Ontology Quality Evaluation Methodology

R. Shyama I. Wilson; Jeevani S. Goonetillake; Athula Ginige; Anusha Walisadeera

doi:10.1007/978-3-031-10522-7_35

Ontology Quality Evaluation Methodology

R. Shyama I. Wilson, Jeevani S. Goonetillake, Athula Ginige, Anusha Walisadeera

School of Computer, Data & Mathematical Sciences

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

5 Citations (Scopus)

Abstract

Lack of methodologies for ontology quality evaluation causes a challenge in producing good quality ontologies. Thus, we developed an iterative quality methodology to address this gap by analyzing the existing quality theories defined in ontology engineering, as well as, the theories in software engineering. Accordingly, this paper presents the developed methodology including how the other ontology quality theories get associated with it. Moreover, a use case in the agriculture domain has been demonstrated in order to provide an understanding of how the methodology can be applied in a real context. In the future, many experiments are expected to be carried out to fine-tune the methodology and to illustrate its usefulness.

Original language	English
Title of host publication	Computational Science and Its Applications - ICCSA 2022 - 22nd International Conference, Proceedings
Editors	Osvaldo Gervasi, Beniamino Murgante, Eligius M. Hendrix, David Taniar, Bernady O. Apduhan
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	509-528
Number of pages	20
ISBN (Print)	9783031105210
DOIs	https://doi.org/10.1007/978-3-031-10522-7_35
Publication status	Published - 2022
Event	22nd International Conference on Computational Science and Its Applications, ICCSA 2022 - Malaga, Spain Duration: 4 Jul 2022 → 7 Jul 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13375 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Computational Science and Its Applications, ICCSA 2022
Country/Territory	Spain
City	Malaga
Period	4/07/22 → 7/07/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Agriculture
Ontology
Ontology quality
Quality evaluation

Access to Document

10.1007/978-3-031-10522-7_35

Cite this

Wilson, R. S. I., Goonetillake, J. S., Ginige, A., & Walisadeera, A. (2022). Ontology Quality Evaluation Methodology. In O. Gervasi, B. Murgante, E. M. Hendrix, D. Taniar, & B. O. Apduhan (Eds.), Computational Science and Its Applications - ICCSA 2022 - 22nd International Conference, Proceedings (pp. 509-528). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13375 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-10522-7_35

Wilson, R. Shyama I. ; Goonetillake, Jeevani S. ; Ginige, Athula et al. / Ontology Quality Evaluation Methodology. Computational Science and Its Applications - ICCSA 2022 - 22nd International Conference, Proceedings. editor / Osvaldo Gervasi ; Beniamino Murgante ; Eligius M. Hendrix ; David Taniar ; Bernady O. Apduhan. Springer Science and Business Media Deutschland GmbH, 2022. pp. 509-528 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Wilson, RSI, Goonetillake, JS, Ginige, A & Walisadeera, A 2022, Ontology Quality Evaluation Methodology. in O Gervasi, B Murgante, EM Hendrix, D Taniar & BO Apduhan (eds), Computational Science and Its Applications - ICCSA 2022 - 22nd International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13375 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 509-528, 22nd International Conference on Computational Science and Its Applications, ICCSA 2022, Malaga, Spain, 4/07/22. https://doi.org/10.1007/978-3-031-10522-7_35

Ontology Quality Evaluation Methodology. / Wilson, R. Shyama I.; Goonetillake, Jeevani S.; Ginige, Athula et al.
Computational Science and Its Applications - ICCSA 2022 - 22nd International Conference, Proceedings. ed. / Osvaldo Gervasi; Beniamino Murgante; Eligius M. Hendrix; David Taniar; Bernady O. Apduhan. Springer Science and Business Media Deutschland GmbH, 2022. p. 509-528 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13375 LNCS).

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

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T1 - Ontology Quality Evaluation Methodology

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AU - Goonetillake, Jeevani S.

AU - Ginige, Athula

AU - Walisadeera, Anusha

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AB - Lack of methodologies for ontology quality evaluation causes a challenge in producing good quality ontologies. Thus, we developed an iterative quality methodology to address this gap by analyzing the existing quality theories defined in ontology engineering, as well as, the theories in software engineering. Accordingly, this paper presents the developed methodology including how the other ontology quality theories get associated with it. Moreover, a use case in the agriculture domain has been demonstrated in order to provide an understanding of how the methodology can be applied in a real context. In the future, many experiments are expected to be carried out to fine-tune the methodology and to illustrate its usefulness.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Wilson RSI, Goonetillake JS, Ginige A, Walisadeera A. Ontology Quality Evaluation Methodology. In Gervasi O, Murgante B, Hendrix EM, Taniar D, Apduhan BO, editors, Computational Science and Its Applications - ICCSA 2022 - 22nd International Conference, Proceedings. Springer Science and Business Media Deutschland GmbH. 2022. p. 509-528. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-10522-7_35

Ontology Quality Evaluation Methodology

Abstract

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Keywords

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