Data Science Journal (Apr 2024)

Advancing FAIR Agricultural Data: The AgReFed FAIR Assessment Tool

  • Christiane Bahlo

DOI
https://doi.org/10.5334/dsj-2024-018
Journal volume & issue
Vol. 23
pp. 18 – 18

Abstract

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The FAIR principles provide guidance for improving the findability, accessibility, interoperability and reuse of research data and other digital objects. The Agricultural Research Federation (AgReFed) has developed a FAIR implementation consisting of policies, resources and tools to enable FAIR agricultural data in Australia. It prescribes minimum acceptable data standards and an associated set of FAIR metrics for agricultural research data. Existing FAIR assessment tools were examined and found to have limitations in serving the purposes of AgReFed. The AgReFed FAIR assessment tool addresses these needs with novel features to help improve FAIRness of datasets and other digital resources. By providing the ability to assess and subsequently re-assess datasets while also enabling users to add comments, it facilitates building work lists that support and document the improvement in FAIRness. Other innovative features include customisable FAIR metrics, storage of assessment results, a versioning system and inbuilt help resources. In addition to user-friendly reporting of AgReFed standards compliance, the integrated automated F-UJI FAIR assessment API provides a supplementary set of machine-readable FAIR scores. The AgReFed FAIR Assessment Tool has been deployed for public use and released as open source to help data custodians enact FAIR principles in domains and data communities within and beyond Australian agriculture.

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