Ontology Engineering and Ontological Data Access

In artificial intelligence, ontologies are used to capture the knowledge of an application domain. They constitute a core component of `intelligent' systems and also play an important role in querying data that is incomplete and heterogeneous, arising in prominent applications such as web data extraction and data integration. In this lecture series, I start with an introduction to ontologies and to description logics as a widely used class of ontology languages, illustrating some basic reasoning problems and techniques, and discussing computational complexity pitfalls. I will then add data to the picture, introducing the central notion of an ontology-mediated query (OMQ), that is, the combination of a traditional database query with an ontology. I survey fundamental properties of OMQs such as their complexity, expressive power, descriptive strength, and rewritability into traditional query languages such as SQL and Datalog. A central observation is that there is a close and fruitful connection between OMQs and constraint satisfaction problems (CSPs) as well as related fragments of monadic NP, which puts OMQs into a more general perspective and gives raise to a number of interesting results.

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