• Lecturer: Jun.-Prof. Dr. Acosta
• Language: English
• Credits: 5 CP
• Examination: 100 % Written Exam (90 Minutes)

Course Description

Knowledge Graphs (KG) allow for representing inter-connected facts or statements annotated with semantics. In KGs, concepts and entities are typically modeles as nodes while their connections are modeles as directed and labeled edges, creating a graph. In recent years, KGs have become core components of modern data ecosystems. KGs, as building blocks of many Artifical Intelligence approaches, allow for harnessing and uncovering patterns from the data. Currently, KGs are used in the data-driven business processes of multinational companies like Google, Microsoft, IBM, eBay, and Facebook. Furthermore, thousands of KGs are openly available on the web following the Linked Data principles. The specific topics covered in the lecture are as follows:

1. Introduction to Knowledge Graphs
2. The Resource Description Framework (RDF)
3. RDF Schema (RDFS)
4. The SPARQL Query Language
5. Semantics of SPARQL
6. Linked Data: Knowledge Graphs and Ontologies on the Web
7. The Web Ontology Language (OWL)
8. Entailment Regimes
9. Reasoning over Knowledge Graphs
10. Property Graphs
11. Knowledge Graphs Applications