Ontological queries: Rewriting and optimization
Ontological queries are evaluated against an enterprise ontology rather than directly on a database. The evaluation and optimization of such queries is an intriguing new problem for database research. In this paper we discuss two important aspects of this problem: query rewriting and query optimizat...
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| Format: | Conference item |
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2011
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| _version_ | 1826262948865114112 |
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| author | Gottlob, G Orsi, G Pieris, A |
| author_facet | Gottlob, G Orsi, G Pieris, A |
| author_sort | Gottlob, G |
| collection | OXFORD |
| description | Ontological queries are evaluated against an enterprise ontology rather than directly on a database. The evaluation and optimization of such queries is an intriguing new problem for database research. In this paper we discuss two important aspects of this problem: query rewriting and query optimization. Query rewriting consists of the compilation of an ontological query into an equivalent query against the underlying relational database. The focus here is on soundness and completeness. We review previous results and present a new rewriting algorithm for rather general types of ontological constraints (description logics). In particular, we show how a conjunctive query (CQ) against an enterprise ontology can be compiled into a union of conjunctive queries (UCQ) against the underlying database. Ontological query optimization, in this context, attempts to improve this process so to produce possibly small and cost-effective output UCQ. We review existing optimization methods, and propose an effective new method that works for Linear Datalog+/-, a description logic that encompasses well-known description logics of the DL-Lite family. |
| first_indexed | 2024-03-06T19:43:54Z |
| format | Conference item |
| id | oxford-uuid:219cada6-dd68-44f9-be3c-8eea5ad02523 |
| institution | University of Oxford |
| last_indexed | 2024-03-06T19:43:54Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | oxford-uuid:219cada6-dd68-44f9-be3c-8eea5ad025232022-03-26T11:34:19ZOntological queries: Rewriting and optimizationConference itemhttp://purl.org/coar/resource_type/c_5794uuid:219cada6-dd68-44f9-be3c-8eea5ad02523Department of Computer Science2011Gottlob, GOrsi, GPieris, AOntological queries are evaluated against an enterprise ontology rather than directly on a database. The evaluation and optimization of such queries is an intriguing new problem for database research. In this paper we discuss two important aspects of this problem: query rewriting and query optimization. Query rewriting consists of the compilation of an ontological query into an equivalent query against the underlying relational database. The focus here is on soundness and completeness. We review previous results and present a new rewriting algorithm for rather general types of ontological constraints (description logics). In particular, we show how a conjunctive query (CQ) against an enterprise ontology can be compiled into a union of conjunctive queries (UCQ) against the underlying database. Ontological query optimization, in this context, attempts to improve this process so to produce possibly small and cost-effective output UCQ. We review existing optimization methods, and propose an effective new method that works for Linear Datalog+/-, a description logic that encompasses well-known description logics of the DL-Lite family. |
| spellingShingle | Gottlob, G Orsi, G Pieris, A Ontological queries: Rewriting and optimization |
| title | Ontological queries: Rewriting and optimization |
| title_full | Ontological queries: Rewriting and optimization |
| title_fullStr | Ontological queries: Rewriting and optimization |
| title_full_unstemmed | Ontological queries: Rewriting and optimization |
| title_short | Ontological queries: Rewriting and optimization |
| title_sort | ontological queries rewriting and optimization |
| work_keys_str_mv | AT gottlobg ontologicalqueriesrewritingandoptimization AT orsig ontologicalqueriesrewritingandoptimization AT pierisa ontologicalqueriesrewritingandoptimization |