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General Information
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.
Course Material
-
Introduction to Knowledge Graphs, the Semantic Web and Linked Data.
-
The Resource Description Framework (RDF, RDFS, RDF*)
-
Shapes Constraint Language (SHACL)
-
The query language SPARQL, SPARQL Formalization
-
Description logics, tableaux techniques
-
The Web Ontology
Language (OWL)
-
Ontology Engineering
-
Rule languages for the
Semantic Web
-
A Data Science Pipeline for Big Linked Earth Observation Data, Discovering Earth Observation Data
-
Linked spatial and temporal data. Spatial and temporal extensions to RDF and SPARQL
-
Transforming geospatial data into RDF
-
YAGO2geo & Geospatial Question Answering
Marking Scheme
-
Three assignments that will include theoretical problem solving and software development.
Bibliography
Main Bibliography:
Other Related Sources:
- Tom
Heath and Christian Bizer. 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, 2011. Book website
- Glen Hart and Catherine Dolbear. Linked Data: A Geographic Perspective. CRC Press, 2013. Book website
-
Dean Allemang and James Hendler. SEMANTIC WEB FOR THE WORKING ONTOLOGIST: Effective Modeling in RDFS and OWL. Elsevier Science & Technology Books, May 2008. Book
website
-
Heiner Stuckenschmidt
and Frank van Harmelen. Information Sharing on the Semantic Web.
Springer, 2005.
-
Asunción Gomez-Perez,
Mariano Fernandez-Lopez and Oscar Corcho.
Ontological Engineering:
With Examples from the Areas of Knowledge Management, E-Commerce and
the Semantic Web, 2nd edition, Springer, 2007.
-
John Davies, Dieter
Fensel, Frank van Harmelen and Frank van Harmelen (editors).
Towards the Semantic
Web: Ontology-Driven Knowledge Management. John-Wiley, 2003.
-
John Davies, Rudi Studer
and Paul Warren (editors). Semantic Web Technologies: Trends and
Research in Ontology-based Systems: Trends and Research.
John-Wiley, 2006.
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