WS2UC1

Details for the use case workshop "Buildings efficiency".

The aim of this session is to build up on discussions that took place in 1st EERADATA workshop together with the participation of the invited experts, utilizing the experience related to the FAIR assessment in order to: a) Highlight main issues with FAIRness, b) Jointly come up with possible remedies and solutions, and c) Identify pointers to metadata standardization, if and how it can be achieved in Buildings Efficiency domain.

Detailed agenda

2nd Dec. 10:00-12:00 (GMT+1)	Use case “Buildings efficiency” Link to register:
10.00-10.10	Introduction: What does the “Buildings Efficiency” use case of EERADATA aim? Mehmet Efe Biresselioğlu, IUE
10.10-10.25	Standardized Flexibility: FAIR data principles in H2020 projects - ECHOES and ENCHANT - databases, Jens Olgard Dalseth Røyrvik, NTNU Samfunnsforskning
10.25-10.40	Achieving Fair Principles: An Overview of the Hotmaps Project and Hotmaps Building Stock EU28 Dataset, Simon Pezzutto, EURAC
10.40-10.55	openENTRANCE CS1 residential energy demand response: The importance of nomenclature and data transparency for open source energy system model platform, Ryan O’Reilly, Energieinstitut an der JKU
10.55-11.10	Exceed database: Lessons learned and continuous improvement, Daniele Antonucci, EURAC
11.10-11.15	Short Break
11.15-12.00	Panel Discussion with Q&A

Notes

Jens Olgard Dalseth Røyrvik from NTNU Samfunnsforskning provided highlights from two H2020 projects, ECHOES and ENCHANT. The title of his presentation was "Standardized Flexibility: FAIR data principles in H2020 projects - ECHOES and ENCHANT - databases". The recently completed ECHOES project's aim was to understand energy behaviour in Europe (EU 28 + Norway and Turkey). The project focused on technological foci, buildings, e-mobility, and smart energy systems. The buildings data captured and generated by the project includes type of house, type of heating, number of indoor living spaces, energy efficiency renovations, type of insulation. Mainly, 3 methods were used for data collection: survey, psychological experiments, focus groups. The ENCHANT project has kicked-off only recently (October 2020), and aims to achieve energy behaviour change through theoretically proven intervention types. ENCHANT plans to utilize 6 main methods for data collection: surveys, focus groups, interviews, netnography, workshop, discussion events. Regarding data-related challenges of both projects, managing qualitative and quantitative data together, accessibility issues due to context sensitivity, anonymity, protection of personal information, insufficient or inaccessible data or metadata, technical capacity limitations, and pragmatic barriers regarding compliance with rules and regulations are among the main difficulties. As for the strengths, the projects share aspects such as the availability of a big data reservoir which is representative both in terms of questions, respondents, and decision-making levels, handling different types of data successfully in accordance with open data and FAIR data principles, data protection principles, GDPR and national law, offering not only publicly available and open data, but also protected data, providing easy access to data and raw data – available online, implementing a very clear process of gathering qualitative and quantitative data and a clear procedure to collect metadata.

Simon Pezzutto from EURAC delivered a presentation titled "Achieving Fair Principles: An Overview of the Hotmaps Project and Hotmaps Building Stock EU28 Dataset". The Hotmaps project aims to develop, demonstrate and disseminate a toolbox to support public authorities, energy agencies, and planners in strategic heating and cooling planning at local, regional, and national levels, and in line with EU policies. The project processes data regarding building type, building age, area, ownership status, occupancy, construction features, construction materials, useful energy demand, final energy consumption, etc. The database of the project is user-driven, developed in collaboration with 7 pilot areas. Although challenges with handling a large dataset are encountered, the project database performed well in following the FAIR principles. The data and metadata was Findable over a web page. In terms of Accessibility, the data was open access and easy to access. Not only the publications in the project were open-source and accessible but also the dataset was freely accessible, with clearly provided metadata, and open access code. The Hotmaps platform was also Interoperable, the data being downloadable (with attached metadata, in .csv and .xlsx formats), and processable without restrictions. There was also the opportunity for users to upload their own data for the platform to run and map it. The data on the platform was Reusable through a Creative Commons Attribution 4.0 International License, where everybody is allowed to use this data on the condition of citation.

Ryan O’Reilly from Energieinstitut an der JKU focused on the ENTRANCE database in his speech titled "openENTRANCE CS1 residential energy demand response: The importance of nomenclature and data transparency for open source energy system model platform". The open-ENTRANCE project has the goal of developing a FAIR and integrated modelling platform to assess low carbon transition pathways in Europe. The project platform hosts 13 different open integrated modelling tools, including data on hourly energy demand profiles, heating cooling degree days, and energy demand response with a geographical coverage of EU27, UK, Turkey, Norway, and China. The strong suits of the platform are being open to the public, hence Accessible for individuals as well as researchers, the possibility for users to upload and analyze their own data using platform tools, and the use of a standardized data format that fosters interoperability. The platform is coded using Python, which is open source and extremely flexible. However, the dependence on Phyton (as opposed to more commonly used tools) may also become an issue for interoperability. Since the users have the chance to upload their own data, the quality of data and metadata on the platform is also an issue to be continuously monitored.

Daniele Antonucci from EURAC presented the case of the recently terminated Exceed database. His presentation was titled "Exceed database: Lessons learned and continuous improvement". The Exceed platform involved the construction of a geo-clustering and benchmarking tool, as part of the projects overall aim of creating a European self-sustainable and dynamic platform, that will collect, post-process and publish measured and qualitative data. The platform is intended to provide knowledge different user groups. Although the platform is not maintained anymore, it had the strengths of being a fully operative platform for building performance characterization and building stock analysis, including data and metadata from a wide spectrum of different types of buildings, and being Interoperable through the normalization of the data. the challenges associated with the platform finally led to the termination of the platform. Main issues were, being unable to achieve sufficient flow of data to the platform, market players not being motivated to use platform, high costs, especially the costs of using an external commercial platform, time restrictions of the project, and late launch of the platform.

Workshop results

As a result of expert opinions from the Buildings Efficiency Use Case Session, the following can be listed as general achievements:

• Open access data
• Data Protection and Compatibility with GDPR
• Transparency
• Representative Data

When we consider what is generally not achieved, we have:

• Merging qualitative and quantitative data
• Building sufficient technical capacity to share qualitative data
• Handling high costs
• Sustainability
• Efficiently overcoming pragmatic Barriers

A number of recommendations can also be listed:

• Utilization of larger platform for hosting data instead of smaller individual projects platforms
• Standardization
• Building common repositories for similar databases
• Using repositories for metadata augmentation