Efficient Ontology-Mediated Query Answering: Extending DL-liteR and Linear ELH
Abstract
The OWL 2 QL profile of the OWL 2 Web Ontology Language, based on the family of description logics called DL-Lite, is designed so that data stored in a standard relational database system (RDBMS) can be queried through an ontology via a rewriting mechanism, i.e., by rewriting the query into an SQL query that is then answered by the RDBMS system, without any changes to the data. In this paper we propose a language whose expressive power goes beyond that of DL-Lite while still allowing query answering via rewriting of queries into unions of conjunctive two-way regular path queries (UC2RPQs) instead of SQL queries. Our language is an extension of both OWL 2 QL and linear ELH: OWL 2 QL is extended by allowing qualified existential quantification on the left-hand side of concept inclusion axioms, and linear ELH by allowing inverses in role inclusion axioms. We identify a syntactic property of the extended language that guarantees UC2RPQ-rewritability. We propose a novel rewriting technique for conjunctive queries (CQs) under our ontology language that makes use of nondeterministic finite state automata. We show that CQ answering in our setting is NLOGSPACE-complete with respect to data complexity and NP-complete for combined complexity; we also show that answering instance queries is NLOGSPACE-complete for data complexity and in PTIME for combined complexity.
Cite
Text
Dimartino et al. "Efficient Ontology-Mediated Query Answering: Extending DL-liteR and Linear ELH." Journal of Artificial Intelligence Research, 2025. doi:10.1613/JAIR.1.16401Markdown
[Dimartino et al. "Efficient Ontology-Mediated Query Answering: Extending DL-liteR and Linear ELH." Journal of Artificial Intelligence Research, 2025.](https://mlanthology.org/jair/2025/dimartino2025jair-efficient/) doi:10.1613/JAIR.1.16401BibTeX
@article{dimartino2025jair-efficient,
title = {{Efficient Ontology-Mediated Query Answering: Extending DL-liteR and Linear ELH}},
author = {Dimartino, Mirko Michele and Wood, Peter T. and Calì, Andrea and Poulovassilis, Alexandra},
journal = {Journal of Artificial Intelligence Research},
year = {2025},
pages = {851-899},
doi = {10.1613/JAIR.1.16401},
volume = {82},
url = {https://mlanthology.org/jair/2025/dimartino2025jair-efficient/}
}