Relaxing and Restraining Queries for OBDA

TL;DR

This paper introduces methods for relaxing and restraining queries in ontology-based data access, leveraging complex role inclusions and dataset patterns to improve query flexibility and precision.

Contribution

It extends DL-Lite with complex role inclusions ensuring FO rewritability and proposes rules for query relaxation and restriction based on ontologies and dataset patterns.

Findings

Extended DL-Lite with CRI maintains FO rewritability.

Proposed rules enable flexible query modifications.

Dataset-driven rules allow fine-grained query adjustments.

Abstract

In ontology-based data access (OBDA), ontologies have been successfully employed for querying possibly unstructured and incomplete data. In this paper, we advocate using ontologies not only to formulate queries and compute their answers, but also for modifying queries by relaxing or restraining them, so that they can retrieve either more or less answers over a given dataset. Towards this goal, we first illustrate that some domain knowledge that could be naturally leveraged in OBDA can be expressed using complex role inclusions (CRI). Queries over ontologies with CRI are not first-order (FO) rewritable in general. We propose an extension of DL-Lite with CRI, and show that conjunctive queries over ontologies in this extension are FO rewritable. Our main contribution is a set of rules to relax and restrain conjunctive queries (CQs). Firstly, we define rules that use the ontology to produce CQs that are relaxations/restrictions over any dataset. Secondly, we introduce a set of data-driven rules, that leverage patterns in the current dataset, to obtain more fine-grained relaxations and restrictions.