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    Advanced processing for ontological queries

    Calì, Andrea and Gottlob, G. and Pieris, A. (2010) Advanced processing for ontological queries. In: UNSPECIFIED (ed.) 36th International Conference on Very Large Data Bases 2010 (VLDB 2010), Singapore, 13-17 September 2010. Proceedings of the VLDB Endowment 3. New York, U.S.: Association for Computing Machinery, pp. 554-565. ISBN 9781617820373.

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    Abstract

    Ontology-based data access is a powerful form of extending database technology, where a classical extensional database (EDB) is enhanced by an ontology that generates new inten- sional knowledge which may contribute to answer a query. The ontological integrity constraints for generating this intensional knowledge can be specified in description logics such as DL-Lite. It was recently shown that these formalisms allow for very efficient query-answering. They are, however, too weak to express simple and useful integrity constraints that involve joins. In this paper we introduce a more expressive formalism that takes joins into account, while still enjoying the same low query-answering complex- ity. In our framework, ontological constraints are expressed by sets of rules that are so-called tuple-generating dependencies (TGDs). We propose the language of sticky sets of TGDs, which are sets of TGDs with a restriction on multiple occurrences of variables (including joins) in the rule bodies. We establish complexity results for answering conjunctive queries under sticky sets of TGDs, showing, in particular, that ontological conjunctive queries can be compiled into first-order and thus SQL queries over the given EDB instance. We also show how sticky sets of TGDs can be combined with functional dependencies. In summary, we obtain a highly expressive and effective ontological modeling language that unifies and generalizes both classical database constraints and important features of the most widespread tractable description logics.

    Metadata

    Item Type: Book Section
    Additional Information: Series ISSN: 2150-8097
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Sarah Hall
    Date Deposited: 10 May 2013 09:38
    Last Modified: 02 Dec 2016 13:22
    URI: https://eprints.bbk.ac.uk/id/eprint/6686

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