An automated solution for measuring the progress toward FAIR research data

Anusuriya Devaraju; Robert Huber

doi:10.1016/j.patter.2021.100370

An automated solution for measuring the progress toward FAIR research data

Patterns (N Y). 2021 Oct 29;2(11):100370. doi: 10.1016/j.patter.2021.100370. eCollection 2021 Nov 12.

Authors

Anusuriya Devaraju¹, Robert Huber²

Affiliations

¹ Terrestrial Ecosystem Research Network (TERN), The University of Queensland, Long Pocket Precinct, Level 5 Foxtail Building #1019, 80 Meiers Road, Indooroopilly, QLD 4068 Australia.
² Center for Marine Environmental Sciences (MARUM), University of Bremen, Leobener Strasse 8, 28359 Bremen, Germany.

Abstract

With a rising number of scientific datasets published and the need to test their Findable, Accessible, Interoperable, and Reusable (FAIR) compliance repeatedly, data stakeholders have recognized the importance of an automated FAIR assessment. This paper presents a programmatic solution for assessing the FAIRness of research data. We describe the translation of the FAIR data principles into measurable metrics and the application of the metrics in evaluating FAIR compliance of research data through an open-source tool we developed. For each metric, we conceptualized and implemented practical tests drawn upon prevailing data curation and sharing practices, and the paper discusses their rationales. We demonstrate the work by evaluating multidisciplinary datasets from trustworthy repositories, followed by recommendations and improvements. We believe our experience in developing and applying the metrics in practice and the lessons we learned from it will provide helpful information to others developing similar approaches to assess different types of digital objects and services.

Keywords: FAIR data principles; automated assessment; data discovery; data reuse; metrics; research objects; trustworthy digital repository.