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Ruben Verborgh

MontoloStats – Ontology Modeling Statistics

Sven Lieber, Ben De Meester, Anastasia Dimou, and Ruben Verborgh

Within ontology engineering, concepts are modeled as classes and relationships, and restrictions as axioms. Reusing ontologies requires assessing if existing ontologies are suited for an application scenario. Different scenarios not only influence concept modeling, but also the use of different restriction types, such as subclass relationships or disjointness between concepts. However, metadata about the use of such restriction types is currently unavailable, preventing accurate assessments for reuse. We created the RDF Data Cube-based dataset MontoloStats, which contains restriction use statistics for 660 LOV and 565 BioPortal ontologies.We analyze the dataset and discuss the findings and their implications for ontology reuse. The MontoloStats dataset reveals that 94% of LOV and 95% of BioPortal ontologies use RDFS-based restriction types, 49% of LOV and 52% of BioPortal ontologies use at least one OWL-based restriction type, and different literal value-related restriction types are not or barely used. Our dataset provides modeling insights, beneficial for ontology reuse to discover and compare reuse candidates, but can also be the basis of new research that investigates novel ontology engineering methodologies with respect to restrictions definition.

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Published in 2019 in Proceedings of the 10th International Conference on Knowledge Capture.

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Cite this article easily using its BibTeX entry:

@inproceedings{lieber_kcap_2019,
  author = {Lieber, Sven and De Meester, Ben and Dimou, Anastasia and Verborgh, Ruben},
  title = {{MontoloStats} -- Ontology Modeling Statistics},
  booktitle = {Proceedings of the 10th International Conference on Knowledge Capture},
  year = 2019,
  month = nov,
  publisher = {ACM},
  url = {https://biblio.ugent.be/publication/8631960/file/8631961.pdf},
}

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ACM
Sven Lieber, Ben De Meester, Anastasia Dimou, and Ruben Verborgh. 2019. MontoloStats – Ontology Modeling Statistics. In Proceedings of the 10th International Conference on Knowledge Capture, ACM.
APA
Lieber, S., De Meester, B., Dimou, A., & Verborgh, R. (2019, November). MontoloStats – Ontology Modeling Statistics. Proceedings of the 10th International Conference on Knowledge Capture.
IEEE
S. Lieber, B. De Meester, A. Dimou, and R. Verborgh, “MontoloStats – Ontology Modeling Statistics,” in Proceedings of the 10th International Conference on Knowledge Capture, 2019.
LNCS
Lieber, S., De Meester, B., Dimou, A., Verborgh, R.: MontoloStats – Ontology Modeling Statistics. In: Proceedings of the 10th International Conference on Knowledge Capture. ACM (2019).
MLA
Lieber, Sven, et al. “MontoloStats – Ontology Modeling Statistics.” Proceedings of the 10th International Conference on Knowledge Capture, ACM, 2019.

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