The Swiss Personalized Health Network FAIR Data Point: Bridging Semantic Interoperability and User-Friendly Metadata Discovery

The FAIR Data Point specification provides a standards-based framework for publishing FAIR metadata usingsemantic web technologies and linked-data standards. While FDPs support rich metadata representation andsemantic querying through RDF and SPARQL, these technologies can present a barrier for users who are primarilyinterested in discovering relevant datasets through intuitive search interfaces. The Swiss Personalized HealthNetwork FAIR Data Point extends the reference FDP implementation with a user-centered discovery layerdesigned to improve metadata exploration across health research datasets and catalogs. The SPHN FAIR DataPoint preserves the underlying FAIR-compliant semantic metadata model while introducing a lightweight JSON-based indexing mechanism that transforms RDF metadata into a retrieval-optimized representation. This indexpowers responsive full-text search and faceted filtering within the web interface, enabling users to quickly identifyrelevant resources without requiring knowledge of RDF, ontologies, or SPARQL. At the same time, the originalsemantic metadata remain accessible through standard FDP interfaces, including machine-readable metadataexports, REST API, and SPARQL-based querying. By combining standards-compliant semantic interoperabilitywith a lightweight search index, the SPHN FAIR Data Point provides two complementary pathways for accessingthe same metadata: semantic querying for advanced and machine-driven use cases, and interactive search andfiltering for human-centered dataset discovery. This approach enhances the usability and discoverability of FAIRmetadata within the SPHN Metadata Catalog and demonstrates a practical strategy for supporting both technicaland non-technical users in large-scale health data ecosystems.