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