NFDI4Health

National Research Data Infrastructure for Personal Health Data (NFDI4Health) is a german national project that deals with data generated in clinical trials, epidemiological and public health studies. It aims to foster the fulfillment of the FAIR principles requirements and collaboration between these communities. The mission of NFDI4Health is to provide new opportunities for the scientific use of personal health data while respecting privacy requirements.
Based on the FAIR principles, services are provided to researchers to permanently store, semantically enrich and share data in interoperable form and to merge data from different sources.

For more information about the project, visit www.nfdi4health.de/en/

Description of the NFDI4Health Metadata Schema (NFDI4Health-MDS)

NFDI4Health developed a metadata schema (MDS) based on several international standards and studies' registries to collect metadata from clinical, epidemiological and Public Health studies, and associated resources.

The MDS is composed of a generic, core module and further specialized modules to describe the design of certain resources or for specific use cases.

At this stage we provide the following versions of the MDS in ART-DECOR:

• Version 3.0 (Published)

• Version 3.3 (Published)

  • Publisso

  • Simplifier

  • Graphical Representation

  • Data harmonisation and publication - NFDI4Health

Aim of the NFDI4Health-MDS

The NFDI4Health metadata schema (NFDI4Health-MDS) is an information model tailored to describe design elements and context of clinical, epidemiological, and public health studies as well as associated resources such as documents (e.g., study protocol, instruments) or datasets. The NFDI4Health-MDS improves the FAIRness of the cataloged studies and associated resources by making the content searchable and accessible through dedicated centralized search portals such as the German Central Health Study Hub (https://csh.nfdi4health.de/), as well as locally through systems such as NFDI4Health Local Data Hubs (https://www.nfdi4health.de/en/service/local-data-hub.html).

To ensure a broad applicability, the NFDI4Health-MDS combines common elements from reference data models and their controlled vocabularies (value sets). It is modular in design to allow the description of studies from different domains with their specific metadata requirements. In addition to a common core module, the NFDI4Health-MDS contains modules that are specific to certain scientific domains, such as nutritional epidemiology, or for the description of chronic diseases. These modules were developed based on input from subject matter experts involved in NFDI4Health use cases. The metadata model is constantly expanded based on the needs of the user community.

This work serves as base for the NFDI4Health-MDS Simplifier Project.

Authors

Content in ART-DECOR:

• Haitham Abaza, Heidelberg Institute for Theoretical Studies (HITS)

• Paula J. Mayer, Berlin Institute of Health at Charité, Universitätsmedizin Berlin

• Carina N. Vorisek, Berlin Institute of Health at Charité, Universitätsmedizin Berlin

NFDI4Health Subgroup "Metadata schema and standard mapping" of NFDI4Health and of the NFDI4Health Task Force COVID-19:

• Haitham Abaza, Heidelberg Institute for Theoretical Studies (HITS)

• Aliaksandra Shutsko, ZB MED – Information Centre for Life Sciences, Cologne

• Martin Golebiewski, Heidelberg Institute for Theoretical Studies (HITS)

• Sophie A. I. Klopfenstein, Berlin Institute of Health (BIH) at Charité, Universitätsmedizin Berlin

• Carsten Oliver Schmidt, University Medicine Greifswald

• Carina N. Vorisek, Berlin Institute of Health at Charité, Universitätsmedizin Berlin

With contributions from:

• Claudia Brünings-Kuppe, Leibniz Institute for Prevention Research and Epidemiology (BIPS), Bremen

• Vera Clemens, ZB MED – Information Centre for Life Sciences, Cologne

• Johannes Darms, ZB MED – Information Centre for Life Sciences, Cologne

• Sabine Hanß, University Medicine Göttingen

• Timm Intemann, Leibniz Institute for Prevention Research and Epidemiology (BIPS), Bremen

• Franziska Jannasch, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke

• Elisa Kasbohm, University Medicine Greifswald

• Birte Lindstädt, ZB MED – Information Centre for Life Sciences, Cologne

• Matthias Löbe, University Leipzig

• Ester Orban, coverCHILD

• Ines Perrar, University of Bonn

• Manuela Peters, Leibniz Institute for Prevention Research and Epidemiology (BIPS), Bremen

• Ulrich Sax, University Medicine Göttingen

• Matthias Schulze, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke

• Claudia Schupp, coverCHILD

• Florian Schwarz, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke

• Carolina Schwedhelm, MDC-Berlin

• Stefan Strathmann, Georg-August-Universität Göttingen

• Dagmar Waltemath, University Medicine Greifswald

• Hannes Wünsche, Robert Koch Institute (RKI), Berlin

• Atinkut A. Zeleke, University Medicine Greifswald

Acknowledgments

This work was done as part of the NFDI4Health Task Force COVID-19 and NFDI4Health National Research Data Infrastructure for Personal Health Data (www.nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Numbers 451265285 and 442326535.