Thorsten Liebig

Biography

Thorsten CEO of derivo GmbH since 2010. derivo is an SME that supports leading European companies including Siemens, Schaeffler and Festo to successfully build and implement Knowledge Graphs and reasoning technology in complex technical domains. Thorsten studied Computer Science at Ulm University. He received national scholarships to work at the Information Sciences Institute at the University of Southern California and to finish his dissertation at Otto- von-Guericke University in Magdeburg. He also headed the international working group that specified OWLlink, a communication protocol for OWL, that became a W3C member submission in 2011.

Talks and Events

2022 Tutorial: Developing and Refining Schemas for Knowledge Graphs

An advantage of modeling data as a graph – as opposed to a relational data model – is that data graph does not require a data schema from the very beginning. Hence graph data is often loaded from external sources with ad-hoc mappings. However, a Knowledge Graph is mostly understood as a data graph enhanced with a schema, a mechanism to distinguish between data and meta-data and sometimes even axioms/rules. Schemata are of great benefit as they describe the structure and semantics of the data in the graph. KG schemata enable
• different views at various levels of abstraction for a better overview,
• explicit and therefore exchangeable meaning of the graph data,
• higher query performance,
• reasoning by means of axioms/rules.
The tutorial will explain the various schema modeling options for Labeled Property as well as RDF graph data models. We describe the different ways of representing schema information in both models and whether those models are embedded in the data graph or layered above it. Furthermore, we discuss similarities and mutual correspondences as well as advantages and shortcomings of the two graph models. The tutorial will demonstrate tools for the development, maintenance and review of schemas and exemplarily show how to develop and refine KG schemata in both models. In addition, attendees will have the opportunity to work with available KGs and tools to get hands-on experience.
List of the topics that will be studied during the tutorial:

• LPG and RDF schemata and context modeling options
• Compared expressivity of LPG and RDF schemata
• Schema extraction and refinement
• Integration of pre-existing schemata
• Query-, rule- or axiom-based schema materialization/enforcement
• Demonstration of tools to create, view and refine KG schemata

2020 Talk: Visual Analytics of Large Knowledge Graphs

Grasping large Knowledge Graphs is challenging. We present SemSpect, an innovative tool that brings together overview and detail view into one perspective by visually aggregating graph nodes and relationships for efficient exploration and data-driven querying of graphs. It comes either with a reasoning back-end for OWL RL for RDF or as a brand-new Graph App for Neo4j. In our talk we will report on experiences with business-critical, real-world Knowledge Graphs from various domains such as engineering industry, life sciences and intelligence.

View the complete talk in the KGC media library.