Towards metrics-driven ontology engineering

Abstract

The software engineering field is continuously making an effort to improve the effectiveness of the software development process. This improvement is performed by developing quantitative measures that can be used to enhance the quality of software products and to more accurately describe, better understand and manage the software development life cycle. Even if the ontology engineering field is constantly adopting practices from software engineering, it has not yet reached a state in which metrics are an integral part of ontology engineering processes and support making evidence-based decisions over the process and its outputs. Up to now, ontology metrics are mainly focused on the ontology implementation and do not take into account the development process or other artefacts that can help assessing the quality of the ontology, e.g. its requirements. This work envisions the need for a metrics-driven ontology engineering process and, as a first step, presents a set of metrics for ontology engineering which are obtained from artefacts generated during the ontology development process and from the process itself. The approach is validated by measuring the ontology engineering process carried out in a research project and by showing how the proposed metrics can be used to improve the efficiency of the process by making predictions, such as the effort needed to implement an ontology, or assessments, such as the coverage of the ontology according to its requirements.

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Notes

  1. 1.

    https://protege.stanford.edu/.

  2. 2.

    https://webprotege.stanford.edu/.

  3. 3.

    The authors of the analysed paper refer to the knowledge base as the set of TBox and Abox.

  4. 4.

    https://github.com/.

  5. 5.

    https://www.w3.org/TR/rdf-sparql-query/.

  6. 6.

    http://vicinity2020.eu/vicinity/.

  7. 7.

    http://iot.linkeddata.es/def/core/.

  8. 8.

    http://iot.linkeddata.es/def/wot/.

  9. 9.

    http://iot.linkeddata.es/def/wot-mappings/.

  10. 10.

    http://iot.linkeddata.es/def/adapters/.

  11. 11.

    http://iot.linkeddata.es/def/datatypes/.

  12. 12.

    https://www.w3.org/WoT/WG/.

  13. 13.

    http://vicinity.iot.linkeddata.es.

  14. 14.

    The link to all the Github repositories are indicated in the VICINITY ontology portal: http://vicinity.iot.linkeddata.es/ which due to its version control allows the ontology engineers to be aware of the evolution of the artefacts during the development iterations. Test suites are also stored in the GitHub repository of its associated ontology.

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Acknowledgements

This work is partially supported by the H2020 project VICINITY: Open virtual neighbourhood network to connect intelligent buildings and smart objects (H2020-688467) and by a Predoctoral grant from the I+D+i program of the Universidad Politécnica de Madrid. We are very grateful to María Navas-Loro for her formula revisions and comments.

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Correspondence to Alba Fernández-Izquierdo.

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Fernández-Izquierdo, A., Poveda-Villalón, M., Gómez-Pérez, A. et al. Towards metrics-driven ontology engineering. Knowl Inf Syst (2021). https://doi.org/10.1007/s10115-021-01545-9

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Keywords

  • Metrics
  • Ontology engineering
  • Requirements
  • Ontology development