preVIEW: COVID-19 – Information search in preprints made easier

The Preprint Viewer was developed as the first result of the COVID-19 Task Force. Members of NFDI4Health launched the initiative to make it easier for the specialist community to find relevant studies and to exchange data more effectively. The COVID-19 Task Force is funded by the DFG.

Currently, preprints from bioRxiv, medRxiv, ChemRxiv, arXiv, Preprints.org, ssrn and researchsquare are integrated into the service.

The tool, which is based on text mining, was developed in the research group of Prof. Dr. Juliane Fluck. It offers advanced search and filter functions for abstracts, direct links to the corresponding full texts and export functions for retrieved results. The abstracts are updated daily.

Go to the COVID-19 Preprint Viewer: https://preview.zbmed.de

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

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.