Health Study Hub

German Central Health Study Hub – A platform to find and publish personal health research data

The German Central Health Study Hub is a platform that serves two different kinds of users. First, it allows scientists and data holding organizations (data producers) to publish their project characteristics, documents and data related to their research endeavour in a FAIR manner. Obviously, patient-level data cannot be shared publicly, however, metadata describing the patient-level data along with information about data access can be shared via the platform (preservation description information). The other kind of user is a scientist or researcher (data consumer) that likes to find information about past and ongoing studies and is interested in reusing existing patient-level data for their project. To summarize, the platforms connect data providers with data consumers in the domain of clinical, public health and epidemiologic health research to foster reuse. Since the system is freely accessible via a web browser and provides explanatory information about collected information via an extensive glossary, the system can also be used by scientists of other research domains.


The aim of the German Central Health Study Hub is to make research data from clinical, public health and epidemiological studies as accessible as possible to people and machines. This does not mean, however, that the data are publicly accessible and can be reused without restriction. Rather, the aim is to open up research results and data for new usage scenarios within the legal and technical limits. 

Data holders (data producers) can publish their information according to the FAIR principles (Findable, Accessible, Interoperable and Reusable) via a graphical web-based user interface or an interoperable application programming interface (API).

How FAIR are your data? Test your data with our checklist for studies and get a first impression:

As sharing data is often seen as a burden or an afterthought, the process of doing so must be as simple and straightforward as possible. Consequently, information should be collected once and not multiple times. APIs are therefore available to transfer information from existing (internal) systems, and software consultants can assist in developing the necessary transformation processes. Where information cannot be re-used, a graphical data capture form is available and trained data stewards are available to assist with data capture.

The platform aggregates and harmonizes information
In addition, the platform aggregates and harmonizes information already entered in various public repositories such as DRKS,, WHO ICTRP to provide a holistic view of the German research landscape in the aforementioned research areas. In addition, data stewards actively collect available information from (public) resources such as websites that cannot be automatically integrated.

The inventory of descriptive information and preservation data, either transferred/input by data producers, collected by other repositories or actively collected by data stewards, is an asset used by the platform to enable data consumers (scientists or researchers) to find relevant information about past and ongoing studies and to provide information about access rights. Depending on the data available, semantic search and exploration down to variable and item level is possible. In addition, the system links research artefacts and provides summary statistics on the available data.

The service started during the COVID-19 pandemic
The development of the service started during the COVID-19 pandemic to establish a nationwide COVID-19 research information and advice infrastructure. To ensure the long-term availability of the service, the scope was extended to include personal health research data in Germany, and further development is being carried out within the NFDI4Health project. The number of records grew steadily to over 1600 records in April 2023. Similarly, the number of page visits and registered users grew, indicating increased usability of the service.   

As the platform is developed for the community, it must meet the community's requirements and needs. To achieve this, the software is developed interactively with the community (represented by use cases within the project). However, we also invite everyone else to suggest features, ideas, requirements and report bugs to the development team.

Our Services

Health Study Hub

The German Central Health Study Hub allows researchers to publish their project characteristics, documents and data related to their research project in a FAIR manner or to find information about past and ongoing studies.

Data Train

The Data Train cross-disciplinary graduate training programme, a core element of the NFDI4Health training approach, aims at building the next generation of data-savvy researchers in the biomedical sciences.

Personal Health Train

To foster data-driven innovation in medicine, we developed a distributed analysis infrastructure that enables research on sensitive data without prior data sharing while supporting diverse data formats.

Local Data Hub

The LDH is the local node in the federated concept of NFDI4Health. We develop and promote the dissemination of a unified data sharing platform based on the FAIR principles in line with the NFDI4Health standards.

Data publication

Health data, as collected in clinical trials and epidemiological, as well as public health studies, cannot be freely published, but are valuable datasets whose reuse is of high importance for health research. NFDI4Health has established a metadata standard and process for the publication of health studies to make health data FAIR.

Data harmonisation

To make health studies and their data FAIR we have developed guidelines and standards for metadata description and data sharing. We have developed data publication guidelines, common metadata description standards and adaptations of health data interoperability standards to harmonize the description of studies and their corresponding metadata.

Data Quality Assessment

It is a paradox: on the one hand, good scientific work depends on high data quality. On the other hand, a lot of effort is put into the design and conduct of studies, but not into data quality assessments. We help to facilitate the efficient performance of such assessments with versatile concepts and tools


Expansion of decentralised research projects with DataSHIELD: Until now, data protection concerns and the lack of special IT infrastructure have prevented the expansion of cross-institutional research projects. DataSHIELD is intended to solve that problem.
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