Analysis of Automated Tools for FAIRness Evaluation: A Literature Perspective

The FAIR Principles were introduced to address data challenges and improve the Findability, Accessibility, Interoperability, and Reusability of digital resources, following several Semantic Web standards. 'FAIRness' corresponds to a percentage grade indicating how close a digital object is to abiding by those principles. Several tools have been developed to assess the FAIRness of data digital objects in support of enacting the FAIR Principles. This work offers an appraisal of tools that evaluate the FAIRness of such objects, focusing on fully automated solutions. We conduct a literature review about existing tools, extract from it a set of requirements they aim to fulfill, and assess how each one fares considering this ensemble. Our results help researchers, developers, and data stewards with an overview of the tools, including an analysis of tools' fulfillment to the elicited requirements, making explicit existing gaps, and giving directions to improvements needed.