Künstliche Intelligenz 34(3) - September 2020

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Zeitschriftenartikel
Querying Rich Ontologies by Exploiting the Structure of Data
(KI - Künstliche Intelligenz: Vol. 34, No. 3, 2020) Bajraktari, Labinot
Ontology-based data access (OBDA) has emerged as a paradigm for accessing heterogeneous and incomplete data sources. A fundamental reasoning service in OBDA, the ontology mediated query (OMQ) answering has received much attention from the research community. However, there exists a disparity in research carried for OMQ algorithms for lightweight DLs which have found their way into practical implementations, and algorithms for expressive DLs for which the work has had mainly theoretical oriented goals. In the dissertation, a technique that leverages the structural properties of data to help alleviate the problems that typically arise when answering the queries in expressive settings is developed. In this paper, a brief summary of the technique along with the different algorithms developed for OMQ for expressive DLs is given.