research-article

Optimizing query rewriting in ontology-based data access

Authors:

Floriana Di Pinto,

Domenico Lembo,

Maurizio Lenzerini,

Riccardo Mancini,

Antonella Poggi,

Riccardo Rosati,

Marco Ruzzi, and

Domenico Fabio SavoAuthors Info & Claims

EDBT '13: Proceedings of the 16th International Conference on Extending Database Technology

March 2013

Pages 561 - 572

https://doi.org/10.1145/2452376.2452441

Published: 18 March 2013 Publication History

Abstract

In ontology-based data access (OBDA), an ontology is connected to autonomous, and generally pre-existing, data repositories through mappings, so as to provide a high-level, conceptual view over such data. User queries are posed over the ontology, and answers are computed by reasoning both on the ontology and the mappings. Query answering in OBDA systems is typically performed through a query rewriting approach which is divided into two steps: (i) the query is rewritten with respect to the ontology (ontology rewriting of the query); (ii) the query thus obtained is then reformulated over the database schema using the mapping assertions (mapping rewriting of the query). In this paper we present a new approach to the optimization of query rewriting in OBDA. The key ideas of our approach are the usage of inclusion between mapping views and the usage of perfect mappings, which allow us to drastically lower the combinatorial explosion due to mapping rewriting. These ideas are formalized in PerfectMap, an algorithm for OBDA query rewriting. We have experimented PerfectMap in a real-world OBDA scenario: our experimental results clearly show that, in such a scenario, the optimizations of PerfectMap are crucial to effectively perform query answering.

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Cited By

Thapa RGiese M(2023)Optimizing SPARQL Queries with SHACLThe Semantic Web – ISWC 202310.1007/978-3-031-47240-4_3(41-60)Online publication date: 27-Oct-2023
https://doi.org/10.1007/978-3-031-47240-4_3
Ren XRen KXu ZLi XZhou ASong JDeng K(2021)Improving Ocean Data Services with Semantics and Quick IndexJournal of Computer Science and Technology10.1007/s11390-021-1374-036:5(963-984)Online publication date: 30-Sep-2021
https://doi.org/10.1007/s11390-021-1374-0
Toman DWeddell G(2020)Using Feature-Based Description Logics to avoid Duplicate Elimination in Object-Relational Query LanguagesKI - Künstliche Intelligenz10.1007/s13218-020-00666-7Online publication date: 17-Jul-2020
https://doi.org/10.1007/s13218-020-00666-7
Show More Cited By

Index Terms

Optimizing query rewriting in ontology-based data access
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
      2. Database transaction processing
    2. Query languages
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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cover image ACM Other conferences

EDBT '13: Proceedings of the 16th International Conference on Extending Database Technology

March 2013

793 pages

ISBN:9781450315975

DOI:10.1145/2452376

General Chair:
Giovanna Guerrini
Università di Genova, Italy
,
Program Chair:
Norman W. Paton
University of Manchester, UK

Copyright © 2013 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 March 2013

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Seventh Framework Programme

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EDBT/ICDT '13

EDBT/ICDT '13: Joint 2013 EDBT/ICDT Conferences

March 18 - 22, 2013

Genoa, Italy

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Overall Acceptance Rate 7 of 10 submissions, 70%

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Cited By

Thapa RGiese M(2023)Optimizing SPARQL Queries with SHACLThe Semantic Web – ISWC 202310.1007/978-3-031-47240-4_3(41-60)Online publication date: 27-Oct-2023
https://doi.org/10.1007/978-3-031-47240-4_3
Ren XRen KXu ZLi XZhou ASong JDeng K(2021)Improving Ocean Data Services with Semantics and Quick IndexJournal of Computer Science and Technology10.1007/s11390-021-1374-036:5(963-984)Online publication date: 30-Sep-2021
https://doi.org/10.1007/s11390-021-1374-0
Toman DWeddell G(2020)Using Feature-Based Description Logics to avoid Duplicate Elimination in Object-Relational Query LanguagesKI - Künstliche Intelligenz10.1007/s13218-020-00666-7Online publication date: 17-Jul-2020
https://doi.org/10.1007/s13218-020-00666-7
Lanti DXiao GCalvanese DNgonga Ngomo AFundulaki IKrithara A(2019)VIGSemantic Web10.3233/SW-18033610:2(413-433)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.3233/SW-180336
Xiao GDing LCogrel BCalvanese D(2019)Virtual Knowledge Graphs: An Overview of Systems and Use CasesData Intelligence10.1162/dint_a_000111:2(201-223)Online publication date: May-2019
https://doi.org/10.1162/dint_a_00011
Cavallo GDi Mauro FPasteris PSapino MCandan K(2019)Crowd Sourced Semantic Enrichment (CroSSE) for knowledge driven querying of digital resourcesJournal of Intelligent Information Systems10.1007/s10844-019-00559-8Online publication date: 25-Jul-2019
https://doi.org/10.1007/s10844-019-00559-8
Xiao GCalvanese DKontchakov RLembo DPoggi ARosati RZakharyaschev M(2018)Ontology-based data accessProceedings of the 27th International Joint Conference on Artificial Intelligence10.5555/3304652.3304791(5511-5519)Online publication date: 13-Jul-2018
https://dl.acm.org/doi/10.5555/3304652.3304791
Cavallo GDi Mauro FPasteris PSapino MCandan K(2018)Contextually-Enriched Querying of Integrated Data Sources2018 IEEE 34th International Conference on Data Engineering Workshops (ICDEW)10.1109/ICDEW.2018.00008(9-16)Online publication date: Apr-2018
https://doi.org/10.1109/ICDEW.2018.00008
Bienvenu MKikot SKontchakov RPodolskii VRyzhikov VZakharyaschev MSallinger EVan den Bussche JGeerts F(2017)The Complexity of Ontology-Based Data Access with OWL 2 QL and Bounded Treewidth QueriesProceedings of the 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3034786.3034791(201-216)Online publication date: 9-May-2017
https://dl.acm.org/doi/10.1145/3034786.3034791
Lanti DXiao GCalvanese D(2017)Cost-Driven Ontology-Based Data AccessThe Semantic Web – ISWC 201710.1007/978-3-319-68288-4_27(452-470)Online publication date: 4-Oct-2017
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