NFDI4Health – National Research Data Infrastructure for Health

The vision of NFDI4Health is to establish a comprehensive and sustainable research data infrastructure for personal health data in Germany, facilitating advancements in medical research and public health while ensuring compliance with ethical standards and data protection regulations.

In recent years, the proliferation of health-related data from clinical trials, epidemiological studies, and public health surveys has underscored the need for a unified infrastructure that enables secure and efficient data sharing. Personal health data are particularly sensitive and require stringent privacy protections, which often hinder their accessibility and interoperability. NFDI4Health aims to address these challenges by promoting the FAIR principles (Findable, Accessible, Interoperable, Reusable) in health data management.

The overarching objective of NFDI4Health is to develop, implement, and maintain a national research data infrastructure that enhances the findability and accessibility of structured health data. This includes creating a federated framework for data-holding organizations, facilitating data exchange and record linkage in compliance with privacy regulations, and establishing automated services such as search and analysis tools. By fostering interoperability and reusability of data, NFDI4Health seeks to support collaborative research efforts across various health-related disciplines.

NFDI4Health represents the clinical and epidemiological research communities in Germany, encompassing a multidisciplinary consortium with expertise in medicine, epidemiology, law, informatics, and statistics. In its initial phase, NFDI4Health focuses on integrating data from clinical trials, epidemiological studies, and public health surveys, aiming to create a harmonized and accessible repository of personal health data to advance medical research and improve public health outcomes.

• Data Fragmentation: Health research data is often dispersed across various institutions and systems, leading to fragmented datasets that hinder comprehensive analysis. This dispersion complicates efforts to integrate data for large-scale studies and impedes the development of holistic health insights.
• Privacy Constraints: The sensitive nature of personal health information imposes strict privacy regulations, limiting data accessibility for research purposes. These constraints pose significant challenges in balancing the need for data-driven health advancements with the imperative to protect individual privacy.
• Standardization Deficits: The lack of uniform standards for data collection, formatting, and terminology in health research leads to inconsistencies that obstruct data interoperability. This deficiency hampers the ability to effectively share and compare data across different studies and institutions.

• Enhance the findability and accessibility of structured health data from clinical trials, epidemiological studies, disease registries, administrative health databases, and public health surveillance in Germany.
• Implement a health data framework for centralized searching and accessing existing decentralized epidemiological and clinical trial data infrastructures.
• Facilitate data sharing, record linkage, harmonized data quality assessments, and federated analyses of personal health data.
• Enable the development and deployment of new, machine-processable consent mechanisms and innovative data access services.
• Support cooperation between clinical trial research, epidemiological, and public health communities.
• Foster interoperability of currently fragmented IT solutions related to metadata repositories, cohort browsing, data quality, and harmonization.
• Develop and provide services such as data harmonization, anonymization tools, annotation workbench, terminology services, and FAIR training to support researchers in managing and sharing health data responsibly.
• Establish Local Data Hubs (LDHs) to support federated data structuring and sharing for sensitive health data, ensuring data remains under the control of data owners while being discoverable and accessible through a centralized platform.

• Fraunhofer-Gesellschaft (Fraunhofer FIT, MEVIS, SCAI)
• Leibniz Institute for Prevention Research and Epidemiology – BIPS
• Berlin Institute of Health at Charité (BIH)
• German Institute of Human Nutrition Potsdam-Rehbruecke
• Heidelberg Institute for Theoretical Studies (HITS)
• KKS Network
• Max Delbrück Center for Molecular Medicine
• Robert Koch Institute
• TMF – Technology, Methods, and Infrastructure for Networked Medical Research
• University of Bonn
• University of Bremen
• University and City Library of Cologne
• University Hospital of Cologne
• Leipzig University (IMISE, LIFE, CTRL)
• University of Applied Sciences Mittweida
• University Medical Center Göttingen
• Greifswald University Hospital

Funding: DFG (Deutsche Forschungsgemeinschaft)