Course details

Ontologie a sémantický web

SWD Acad. year 2023/2024 Winter semester

Explicit knowledge representation, knowledge graphs. Formal description of data semantics using Resource description framework. Ontologies and languages for their description. Querying over knowledge graphs, linked data and existing knowledge bases. Design and publication of ontologies and linked data, design patterns, quality, consistency. Creating software applications based on semantic technologies and existing software tools.

Guarantor

Burget Radek, doc. Ing., Ph.D. (DIFS)

Language of instruction

Czech, English

Completion

Examination

Time span

  • 26 hrs lectures

Assessment points

  • 100 pts final exam

Department

Department of Information Systems (UIFS)

Learning objectives

Gain an overview of formal data semantics modelling, linked data creation and publishing. Master the design of knowledge-based applications using Semantic Web technologies.

Study literature

  • Stuart, D. (2016). Practical Ontologies for Information Professionals. Facet. doi:10.29085/9781783301522
  • Aidan Hogan, et al. (2021) Knowledge Graphs, Synthesis Lectures on Data, Semantics, and Knowledge, No. 22, 1–237, DOI: 10.2200/S01125ED1V01Y202109DSK022, Springer
  • Rudi Studer (Editor), Stephan Grimm (Editor), Andreas Abecker (Editor). 2007. Semantic Web Services: Concepts, Technologies, and Applications, Springer

Fundamental literature

  • Dean Allemang, Jim Hendler, and Fabien Gandon. 2020. Semantic Web for the Working Ontologist: Effective Modeling for Linked Data, RDFS, and OWL (3rd. ed.). Association for Computing Machinery, New York, NY, USA.
  • Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph. Foundations of Semantic Web Technologies. 2009. Chapman and Hall/CRC; 1st edition
  • Tom Heath and Christian Bizer. 2011. 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.

Syllabus of lectures

  1. Knowledge representation, explicit and parametric representation, knowledge graphs.
  2. Resource description framework (RDF) and formal semantics.
  3. Ontologies in the context of IT, languages for ontology representation.
  4. Description logic and OWL.
  5. Serialization and storage of knowledge graphs.
  6. Querying over knowledge graphs, query languages.
  7. Existing ontologies and knowledge bases.
  8. Ontology design, requirements analysis, inference, consistency.
  9. Rules and constraints, SWRL and SHACL languages.
  10. Linked data, design patterns.
  11. Data semantics on the WWW.
  12. Architecture and implementation of semantic applications.
  13. Software tools and libraries.

Progress assessment

Writing and presentation of a paper on the chosen topic, exam. Teaching is carried out in the form of lectures or guided self-study; missed classes must be covered by self-study.

Course inclusion in study plans

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