BigCQ: Generating a Synthetic Set of Competency Questions Formalized into SPARQL-OWL (Student Abstract)

Authors

  • Dawid Wiśniewski Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 3A, Poznan, Poland 60-965
  • Jędrzej Potoniec Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 3A, Poznan, Poland 60-965 CAMIL Center for Artificial Intelligence and Machine Learning, Piotrowo 3A, Poznan, Poland 60-965
  • Agnieszka Ławrynowicz Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 3A, Poznan, Poland 60-965 CAMIL Center for Artificial Intelligence and Machine Learning, Piotrowo 3A, Poznan, Poland 60-965

DOI:

https://doi.org/10.1609/aaai.v36i11.21676

Keywords:

SPARQL-OWL, Competency Questions, Ontology Requirements, SPARQL, Ontology Development, Template-based Method, Dataset, Synthetic Dataset, Automated Quality Assessment

Abstract

We present a method for constructing synthetic datasets of Competency Questions translated into SPARQL-OWL queries. This method is used to generate BigCQ, the largest set of CQ patterns and SPARQL-OWL templates that can provide translation examples to automate assessing the completeness and correctness of ontologies.
AAAI-22 Proceedings Cover

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Published

2022-06-28

How to Cite

Wiśniewski, D., Potoniec, J., & Ławrynowicz, A. (2022). BigCQ: Generating a Synthetic Set of Competency Questions Formalized into SPARQL-OWL (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13079-13080. https://doi.org/10.1609/aaai.v36i11.21676

Issue

Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Section

AAAI Student Abstract and Poster Program