise as a problem. It is sometimes difficult to observe in detail.		* Usability could arise as a problem. It is sometimes difficult to observe in detail.
	* Lack of live data is generally missing.		* Lack of live data is generally missing.
			* Interface design is crucial for the end user.

Mehmetefeb: /* Lessons Learned */

2020-06-03T14:15:28Z

Lessons Learned

← Older revision		Revision as of 14:15, 3 June 2020
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	* Deficiencies in metadata make the research complicated and difficult.		* Deficiencies in metadata make the research complicated and difficult.
	* There is generally either a lack of information in metadata or in data itself.		* There is generally either a lack of information in metadata or in data itself.
			* Usability could arise as a problem. It is sometimes difficult to observe in detail.
			* Lack of live data is generally missing.

Mehmetefeb: /* Lessons Learned */

2020-06-03T14:09:09Z

Lessons Learned

← Older revision		Revision as of 14:09, 3 June 2020
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	== Lessons Learned ==		== Lessons Learned ==

	* One of the major barriers is about uploading the data to an online platform. As consumers are 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 are not volunteer to share their data, the databases remain restricted.
	* When the data is collected from different and high number of sources, its reliability decreases.		* When the data is collected from different and high number of sources, its reliability decreases.
	* 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.

Mehmetefeb: /* WS1 Minutes of the Work Group of Use Case 1 (3 June 2020) */

2020-06-03T14:03:38Z

WS1 Minutes of the Work Group of Use Case 1 (3 June 2020)

← Older revision		Revision as of 14:03, 3 June 2020
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	== WS1 Minutes of the Work Group of Use Case 1 (3 June 2020) ==		== WS1 Minutes of the Work Group of Use Case 1 (3 June 2020) ==

	*Mehmet Efe Biresselioğlu – USE CASE 1		The main aim of USE CASE 1 Workshop is to have a discussion about the selected databases and possible candidate databases. Use case leader designed templates to allow all partners involved to conduct preliminary analyses of the selected databases. In addition, we aimed to select 3-5 databases from the list. Metadata status of the selected databases and lessons learned were also discussed in this session. There are pre-selected databases that are relevant databases that can be used in UC1. Initial assessment has been completed to have a general idea in the buildings efficiency domain.
	The aim of USE CASE 1 is to have a discussion about the selected databases and possible candidate databases. ~~Designed~~ templates allow a preliminary ~~analysis~~ of the selected databases. ~~Our aim is~~ to select 3-5 ~~of them~~. Metadata status of the selected databases and lessons learned ~~will~~ also be discussed in this session. There are pre-selected databases that are relevant databases that can be used in UC1. Initial assessment has been completed to have a general idea in the buildings efficiency domain~~. – How FAIR/O are data of buildings efficiency? Note that perceptions regarding FAIRificaiton and metadata differ from person to person~~.

	There are severe limitations to the: <br>		There are severe limitations to the: <br>

Muhittind: /* Databases of Interest */

2020-06-03T14:02:08Z

Databases of Interest

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	=== Databases of Interest ===		=== Databases of Interest ===

