Speaker
Description
Research Data Management encompasses the systematic organization, storage, preservation, publication and re-use of data throughout a research project's lifecycle. It aims to ensure effective handling, maintenance, and accessibility of data, promoting reproducibility, transparency, and integrity in scientific research. The surge in digital research data led to the need for standardized practices which are already widely in use in the health domain.
Within the KISSKI Service Centre, the Leibniz Data Manager (LDM) will provide a semantically-driven data catalog which ensures data transparency and privacy protection while enabling data exchange within the respective research groups and scientific communities. The data catalog is developed at TIB – Leibniz Centre of Science and Technology. To enable shared data from two domains (i.e., health and energy), the LDM resorts to semantic integration using ontologies and standards to transform research, clinical, genomic, and scientific data into semantically rich factual statements. Digital research objects (e.g., data benchmarks) are available following the FAIR data principles. Because strict data access policies regulate health data (e.g., clinical and genomic data), two customized instances of the LDM are deployed representing both, an open data and a closed data system. While the public instance will support the publication and exchange of non-sensitive, anonymized data, the second instance will include a privacy-aware query engine and high security standards provided by partners at GWDG ensuring compliance with data access regulations. For future data use, aka AI-ready data, project partners will define domain-specific ontologies to establish a common understanding of the included medical datasets.
