# BigCQ: A large-scale synthetic dataset of competency question patterns formalized into SPARQL-OWL query templates

arXiv: https://arxiv.org/abs/2105.09574 · HTML: https://mlsanity.com/paper/2105.09574/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 23 references that are in the map.
- First posted on arXiv 20 May 2021.

## Builds on (most cited first, 1 of 1)

- [The African Wildlife Ontology tutorial ontologies: requirements, design, and content](https://mlsanity.com/paper/1905.09519/) (2019)

## Built on by (most cited first, 2 of 2)

- [A RAG Approach for Generating Competency Questions in Ontology Engineering](https://mlsanity.com/paper/2409.08820/) (2024)
- [Q2Forge: Minting Competency Questions and SPARQL Queries for Question-Answering Over Knowledge Graphs](https://mlsanity.com/paper/2505.13572/) (2025)

## Abstract (arXiv)

Competency Questions (CQs) are used in many ontology engineering methodologies to collect requirements and track the completeness and correctness of an ontology being constructed. Although they are frequently suggested by ontology engineering methodologies, the publicly available datasets of CQs and their formalizations in ontology query languages are very scarce. Since first efforts to automate processes utilizing CQs are being made, it is of high importance to provide large and diverse datasets to fuel these solutions. In this paper, we present BigCQ, the biggest dataset of CQ templates with their formalizations into SPARQL-OWL query templates. BigCQ is created automatically from a dataset of frequently used axiom shapes. These pairs of CQ templates and query templates can be then materialized as actual CQs and SPARQL-OWL queries if filled with resource labels and IRIs from a given ontology. We describe the dataset in detail, provide a description of the process leading to the creation of the dataset and analyze how well the dataset covers real-world examples. We also publish the dataset as well as scripts transforming axiom shapes into pairs of CQ patterns and SPARQL-OWL templates, to make engineers able to adapt the process to their particular needs.