Competency Questions and SPARQL-OWL Queries Dataset and Analysis

TL;DR

This paper presents a dataset of 234 competency questions and their SPARQL-OWL formalizations across various ontologies, analyzing linguistic patterns and query signatures to improve ontology testing and development practices.

Contribution

It introduces a publicly available dataset of CQs and SPARQL-OWL queries, along with an analysis of linguistic patterns and query signatures to enhance ontology engineering methodologies.

Findings

Identified 106 distinct CQ patterns with limited overlap across ontologies.

Discovered that one CQ pattern can correspond to multiple SPARQL-OWL query signatures.

Provided a dataset to support automation and standardization in CQ formulation and formalization.

Abstract

Competency Questions (CQs) are natural language questions outlining and constraining the scope of knowledge represented by an ontology. Despite that CQs are a part of several ontology engineering methodologies, we have observed that the actual publication of CQs for the available ontologies is very limited and even scarcer is the publication of their respective formalisations in terms of, e.g., SPARQL queries. This paper aims to contribute to addressing the engineering shortcomings of using CQs in ontology development, to facilitate wider use of CQs. In order to understand the relation between CQs and the queries over the ontology to test the CQs on an ontology, we gather, analyse, and publicly release a set of 234 CQs and their translations to SPARQL-OWL for several ontologies in different domains developed by different groups. We analysed the CQs in two principal ways. The first stage focused on a linguistic analysis of the natural language text itself, i.e., a lexico-syntactic analysis without any presuppositions of ontology elements, and a subsequent step of semantic analysis in order to find patterns. This increased diversity of CQ sources resulted in a 5-fold increase of hitherto published patterns, to 106 distinct CQ patterns, which have a limited subset of few patterns shared across the CQ sets from the different ontologies. Next, we analysed the relation between the found CQ patterns and the 46 SPARQL-OWL query signatures, which revealed that one CQ pattern may be realised by more than one SPARQL-OWL query signature, and vice versa. We hope that our work will contribute to establishing common practices, templates, automation, and user tools that will support CQ formulation, formalisation, execution, and general management.