Local Data Hub

Your Local Data Hub - business card and portal for your institution's research data management

The Local Data Hub serves to present and exchange your projects, studies, publications, (bio)medical data, models and software tools from the field of health research and is based on the FAIR principles (Findable, Accessible, Interoperable, Reusable).
You can use this tool for research data management directly in your institution - here is an example for the Local Data Hub of the ZKS Leipzig.

In the Local Data Hub, detailed supplementary resources such as study protocols, data sets, references to publications, repositories, registers and analysis platforms are networked and presented in context. Institutions, contact persons and authors, sponsors and funding programs, presentations and studies and much more can be networked and searched. Access to the resources can be open to the public, to a group, only locally or to a small number of people. Existing, proprietary heterogeneous data and project portals may become superfluous. We work according to the principle of Software-as-a-Service: the web-based solution allows various forms of operation, fully operated by you or centrally hosted.

The underlying tool FAIRDOM SEEK is established and, together with the international community, is continuously adapted, further developed and optimized by NFDI4Health to meet the needs of clinical studies, epidemiological cohorts and public health studies.

The NFDI4Health team will support you with installation and training.

Advantages for your users

All information, documents and data for your project in one place.

Automatic retrieval of publication metadata for PubMed publications + author list link.

Direct publication of content in the NFDI4Health German Central Health Study Hub.

Project-specific assignment of rights - you alone decide on access.

Contains the verified NFDI4Health metadata schema.

Advantages as an operator

Independent, license-free data sharing platform.

Permanent archiving of all research activity (citation and referencing).

Connection of own and NFDI4Health tools for data exploration, enrichment and quality assurance.

Documentation for installation and training for operation is a service provided by NFDI4Health.

System requirements

We recommend the use of software containers/ Docker, Linux or Windows (WSL2); a native Linux installation is also possible.
Software and installation instructions can be found here.
Low hardware resources are required (e.g. Linux VM).

Download Local Data Hub Flyer

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.

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

DataSHIELD

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.