	* ~~Beep Database (~~https://www.buildup.eu/en/explore/links/iea-building-energy-efficiency-policies-beep-database) (Policy)		* [https://www.buildup.eu/en/explore/links/iea-building-energy-efficiency-policies-beep-database Beep Database (Policy)]
	* ~~BuildingRating (~~https://entranze.enerdata.net/)		* [https://entranze.enerdata.net/ BuildingRating]
	* ~~CommONEnergy Data Mapper (~~https://eeg.tuwien.ac.at/commonenergy/gla-per-capita-shopping-center)		* [https://eeg.tuwien.ac.at/commonenergy/gla-per-capita-shopping-center CommONEnergy Data Mapper]
	* ~~CommONEnergy Economic Assessment Tool (~~https://eeg.tuwien.ac.at/commonenergy_economic_assessment_tool/#page=input_group1&reload=false)		* [https://eeg.tuwien.ac.at/commonenergy_economic_assessment_tool/#page=input_group1&reload=false CommONEnergy Economic Assessment Tool]
	* ~~De-Risking Energy Effıciency Platform (Deep) (~~https://deep.eefig.eu/)		* [https://deep.eefig.eu/ De-Risking Energy Effıciency Platform (Deep)]
	* ~~Enerfund Tool (~~https://app.enerfund.eu/)		* [https://app.enerfund.eu/ Enerfund Tool]
	* ~~ENTRANZE (~~https://entranze.enerdata.net/)		* [https://entranze.enerdata.net/ ENTRANZE]
	* ~~Eurostat (~~https://ec.europa.eu/eurostat/web/main/home)		* [https://ec.europa.eu/eurostat/web/main/home Eurostat]
	* ~~Exceed platform (~~https://dashboard.exceedproject.eu/)		* [https://dashboard.exceedproject.eu/ Exceed platform]
	* ~~GBPN (~~https://www.gbpn.org/databases-tools/purpose-policy-comparative-tool)		* [https://www.gbpn.org/databases-tools/purpose-policy-comparative-tool GBPN]
	* ~~IEA Policies Database (~~https://www.iea.org/policies(Policy))		* [https://www.hotmaps-project.eu/ Hotmaps]
	* ~~MURE (Mesures d'Utilisation Rationnelle de l'Energie) (Database~~ http://www.measures-odyssee-mure.eu/) (Policy)		* [https://www.iea.org/policies IEA Policies Database (Policy)]
	* ~~Pan-European Thermal Atlas 4.3~~ https://heatroadmap.eu/peta4/		* [http://www.measures-odyssee-mure.eu/ MURE (Mesures d'Utilisation Rationnelle de l'Energie) Database (Policy)]
	* ~~Reegle - Clean Energy Information Portal~~ https://www.reeep.org/reegle-clean-energy-information-portal(No longer active)		* [https://heatroadmap.eu/peta4/ Pan-European Thermal Atlas 4.3]
	* ~~Tabula Web Tool (~~https://episcope.eu/building-typology/webtool/)		* [https://www.reeep.org/reegle-clean-energy-information-portal Reegle - Clean Energy Information Portal (No longer active)]
	* ~~The Building Performance Database(~~https://www.energy.gov/eere/buildings/building-performance-database-bpd)		* [https://episcope.eu/building-typology/webtool/ Tabula Web Tool]
	* ~~The Commercial Building Energy Consumption Survey (~~https://www.eia.gov/consumption/commercial/)		* [https://www.energy.gov/eere/buildings/building-performance-database-bpd The Building Performance Database]
	* ~~The FROnT project: for Fair Renewable Heating and Cooling Options and Trade (~~https://www.front-rhc.eu/tools/)		* [https://www.eia.gov/consumption/commercial/ The Commercial Building Energy Consumption Survey]
	* ~~ZEBRA 2020 Data Mapper (~~https://eeg.tuwien.ac.at/zebra/)		* [https://www.front-rhc.eu/tools/ The FROnT project: for Fair Renewable Heating and Cooling Options and Trade]
	* ~~ZEBRA 2020 Energy efficiency trends in buildings (~~https://zebra-monitoring.enerdata.net/overall-building-activities/share-of-new-dwellings-in-residential-stock.html)		* [https://eeg.tuwien.ac.at/zebra/ ZEBRA 2020 Data Mapper]
	* ZEBRA 2020 ~~nZEB~~ buildings (https://zebra-monitoring.enerdata.net/nzeb-activities/panel-distribution.html)		* [https://zebra-monitoring.enerdata.net/overall-building-activities/share-of-new-dwellings-in-residential-stock.html ZEBRA 2020 Energy efficiency trends in buildings]
	* ~~Klimaaktiv building database (~~https://www.klimaaktiv-gebaut.at/alleProjekte.htm)		* [https://zebra-monitoring.enerdata.net/nzeb-activities/panel-distribution.html ZEBRA 2020 nZEB buildings]
	* Hotmaps (https://www.hotmaps-project.eu/)		* [https://www.klimaaktiv-gebaut.at/alleProjekte.htm Klimaaktiv building database]

	== List of selected databases ==		== List of selected databases ==

Mehmetefeb: /* WS1 Minutes of the Work Group of Use Case 1 (3 June 2020) */

2020-06-03T13:58:42Z

WS1 Minutes of the Work Group of Use Case 1 (3 June 2020)

← Older revision		Revision as of 13:58, 3 June 2020
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	*Mehmet Efe Biresselioğlu – USE CASE 1		*Mehmet Efe Biresselioğlu – USE CASE 1
	The aim of USE CASE 1 is to have a discussion about the selected databases and possible candidate databases. Designed templates allow a preliminary analysis of the selected databases. Our aim is to select 3-5 of them. Metadata status of the selected databases and lessons learned will also be discussed in this session. There are pre-selected databases that are relevant databases that can be used in UC1. Initial assessment has been completed to have a general idea in the buildings efficiency domain. – How FAIR/O are data of buildings efficiency? Note that perceptions regarding FAIRificaiton and metadata differ from person to person.		The aim of USE CASE 1 is to have a discussion about the selected databases and possible candidate databases. Designed templates allow a preliminary analysis of the selected databases. Our aim is to select 3-5 of them. Metadata status of the selected databases and lessons learned will also be discussed in this session. There are pre-selected databases that are relevant databases that can be used in UC1. Initial assessment has been completed to have a general idea in the buildings efficiency domain. – How FAIR/O are data of buildings efficiency? Note that perceptions regarding FAIRificaiton and metadata differ from person to person.

	There are severe limitations to the: <br>		There are severe limitations to the: <br>

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	Openness—restrictions from commercial and security concerns <br>		Openness—restrictions from commercial and security concerns <br>

	Initial ~~assessment—FAIR guiding principles – Wilkinson criteria are used.~~		Initial assessment conducted via template below:
	~~Preliminary Analysis – Template~~
	* Descriptive analysis of the selected databases		* Descriptive analysis of the selected databases
	* Classification of Meta Data		* Classification of Meta Data