SeeQuery: An Automatic Method for Recommending Translations of Ontology Competency Questions into SPARQL-OWL

Abstract

Ontology authoring is a complicated and error-prone process since the knowledge being modeled is expressed using logic-based formalisms, in which logical consequences of the knowledge have to be foreseen. To make that process easier, competency questions (CQs), being questions expressed in natural language are often stated to trace both the correctness and completeness of the ontology at a given time. However, CQs have to be translated into a formal language, like ontology query language (SPARQL-OWL), to query the ontology. Since the translation step is time-consuming and requires familiarity with the query language used, in this paper, we propose an automatic method named SeeQuery, which recommends SPARQL-OWL queries being translations of CQs stated against a given ontology. It consists of a pipeline of transformations based on template matching and filling, being motivated by the biggest to date publicly available CQ to SPARQL-OWL datasets. We provide a detailed description of SeeQuery and evaluate the method on a separate set of 2 ontologies with their CQs. It is, to date, the only automatic method available for recommending SPARQL-OWL queries out of CQs. The source code of SeeQuery is available at: https://github.com/dwisniewski/SeeQuery.