Semantic Web and Knowledge Graphs
| Code | Completion | Credits | Range | Language |
|---|---|---|---|---|
| NIE-SWE | Z,ZK | 5 | 2P+1C | English |
- Garant předmětu:
- Milan Dojčinovski
- Lecturer:
- Milan Dojčinovski
- Tutor:
- Milan Dojčinovski, Jakub Klímek
- Supervisor:
- Department of Software Engineering
- Synopsis:
-
The students will learn the most recent concepts and technologies of the Semantic Web. The course will provide an overview of the Semantic Web technologies, methods and best practices for modelling, integration, publishing, querying and consumption of semantic data. The students will also gain skills in creation of knowledge graphs and their systematic quality assurance.
- Requirements:
-
Basic knowledge of algorithmics, Web technologies, HTTP, HTML, XML, URI, programming skills (e.g. Java), graph theory.
- Syllabus of lectures:
-
1. Key Semantic Web principles and the Semantic Web technology stack.
2. Data models for knowledge representation.
3. Modeling ontologies using Semantic Web languages.
4. Querying semantic data.
5. Prominent ontological models and their use.
6. Linked Data principles.
7. Methods and techonologies for Linked Data publishing.
8. Web Annotations.
9. (2) Semantic knowledge graphs: creation and use of knowledge graphs.
10. Methods for integration and fusion of semantic data.
11. Data quality assurance for the Semantic Web.
12. Machine-readable descriptions of semantic datasets (data
catalogs).
- Syllabus of tutorials:
-
1. Introduction, basic Semantic Web principles and technologies.
2. Ontologies.
3. Querying RDF data (SPARQL).
4. Data integration and Linked Data.
5. Data quality assurance (SHACL).
6. Web annotation mechanisms (microformats, microdata, RDFa).
- Study Objective:
-
This course deals with methods and models supporting automated processing and sharing information on the web by content and meaning. It focuses on formal models of knowledge representation (RDF, RDFS, OWL), their theoretical aspects and also on practical aspects (e.g., annotation of web resources, ontology mapping, querying and data quality assurance).
- Study materials:
-
1. Hitzler, P. - Krotzsch, M. - Rudolph, S. : Foundations of Semantic Web Technologies. Chapman and Hall/CRC, 2009. ISBN 978-1420090505.
2. Wood, D. - Zaidman, M. - Ruth, L. - Hausenblas, M. : Linked Data - Structured Data on the Web. Manning Publications, 2013. ISBN 9781617290398.
3. Pan, Z. P. - Vetere, G. - Gomez-Perez, J. M. - Wu, H. : Exploiting Linked Data and Knowledge Graphs in Large Organisations. Springer, 2017. ISBN 9783319456522.
4. Antoniou, G. - Groth, P. - van Harmelen, F. - Hoekstra, R. : A Semantic Web Primer. MIT Press, 2012. ISBN 0262018284.
- Note:
- Further information:
- https://courses.fit.cvut.cz/NI-SWE/
- Time-table for winter semester 2024/2025:
-
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri - Time-table for summer semester 2024/2025:
- Time-table is not available yet
- The course is a part of the following study plans:
-
- Master specialization Software Engineering, in English, 2021 (elective course)
- Master specialization Computer Security, in English, 2021 (elective course)
- Master specialization Computer Systems and Networks, in English, 2021 (elective course)
- Master specialization Design and Programming of Embedded Systems, in English, 2021 (elective course)
- Master specialization Computer Science, in English, 2021 (elective course)
- Study plan for Ukrainian refugees (elective course)
- Master Specialization Digital Business Engineering, 2023 (compulsory elective course, elective course)
- Master Programme Informatics, unspecified Specialization, in English, 2021 (elective course)
- Master specialization Computer Science, in English, 2024 (elective course)