Efficient query answering in the presence of DL-LiteR constraints

Damian Bursztyn 1, 2 François Goasdoué 3 Ioana Manolescu 2, 1
1 CEDAR - Rich Data Analytics at Cloud Scale
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], Inria Saclay - Ile de France
3 SHAMAN - Symbolic and Human-centric view of dAta MANagement
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : In the presence of an ontology, query answers must reflect not only data explicitly present in the database, but also implicit data, which holds due to the ontology, even though it is not present in the database. A large and useful set of ontology languages enjoys FOL reducibility of query answering, that is: answering a query can be reduced to evaluating a certain first-order logic (FOL) formula (obtained from the query and ontology) against only the explicit facts. We present a novel query optimization framework for ontology-based data access settings enjoying FOL reducibility. Our framework is based on searching within a set of alternative equivalent FOL queries, i.e., FOL reformulations, one with minimal evaluation cost when evaluated through a relational database system. We apply this framework to the DL-LiteR Description Logic underpinning the W3C’s OWL2 QL ontology language, and demonstrate through experiments its performance benefits when two leading SQL systems, one open-source and one commercial, are used for evaluating the FOL query reformulations.
Document type :
Reports
Complete list of metadatas

Cited literature [37 references]  Display  Hide  Download

https://hal.inria.fr/hal-01143498
Contributor : Damian Bursztyn <>
Submitted on : Monday, August 22, 2016 - 2:34:36 PM
Last modification on : Thursday, June 13, 2019 - 11:34:02 AM

File

RR-8714.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01143498, version 4

Citation

Damian Bursztyn, François Goasdoué, Ioana Manolescu. Efficient query answering in the presence of DL-LiteR constraints. [Research Report] RR-8714, INRIA Saclay; INRIA. 2016. ⟨hal-01143498v4⟩

Share

Metrics

Record views

576

Files downloads

494