Knowledge Graphs (HWS 2025)

Knowledge graphs are a universal means of data representation which can be consumed by humans and machines alike, and is therefore a key ingredient in many modern data-driven systems and AI applications, which often need knowledge about the domain they operate in, and/or general purpose knowledge about the world. Knowledge graphs are increasingly used in companies and large organizations, with the most well-known application being the Google Knowledge Graph backing the search engine we all use on a day to day basis. There are also quite a few large-scale open knowledge graphs, like DBpedia or Wikidata, which can be freely used to fuel powerful AI applications.

This course gives an introduction to the underlying standards of knowledge graphs, including knowledge representation and query languages, as well as logical inference. More specifically, it covers the following contents:

• History of Knowledge Graphs and the Semantic Web
• Graph Representation Languages (XML, RDF)
• Graph Inference and Logical Reasoning (RDF Schema, OWL)
• Knowledge Modeling: Ontologies, Linked Data, and Property Graphs
• Knowledge Integration
• Data Quality in Knowledge Graphs
• Commercial and Open Source Tools and Systems

Besides theoretical lectures, the course also consists of hands-on exercises and a practical project in which you build a small knowledge graph backed application.

• Java or Python programming skills are required to pass this course!
• Preferably, some experience with software development
• To pass the course you have to fulfill the following requirements:
  • Pass the final exam (you have to get a 4.0 or better in the exam to pass this course)
  • Successfully work in a group on a project idea (programming!), present the results and write a report
• The final grade is the grade achieved in the final exam, however, the project is a mandatory requirement to pass the course.

• Lecture: Dr. Sven Hertling
• Practical Exercise: Dr. Juan Cano

• Lecture: Tuesday, 15:30 – 17:00, Room C015 Building A5,6 Part C
• Exercise: Friday, 12.00 – 13.30, Room D007 (2)  Building B6,27 Part D (in the backyard of  B6, 23 Part A)

Important dates for the group projects:

• Sunday, October 19th, 23:59: Submission of project proposals
• Sunday, November 30th, 23:59: Submission of final reports & Presentation in PDF

• Aidan Hogan et al.: Knowledge Graphs. Morgan & Claypool, 2022, available online
• Tim Berners-Lee, James Hendler and Ora Lassila. The Semantic Web. Scientific American, 284 (5), pp. 34–43, 2001
• Pascal Hitzler, Markus Krötzsch and Sebastian Rudolph. Foundations of Semantic Web Technologies. Chapman & Hall/CRC, 2009
• Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph and York Sure. Semantic Web: Grundlagen. Springer, 2007 (German)
• Allemang and Hendler (2008): Semantic Web for the Working Ontologist. Verlag Morgan Kaufmann.
• Antoniou and van Harmelen (2004): A Semantic Web Primer. MIT Press.
• Heath and Bizer (2011): Linked Data: Evolving the Web into a Global Data Space. Free online version.