JMIR Publications

ABSTRACT

Background:

Despite wide acceptance in medical research, implementation of the FAIR principles (Findability, Accessibility, Interoperability, Reusability) is lacking in certain health domains and interoperability across data sources remains a challenge. While clinical trial registries collect metadata about clinical studies, numerous epidemiological and public health studies examining chronic disease burden remain unregistered or missing detailed information about relevant study documents. Making valuable data from these studies available to the research community could potentially improve our understanding of these diseases and their risk factors. The National Research Data Infrastructure for Personal Health Data (NFDI4Health) seeks to optimize data sharing among the clinical, epidemiological, and public health research communities, while preserving privacy and ethical regulations. To this end, a metadata schema (MDS) is developed to support the standardized publication of health studies’ metadata on the German Central Health Study Hub (GCHSH), thus making them searchable and findable.

Objective:

This paper describes the development, structure, and implementation of a metadata schema designed to improve the FAIRness of data from clinical, epidemiological, and public health research, while maintaining compatibility with existing data models to ease interoperability.

Methods:

Based on DataCite, ClinicalTrials.gov, and other international standards and models, the first MDS version was developed by the NFDI4Health Task Force COVID-19. It was later extended in a modular fashion, combining generic and use case-specific metadata items relevant to the nutritional epidemiology, chronic diseases, and record linkage domains, the first three use cases covered by NFDI4Health. Mappings to schemas of clinical trial registries and international initiatives were performed to enable interfacing with external resources. The schema is represented in Excel spreadsheets. Yet, a transformation into the ART-DECOR tool was completed towards an improved machine-readable version.

Results:

The MDS comprises over 200 metadata items in five modules. Generic metadata, such as bibliographic and design and data access information, are covered by the core and design modules. Domain-specific metadata are included in use case modules, currently dedicated to nutritional epidemiology, chronic diseases, and record linkage. All modules incorporate mandatory, optional, and conditional items. Mappings to clinical trial registries are used by the GCHSH to automatically upload and display study metadata from their portals. Mappings to other schemas are still in progress, yet several commonalities were identified in the first iterations. Information in the Excel version was fully represented in ART-DECOR.

Conclusions:

With its implementation in the GCHSH, the schema promises to improve the FAIRness of data from clinical, epidemiological, and public health research. Due to its generic nature, it is also transferable to adjacent research fields and useful for a broader user community. The mapping activities and representations enable interoperability with other systems, yet various challenges need to be resolved. Future extensions include clinical trials and imaging/radiomics dedicated modules.