Knowledge Management in the Web
Master's programme(s):
MSc in Data Science, MSc in Information and Communication Technology (ICT) Systems, MSc in Cybersecurity
Course code(s):
DSE01, ISE02, CE03
Instructors:
Course type:
Elective, Elective, Elective
Semester:
2, 2, 2
Learning outcomes:
On completing the course, the student will acquire:
- Knowledge: Familiarization with principles and technologies for representing and reasoning about data, metadata, and knowledge in the Semantic Web, Familiarization with Ontology Engineering and Knowledge Graph deployment techniques, Training on XML editors/processors and RDF and Ontology editors, RDF databases (triplestores).
- Skills: Developing metadata vocabularies and ontologies, Representation of data, metadata, knowledge and ontologies using the following languages: XML, DTD, XSLT, XPATH, RDF, RDF Schema, SPARQL, OWL, SWRL and SPIN.
General competences:
- Search for, analysis and synthesis of data and information, with the use of the necessary technology
- Decision-making
- Working independently
- Production of new research ideas
- Project planning and management
- Criticism and self-criticism
- Production of free, creative and inductive thinking
Syllabus:
- Introduction and General vision of the Semantic Web (SW). SW Architecture. Technologies and Languages of the SW. Modern examples of applications using the SW.
- XML (Description, DTD, Namespaces, XPath, XML tools).
- RDF (Description, Turtle/n-triples/XML syntax, RDF Schema, RDF/RDFS Semantics, Querying RDF/RDFS with SPARQL, Linked Open Data, RDF tools).
- OWL (Introduction to ontologies and OWL, Description and syntax, OWL flavors, Examples, OWL in OWL, Future extensions, OWL tools). OWL2 Presentation.
- Ontology Engineering (Ontology creation, Reusing ontologies, Semi - automatic methods).
- SW Applications. Linked Open Data.
- Logic and Inferencing (SWRL, OWL2 RL, RIF, RuleML, SPIN, SHACL rules)
Full course outline (PDF):