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| Item Type: | Preprint |
|---|---|
| Title: | Advancing FAIR sharing for epidemiological, clinical and public health study data - services and community integration of the German National Research Data Infrastructure NFDI4Health |
| Creators: |
Pigeot, Iris, Peters, Manuela |
| Abstract: | BACKGROUND: Access to high-quality, FAIR health data is essential for advancing epidemiological, public health and clinical research. NFDI4Health, one of the consortia of Germany’s National Research Data Infrastructure (NFDI), was established in 2020 to address this need by improving data FAIRness for the scientific community. METHODS: During the initial funding phase, NFDI4Health developed key infrastructure components and services focusing on interoperability, data sharing and research support. Our approach was guided by user needs and real-world use cases in alignment with (inter)national FAIR standards and infrastructures. RESULTS: We advanced findability of health data by establishing a central Health Study Hub and connecting it to local infrastructures, e.g., through the Local Data Hub software, to facilitate transfer of metadata from the local infrastructures to the Health Study Hub. Accessibility was improved by expanding the German Research Data Portal for Health (FDPG) to provide central access to study data and by providing tools to support anonymisation and synthetic data generation. We also developed an interoperable metadata schema for publishing study data and implemented it in the Health Study Hub. To further improve interoperability, a NFDI4Health FAIR sharing collection and AI support for metadata annotation and harmonisation workflows were established. To enhance reusability, data quality assessment tools were further developed, and two frameworks for federated analysis of sensitive health data were piloted. Intensive engagement with our communities through training, advisory services, and collaborative development ensured user relevance. CONCLUSION/OUTLOOK: NFDI4Health has established a scalable, interoperable, and user-centred infrastructure to support FAIR data sharing in health research. Future work will focus on further developing and consolidating the infrastructure, expanding cross-domain data integration, fostering broader adoption within our research community, and strengthening national and international collaboration. |
| Keywords: | Data Sharing, Federated Data Analysis, Health Study Hub, Metadata, Reusability, Synthetic Data, FAIR, Health Data Literacy, Data Quality |
| Source: | Research Square |
| Publisher: | Research Square |
| Article Number: | rs.3.rs-10082861/v1 |
| Date: | 30 June 2026 |
| Official Publication: | https://doi.org/10.21203/rs.3.rs-10082861/v1 |
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