Semantic Systems Engineering
The research group Semantic Systems Engineering focuses on the research of approaches and algorithms that enable heterogeneous data from different data silos and software systems to be seamlessly collected, integrated, found, understood and processed by humans as well as other technical systems. The main research topics cover in particular the construction, continuous evolution and refinement of knowledge graphs, the (semi-)automated creation of semantic models as well as the improvement of accessibility and usability for semantic technologies in daily business. For this purpose, we especially rely on methods from the area of Artificial Intelligence, such as Graph Neural Networks (GNNs) and Graph embeddings.
Areas of Research
Using embeddings to calculate similarities of semantic concepts
Mapping, modeling and use of knowledge in knowledge graphs and ontologies.
Automatic construction and improvement of semantic models for data management
Building holistic IT systems with semantic concepts as core components
Areas of Application
Integration of heterogeneous data using semantic knowledge graphs
Automated data processing based on semantic descriptions
Management of IoT sensor technology on a semantic level
Development of holistic data management solutions based on the Data Space reference architecture
