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.
- The vision of Semantic Web and Linked Data. The role of semantics and ontologies. Applications of Semantic Web Technologies.
- The Resource Description Framework (RDF and RDFS)
- The query language SPARQL
- Linked spatial and temporal data. Spatial and temporal extensions to RDF and SPARQL
- Description logics
- The Web Ontology Language (OWL)
- Ontology Engineering
- Rule languages for the Semantic Web
More info you can find here