Towards metrics-driven ontology engineering

Fernández-Izquierdo, Alba and Poveda-Villalón, María and Gómez-Pérez, A. and García-Castro, Raúl (2021). Towards metrics-driven ontology engineering. "Knowledge and Information Systems", v. 63 (n. 4); pp. 867-903. ISSN 0219-1377.


Title: Towards metrics-driven ontology engineering
  • Fernández-Izquierdo, Alba
  • Poveda-Villalón, María
  • Gómez-Pérez, A.
  • García-Castro, Raúl
Item Type: Article
Título de Revista/Publicación: Knowledge and Information Systems
Date: April 2021
ISSN: 0219-1377
Volume: 63
Freetext Keywords: · Ontology engineering; Requirements; Ontology development
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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.

Funding Projects

Horizon 2020688467UnspecifiedUnspecifiedProject VICINITY:: Open virtual neighbourhood network to connect intelligent buildings and smart objects

More information

Item ID: 72403
DC Identifier:
OAI Identifier:
DOI: 10.1007/s10115-021-01545-9
Official URL:
Deposited by: Biblioteca Facultad de Informatica
Deposited on: 19 Jan 2023 10:10
Last Modified: 19 Jan 2023 10:11
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