Knowledge Integration and Linked Data Technologies

What kind of smart applications can we build, if we were able to integrate all available knowledge, data and language resources in a meaningful way? While Turing's imitation game is exciting, we are focussing on the actual knowledge engineering to build information machines that enable humans to perform more efficiently in their tasks. To achieve this goal, we believe the following two prerequisites must be met:

1. Knowledge and Data must be rendered discoverable and then transformed, linked, enriched and integrated homogeneously in a huge semantic knowledge graph (DBpedia)
2. Language Technologies must be on the one hand leveraged to understand, categorize and structure available textual content in all its forms. On the other hand, language technology must assist in building adequate interfaces that allow humans to interact effectively with data and information via discovery, querying and reorganization.

Research in this group focusses on contextualising data and ontologies as well as capturing deep linguistic knowledge to improve machine understanding. Besides research, we are taking the extra effort to undertake transfer and innovation projects and support industrial applications such as in the JURION use case.

Main contact: Dr.-Ing. Sebastian Hellmann