M164 - CS2: Knowledge Technologies  

Fall 2023-2024

General Information

  The goal of this course is to introduce the theory and practice of Knowledge Technologies to graduate students. The course belongs to the general area of  Artificial Intelligence and covers some modern topics in  Knowledge Representation and Reasoning .
   In the last few years the course focuses on  Knowledge Representation and Reasoning for the World Wide Web, i.e., on the research areas of Semantic Web and Linked Data . We study the fundamental principles of the Semantic Web and Linked Data, related technologies that have been developed recently and how to build applications using these technologies. In this way, we study in depth a modern research area that has been significantly productive lately and has the vision of changing radically what the World Wide Web is today.
   The course is targeted to students that have already completed an undergraduate course in Artificial Intelligence (e.g., "Artificial Intelligence" or "Logic Programming" offered by our department), Databases (e.g., the course on relational data modeling and SQL offered in our department) and are familiar with Web technologies.
  The material covered by the course is at the frontiers of current research in this area. Students that complete the course successfully can immediately start their M.Sc. thesis in the areas of Semantic Web and Linked Data.

Course Material

  1. Introduction to Knowledge Graphs, the Semantic Web and Linked Data.
  2. The Resource Description Framework (RDF, RDFS, RDF*) 
  3. Shapes Constraint Language (SHACL)
  4. The query language SPARQL, SPARQL Formalization
  5. Description logics, tableaux techniques
  6. The Web Ontology Language (OWL)
  7. Ontology Engineering
  8. Rule languages for the Semantic Web
  9. A Data Science Pipeline for Big Linked Earth Observation Data, Discovering Earth Observation Data
  10. Linked spatial and temporal data. Spatial and temporal extensions to RDF and SPARQL
  11. Transforming geospatial data into RDF
  12. YAGO2geo & Geospatial Question Answering

Marking Scheme

  • Assignments that will include theoretical problem solving and software development: 70%
  • Term Project:  30%



Main Bibliography:

Other Related Sources:

  • Tom Heath and Christian Bizer. Linked Data: Evolving the Web into a Global Data Space (1st edition). Synthesis Lectures on the Semantic Web: Theory and Technology, 1:1, 1-136. Morgan & Claypool, 2011. Book website

  • Glen Hart and Catherine Dolbear. Linked Data: A Geographic Perspective. CRC Press, 2013. Book website

  • Dean Allemang and James Hendler. SEMANTIC WEB FOR THE WORKING ONTOLOGIST: Effective Modeling in RDFS and OWL. Elsevier Science & Technology Books, May 2008. Book website

  • Heiner Stuckenschmidt and Frank van Harmelen. Information Sharing on the Semantic Web. Springer, 2005.

  • Asunción Gomez-Perez, Mariano Fernandez-Lopez and Oscar Corcho. Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web, 2nd edition, Springer, 2007.

  • John Davies, Dieter Fensel, Frank van Harmelen and Frank van Harmelen (editors). Towards the Semantic Web: Ontology-Driven Knowledge Management. John-Wiley, 2003.

  • John Davies, Rudi Studer and Paul Warren (editors). Semantic Web Technologies: Trends and Research in Ontology-based Systems: Trends and Research. John-Wiley, 2006.