Knowledge Graphs (HWS 2022)

Note: This lecture replaces the old lecture IE 650 Semantic Web Technologies.

Important: Portal2 initially showed a wrong time and place for this lecture. The lecture takes place on Tuesdays, 3:30 pm, in B6 30–32, E-F, room 209.

Course Description

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
  • Representation Languages (XML, RDF, RDF Schema, OWL)
  • Knowledge Modeling: Ontologies, Linked Data, and Property Graphs
  • Data Quality in Knowledge Graphs
  • Logical Reasoning in RDF and OWL
  • 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.

Exam Review

In case you want to review your second exam of HWS 2022, please write a mail to Bianca Lermer until Friday, 10 March 2023.


  • 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: Tuesday, 15:30 – 17:00, room B6 30–32, building part E-F, 209
  • Exercise: Friday, 12.00 – 13.30, room B6 A1.04


12.09.2022Lecture: IntroductionExercise: Introduction
19.09.2022Lecture: RDFExercise: RDF
26.09.2022Lecture: RDFSExercise: RDFS
03.10.2022Lecture: Linked Data, Semantic Web ProgrammingExercise: Linked Data, Semantic Web Programming
10.10.2022Lecture: SPARQL and other Query ParadigmsExercise: SPARQL, Kick off Group Projects
17.10.2022Lecture: Public Knowledge GraphsExercise: Public Knowledge Graphs
24.10.2022Lecture: Labeled Property GraphsExercise: Labeled Property Graphs
31.12.2022Public holidayNo exercise


Lecture: OWL Part 1Exercise: OWL Part 1
14.11.2022Lecture: OWL Part 2Exercise: OWL Part 2
21.11.2022Lecture: Knowledge ModelingExercise: Knowledge Modeling
28.11.2022Lecture: Data Quality and Interlinking

Exercise: Data Quality and Interlinking

05.12.2022Project Presentations 

Important dates for the group projects:

  • Sunday, October, 16th, 23:59: Submission of project proposals
  • Sunday, December 11th, 23:59: Submission of final reports