Good practice
FAIR-Checker is an online tool supporting scientists in automating FAIR assessments. It assists data stewards in evaluating metadata quality and prioritising relevant metadata. Presented at various scientific events and published in the Journal of Biomedical Semantics, FAIR-Checker is widely used, with an average of 115 000 FAIR metrics evaluations conducted monthly in 2024.
Problem addressed
Ensuring that research activities follow FAIR principles is crucial for open and reproducible science. These principles are generally specified through technology-agnostic guidelines. Scientists and data stewards can become lost in the jungle of technological approaches, wondering how to select the most FAIR-compliant data repository or improve metadata quality. FAIR-Checker is a tool designed to address this urgent need.
Added value
Providing quick, automated checks, ensuring research data aligns with FAIR principles, saving time and effort for researchers.
Improving data quality by identifying opportunities to make datasets more accessible, interoperable and reusable.
Boosting research impact by facilitating better data sharing across communities, increasing dataset visibility and fostering collaboration.
Overall FAIR assessment process using FAIR-Checker. Image: Alban Gaignard
SRIA General Objective
Research areas
Type of result
