Currently submitted to: JMIR Medical Informatics
Date Submitted: Dec 23, 2025
Open Peer Review Period: Jan 4, 2026 - Mar 1, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
The SPHN Metadata Catalog: A platform for health data discovery and exploration based on FAIR principles
ABSTRACT
Background:
The Swiss Personalized Health Network facilitates the interoperability and secure sharing of health-related data for research in Switzerland, in line with the FAIR principles. Since medical datasets can be highly sensitive, access is often governed by complex legal and regulatory requirements. Enabling researchers to discover, understand, and evaluate datasets through rich, well-structured metadata is therefore essential to support informed decisions about data suitability and reuse.
Objective:
This study describes the design and functionality of the SPHN Metadata Catalog and its role in supporting the discovery, exploration, and reuse assessment of health-related datasets.
Methods:
The SPHN Metadata Catalog is a FAIR Data Point-compliant infrastructure that provides rich, structured metadata in both human and machine-readable form. Dataset descriptions are based on HealthDCAT, ensuring a standardized representation of health data catalogs. Beyond the descriptive metadata typically offered by other catalogs, the SPHN Metadata Catalog includes extensive dataset-level statistics expressed using the Vocabulary of Interlinked Datasets. An interactive visualization component further enables users to explore graph-based schemas and datasets, including entities, attributes, relationships, and their relative abundances.
Results:
The SPHN Metadata Catalog enables users to explore the semantic structure of graph schemas and statistics of datasets prior to requesting access. Researchers can examine data structures, relationships, attributes, and the abundances of individual data elements. This functionality supports feasibility assessments and informed evaluations of dataset suitability and reuse conditions.
Conclusions:
By combining HealthDCAT-based descriptions with rich statistical metadata and interactive exploration capabilities, the SPHN Metadata Catalog enhances dataset discoverability and supports FAIR-compliant data reuse. As a key component of Switzerland’s health data research infrastructure, the SPHN Metadata Catalog provides a foundation for future interoperability initiatives, including potential alignment with emerging frameworks such as the European Health Data Space.
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Copyright
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