Querying Rich Ontologies by Exploiting the Structure of Data
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DISSERTATION AND HABILITATION ABSTRACTS
Querying Rich Ontologies by Exploiting the Structure of Data Labinot Bajraktari1 Received: 22 December 2019 / Accepted: 28 May 2020 © The Author(s) 2020
Abstract 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. Keywords Knowledge representation · Description logics · Ontologies · Query answering
1 Introduction Managing and acquiring knowledge from today’s data-bases is a complicated endeavor for organizations, in large part due to the limited semantics of the stored data. To remedy the situation one can use description logics (DL)—a family of ontological languages with rich modeling features that can be used effectively for representing knowledge. The ontology-based data access (OBDA) [1] paradigm has emerged as a way of managing and integrating traditional data sources using ontologies to add knowledge modeling and inferential capabilities on top of databases. An essential reasoning service in OBDA and the core subject of the doctoral dissertation [2] is the ontology mediated query (OMQ) answering. OMQ answering has received much attention in the last decade, and there exist quite some practical algorithms implemented in resonsers for the cases where ontology uses simpler features to express the knowledge. However for expressive ontologies, particularly for those that use the disjunctive operator, the work has been mainly foundational and theoretical. In the doctoral dissertation, we study a more feasible approach for OMQ in the setting of expressive ontologies, which utilizes the structure * Labinot Bajraktari [email protected] 1
Institute of Logic and Computation, Favoritenstraße 11, 1040 Wien, Austria
of data (ABox in DL jargon) for ‘guiding’ the reasoning of query answering algorithms. We propose a generic description of the structure of ABoxes, and use it for obatining scalable algorithms for answering OMQs in expressive setting. More specifically we use the knowledge about the structure of ABoxes of interest to obtain a more goal-oriented reasoning procedure for an expressive DL ( ALCHI ) for a broad range of queries. We also extend our approach to hybrid languages which combine ontologies and rules. Moreover, we show the potential of adopting our apporach to optimize existing a
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