DBIS

Knowledge Graphs represent knowledge as a network of entities and their relationships and form the basis of many modern data-driven applications. As part of the W3C Semantic Web initiative, standards and technologies have been developed for machine-readable exchange of data, information and knowledge on the Web, which to this day provide the technical foundation of open Knowledge Graphs. These standards and technologies are increasingly being used in applications and have already led to a number of exciting projects (e.g. DBpedia, Wikidata, semantic wikis, or commercial applications such as schema.org, OpenCalais, or Google’s Knowledge Graph). Increasingly, Knowledge Graphs also serve as a foundation for generative AI: they supply large language models with reliable, structured factual knowledge and thus enable traceable answers. Approaches such as graph-based retrieval-augmented generation (GraphRAG) combine the expressive power of language models with the precision and verifiability of symbolic knowledge representation. The module provides a theoretically grounded and practically oriented introduction to this area. The topics discussed within the lecture include: history of the Web, Semantic Web and Knowledge Graphs; RDF syntax and data model; RDF Schema and formal semantics of RDF(S); ontologies in OWL and formal semantics of OWL; graph and RDF databases, triple and knowledge stores, query languages; Linked Data Web and Knowledge Graph applications.