An Automated Assessment of the FAIRness of Research Data

This paper offers two essential contributions to the FAIR assessment of research data objects: a set of core quantifiable FAIR metrics and an open-source tool, F-UJI, that applies the metrics to measure the progress of FAIR aspects of data programmatically. Throughout this paper, the term “data object” refers to research data. “Core metrics” refers to the domain-agnostic assessment criteria that are centered on generally applicable metadata and data characteristics.

Outcomes from FAIRsFAIR Focus Group: Universidad Carlos III de Madrid

Twenty-five representatives from higher education institutes gathered at the Universidad Carlos III de Madrid in October to share insights on the challenges associated with implementing FAIR principles.