Scientific Data Management research group

Prof. Dr. Maria-Esther Vidal

© Quelle: Christian Malsch / LUH

The Scientific Data Management research group was founded in 2021 with the aim of addressing data management challenges in every phase of scientific work. The research group is headed by Prof. Dr. Maria-Esther Vidal.

 

The Scientific Data Management research group was founded in 2021 with the aim of addressing data management challenges in every phase of scientific work. The research group is headed by Prof. Dr. Maria-Esther Vidal.

 

​​The challenges that the research group is working on include:

  • Devise Knowledge graphs able to encode the meaning and context of scientific data and contain knowledge about provenance, privacy, quality, and uncertainty.
  • Domain-specific ontologies and link discovery techniques are capable of promoting the interoperability of heterogeneous and large scientific datasets in a scalable manner.
  • Integration methods for heterogeneous and extensive scientific data sources, for example, legacy data, structured and unstructured data, as well as static data and continuous data streams.
  • Storage and distribution of large-scale scientific data and knowledge graphs.
  • Access control methods to enforce privacy regulations for sensitive data. 
  • Query engines for distributed scientific knowledge graphs.
  • Data analysis and methods of knowledge discovery via scientific knowledge graphs.