Lessons learned from evaluating the NFDI4Health metadata schema for health studies using the Research Data Alliance's FAIR data maturity model

Objectives: The German National Research Data Infrastructure for Personal Health Data (NFDI4Health) has developed a metadata schema (MDS) for harmonizing health study descriptions, along with a platform for content discovery. This work evaluates how well the MDS promotes FAIR data principles (Findability, Accessibility, Interoperability, Reusability) and serves as a proxy for assessing study FAIRness. Materials and Methods: Using the Research Data Alliance's 'FAIR data maturity model', we assessed the scope of evaluable FAIRness indicators for NFDI4Health's MDS (version 3.3). Results: 29 of 41 FAIRness indicators can be evaluated (Findability: 7/7, Interoperability: 7/12, Accessibility: 7/12, Reusability: 8/10). The remaining indicators relate to the research data's format and access procedures. Discussion: The MDS provides a viable basis for evaluating study FAIRness. To enable full indicator coverage, additional metadata elements should be incorporated. Conclusion: NFDI4Health's MDS effectively promotes FAIR-compliant study descriptions, although adjustments could strengthen its utility for assessing research data FAIRness.