FAIR is a set of data stewardship principles that promotes making research data Findable, Accessible, Interoperable, and Reusable.
FAIR practices improve discoverability and structured reuse of datasets by applying standardized metadata, identifiers, and formats. In clinical research, FAIR implementation must balance data sharing with privacy protections, consent limitations, and security requirements. Adoption supports reproducibility, secondary research value, and efficient cross-study integration. FAIR-aligned data practices are increasingly tied to expectations from funders and scientific stakeholders and can strengthen confidence in research outputs.