New project: 3DFAIR - developing FAIR data research methods for building energy studies

This post introduces the 3DFAIR project, a new EPSRC-funded project studying at FAIR data research methods.

New project: 3DFAIR -  developing FAIR data research methods for building energy studies
Photo by Alina Grubnyak / Unsplash

The 3DFAIR project

3DFAIR is a new research project which I am leading and is funded by the Engineering and Physical Sciences Research Council (EPSRC).

The full title of the project is:

Data for Digital Decarbonisation: A FAIR approach to energy demand data in buildings

The funding details and summary can be viewed here:

The project is a 12 month feasibility study which runs from December 2021 to November 2022.

What is the project about?

The project is studying the FAIR data principles. FAIR stands for Findable, Accessible, Interoperable and Reusable. The FAIR data principles are a set of guidelines for working with data and other digitial assets to improve their openness, transparency and reusability. This allows other users, who were not involved in the original creation of the dataset, to easily understand and reuse the data for their own purposes.

The FAIR principles have gained significant attention since their first publication in 2016. They have been largely accepted by the Open Research movement and now feature in the Open Data policy statements of many insititutions. However, the FAIR principles are just that, a set of high-level principles which datasets and other digital assets should aspire to. They do not contain the details of how exactly a dataset should be organised, formatted and stored to meet the FAIR criteria. Rather this is left to individual domains as the solutions will differ in different disciplines.

How to create FAIR datasets is an ongoing debate and many research communities are still working towards their own solutions. This project considers FAIR data in the context of building energy studies, which often measure or predict energy and performance information about buildings such as their internal air temperatures or fuel consumption for heating. There are many datasets already available in the building energy field and by applying the FAIR principles these could become more understandable and reuseable for other researchers. This will enable easier and more robust analysis of these datasets, both individually and in combination, which leads to greater insights when developing solutions to improve energy efficiency and reduce carbon emissions in the building stock.

What will the project do?

The research hypothesis for the project is:

The use of FAIR data will enable energy demand researchers and practitioners to gain significantly more value from new and existing datasets for developing policy, design and technological solutions to reducing carbon emissions.

The project has the following objectives:

  1. Review the FAIR data principles, the latest developments in FAIR implementation, and the application of FAIR to building energy studies.
  2. Develop new research methods for structuring building energy demand datasets to meet the FAIR criteria. This may include outputs such as new guidelines, software, data structures and ontologies.
  3. Convert a number of existing building energy datasets to FAIR-compliant data structures. This will be a proof-of-concept exercise and will provide validation for the new research methods proposed.
  4. Publish all outputs and findings from the work in real time as the project progresses.

Where can I find the results?

I plan to publish the project outputs as they are completed during the project's 12 month period.

Intermediate outputs and progress updates will be published on this website as a series of blog post updates and shared and promoted on Twitter and LinkedIn.

The new FAIR research methods will be hosted on the project's GitHub repository:

Final versions of outputs such as new software and ontologies will be placed on Loughborough University's Research Repository as a permenant record of the output with an associated DOI.

The overall findings of the research will also be published as Open Access journal papers.

How do I find out more?

For more details please do contact me.