Toward a Domain-Overarching Metadata Schema for Making Health Research Studies FAIR (Findable, Accessible,...

Area of Science:

• Health Informatics
• Data Science
• Epidemiology

Background:

• Implementing FAIR principles in health research faces challenges, particularly with data interoperability across diverse sources.
• Clinical trial registries capture study metadata, but many epidemiological and public health studies lack detailed, accessible information.
• Improved data sharing from these studies is crucial for advancing understanding of diseases and risk factors.

Purpose of the Study:

• To develop a tailored metadata schema (MDS) for standardized publication of health study metadata within NFDI4Health and other services.
• To enhance the FAIRness of metadata from clinical, epidemiological, and public health research.
• To ensure compatibility with existing metadata models for improved interoperability.

Main Methods:

• Developed an MDS based on DataCite, ClinicalTrials.gov, and international standards, initially by the NFDI4Health Task Force COVID-19.
• Extended the MDS modularly with generic and use-case-specific items (nutritional epidemiology, chronic diseases, record linkage) and mapped it to external schemas.
• Utilized ART-DECOR for transformation into a machine-readable format, facilitating editing, maintenance, and versioning.

Main Results:

• The MDS is implemented in NFDI4Health services, structuring and exchanging study metadata.
• Version 3.3 includes 220 metadata items across 5 modules, covering generic and domain-specific information.
• Mappings to clinical trial registries and other resources facilitate metadata integration and interoperability.

Conclusions:

• Implementation in NFDI4Health services improves data FAIRness for clinical, epidemiological, and public health research.
• The schema's generic nature and interoperability make it transferable to adjacent domains, benefiting a wider user community.