Supporting FAIR: experiences in improving the scores on the doors

FAIR Assessment Tools Review FAIR Assessment Tools generate machine-oriented tests based on FAIR Metrics. These tests result in a quantifiable “FAIRness” score for a piece of data. This score can not only improve trust in the use of data we hold by showing how Reusable and Interoperable it is but also shows the EDC’s due-diligence in supporting FAIR data. Using these tools on samples of data within the EDC showed that the FAIRsFAIR tool F-UJI was the most relevant due to its domain-agnostic nature and easily retrievable results. Discussions on how a data’s FAIRness score could be displayed to the user have involved showing averages across each letter of FAIR, as well as visualisations of these scores. Supporting FAIR: Experiences in Improving the Scores on the Doors Catherine Jones, Peter Holt, and Oliver Brough (Technology Department) Karen VanHaltren and Teagan Zoldoske (Scientific Computing Department) UKRI/STFC Access to energy information now and for the future UKERC is funded by Grant UKRI-98 and DINI is funded by DSIT The UK Energy Research Centre (www.ukerc.ac.uk) undertakes “Independent whole systems research for a sustainable energy future” and was formed in 2004. The Energy Data Centre (EDC) is a capability of UKERC and provides a discovery portal and data management expertise for researchers funded through UKERC. Continuing service development and maintenance Enabling FAIR data Focusing on Environmental sustainability Preserving energy knowledge through building a grey literature collection Contributing to UKRI Digital Research Infrastructure EDC Policies Review We have reviewed our existing policies over the years to continuously improve the EDC’s functionality as a FAIR facing repository. This has come under 2 approaches, both resulting in action plans: Rapid Assessment Model (RAM) Approach: Identify current status and aspirations across a set of topics needed for a service to effectively preserve content FAIR Approach: Starting from the principles, assess whether the EDC meets them and what is needed to improve By using RAM in 2020/21 to convert implicit policy to explicit policy, and revising our existing policy in 2024 to include clearer links to FAIR, we have been able to explore the similarities and differences between FAIR and Forever policies and highlighted the key areas for the EDC to focus on to meet these goals. FAIR-Enabled API The Digital Infrastructure for National Infrastructure (DINI) Project gave us an opportunity to specify an API to enable machine access which has FAIR considerations at the heart of the design. To demonstrate this API is FAIR, we will: •Use the Open API standard •Include clear Terms of Service and licenses •Have good documentation for the API To demonstrate the repository is Trustworthy, we will: •Be certified – On the EDC Service development roadmap •Enable metadata about the repository itself to be interrogated so that the service using the API based on RDA recommendations FAIR Data: Data that is Findable, Accessible, Interoperable and Reuseable Energy Ontology Landscape Review The FAIR principles recommend that for interoperability FAIR vocabularies should be used, with an emphasis on domain standards. This work reviewed the landscape of energy semantic artefacts. The Open Energy Ontology (OEO) was identified as the largest energy focused ontology The EDC uses energy categories to add subjects which based on the IEA scheme from 2004. Use of energy categories means that the EDC has consistently classified records but issues with terminology changes and no ability to traverse relationships. These will need to be addressed to further refine FAIR practice. Current key priorities for the EDC are: Find out more about RAM at: https://www.dpconline.org/digipres/implement-digipres/dpc-ram Visit our Website