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Semantic Technologies

Semantic Technologies are a family of recently emerged technologies particularly well suited for managing and sharing large volumes of heterogeneous, rapidly evolving data. This course is an introductory course covering the Semantic Web languages RDF(S), OWL, and SPARQL. The course is a combination of lectures covering both practical and theoretic aspects of the aforementioned languages and extensive hands-on sessions on modelling and querying semantic knowledge bases. The book ``A Semantic Web Primer'' by Frank van Harmelen and his group will be used as a course text book. In our hands-on sessions, we use the ontology editor Protege and the SPARQL query engine StarDog.


This subject has been discontinued; no further courses are planned.


By the end of the course, students are expected to have acquired the following skills:

  • Solid understanding of capabilities and  limitations of RDF(S), OWL and SPARQL
  • Ability to effectively apply those languages to model relevant aspects of the domain and query semantic knowledge bases
  • Ability to keep track of  the consequences of modeling decisions and to determine modeling alternatives that enable effective querying of the corresponding knowledge base
  • Awareness of the trade-off between the expressivity of modeling languages and the computational efficiency of querying


Resource Description Framework

  • General idea of graph-based data representation and core concepts 

  • Terse RDF Triple Language

  • Advanced RDF features

  • Advice on publishing RDF data

RDF Schema (RDFS)

  • Discussion of the added value of a schema driven by examples

  • Syntax and semantics of the core features: classes, properties and their

  • characteristics

  • Relationships between RDFS vocabulary elements

  • Computing answers to typical queries over RDFS datasets

  • RDFS Satisfiability and Entailment

  • Using Protege for modeling and querying RDFS datasets

  • Limitations of RDFS

Querying Semantic Web with SPARQL

  • Core concepts

  • Basic graph patterns

  • Querying datasets with the SPARQL engine StarDog

  • Filters and SPARQL expressions

  • Property path expressions

  • Complex graph patterns with advanced features such as optional parts, aggregation and ordering

  • Other query types

  • Updating with SPARQL

OWL Web Ontology Language
  • Core concepts and differences to RDFS

  • Overview of OWL modeling constructs

  • Modeling and assessing the benefits of alternative models in a particular application context

  • Substitutability of modeling constructs

  • Discussion of the trade-off between the expressivity of modeling lan-

    guages and the computational efficiency of querying

  • OWL profiles

  • Limitations of the expressive power of OWL