Maintaining the quality of evolving ontologies in the agriculture domain: challenges and a specialised evaluation tool

Shyama Wilson; Athula Ginige; Jeevani Goonetillake

doi:10.1007/978-3-031-64608-9_18

Maintaining the quality of evolving ontologies in the agriculture domain: challenges and a specialised evaluation tool

Shyama Wilson, Athula Ginige, Jeevani Goonetillake

School of Computer, Data and Mathematical Sciences

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

Abstract

The development of well-engineered quality ontologies is crucial to ensure capabilities of ontologies such as enhanced communication, knowledge reuse, and knowledge analytical capabilities. Ontology engineers conduct comprehensive evaluations to ensure ontology quality by utilising multiple tools and approaches. However, the ontology evaluators encountered challenges in choosing appropriate evaluation tools and approaches, especially in the context of a decision support system where knowledge accuracy, completeness and relevancy are highly required. This study discusses the challenges encountered when assessing ontology quality, primarily considering the agriculture domain and highlights anomalies in the existing evaluation tools. Consequently, the study developed a tool which addresses the identified limitations in the existing tools. This tool includes measures for assessing crucial quality characteristics related to agriculture ontologies, such as complexity, completeness, consistency, modularity, and comprehensibility. Further, it supports developers in gaining valuable insights to mitigate the issues associated with these key quality characteristics of ontologies.

Original language	English
Title of host publication	Computational Science and Its Applications – ICCSA 2024: 24th International Conference, Hanoi, Vietnam, July 1–4, 2024, Proceedings, Part II
Editors	Osvaldo Gervasi, Beniamino Murgante, Chiara Garau, David Taniar, Ana Maria A. C. Rocha, Maria Noelia Faginas Lago
Place of Publication	Switzerland
Publisher	Springer
Pages	273-292
Number of pages	20
ISBN (Electronic)	9783031646089
ISBN (Print)	9783031646072
DOIs	https://doi.org/10.1007/978-3-031-64608-9_18
Publication status	Published - 2024
Event	International Conference on Computational Science and Its Applications - Hanoi, Viet Nam Duration: 1 Jul 2024 → 4 Jul 2024 Conference number: 24th

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14814 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Computational Science and Its Applications
Abbreviated title	ICCSA
Country/Territory	Viet Nam
City	Hanoi
Period	1/07/24 → 4/07/24

Keywords

Agriculture
Ontology Evaluation
Quality Characteristics

Access to Document

10.1007/978-3-031-64608-9_18

Cite this

Wilson, S., Ginige, A., & Goonetillake, J. (2024). Maintaining the quality of evolving ontologies in the agriculture domain: challenges and a specialised evaluation tool. In O. Gervasi, B. Murgante, C. Garau, D. Taniar, A. M. A. C. Rocha, & M. N. Faginas Lago (Eds.), Computational Science and Its Applications – ICCSA 2024: 24th International Conference, Hanoi, Vietnam, July 1–4, 2024, Proceedings, Part II (pp. 273-292). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14814 LNCS). Springer. https://doi.org/10.1007/978-3-031-64608-9_18

Wilson, Shyama ; Ginige, Athula ; Goonetillake, Jeevani. / Maintaining the quality of evolving ontologies in the agriculture domain : challenges and a specialised evaluation tool. Computational Science and Its Applications – ICCSA 2024: 24th International Conference, Hanoi, Vietnam, July 1–4, 2024, Proceedings, Part II. editor / Osvaldo Gervasi ; Beniamino Murgante ; Chiara Garau ; David Taniar ; Ana Maria A. C. Rocha ; Maria Noelia Faginas Lago. Switzerland : Springer, 2024. pp. 273-292 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The development of well-engineered quality ontologies is crucial to ensure capabilities of ontologies such as enhanced communication, knowledge reuse, and knowledge analytical capabilities. Ontology engineers conduct comprehensive evaluations to ensure ontology quality by utilising multiple tools and approaches. However, the ontology evaluators encountered challenges in choosing appropriate evaluation tools and approaches, especially in the context of a decision support system where knowledge accuracy, completeness and relevancy are highly required. This study discusses the challenges encountered when assessing ontology quality, primarily considering the agriculture domain and highlights anomalies in the existing evaluation tools. Consequently, the study developed a tool which addresses the identified limitations in the existing tools. This tool includes measures for assessing crucial quality characteristics related to agriculture ontologies, such as complexity, completeness, consistency, modularity, and comprehensibility. Further, it supports developers in gaining valuable insights to mitigate the issues associated with these key quality characteristics of ontologies.",

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Wilson, S, Ginige, A & Goonetillake, J 2024, Maintaining the quality of evolving ontologies in the agriculture domain: challenges and a specialised evaluation tool. in O Gervasi, B Murgante, C Garau, D Taniar, AMA C. Rocha & MN Faginas Lago (eds), Computational Science and Its Applications – ICCSA 2024: 24th International Conference, Hanoi, Vietnam, July 1–4, 2024, Proceedings, Part II. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14814 LNCS, Springer, Switzerland, pp. 273-292, International Conference on Computational Science and Its Applications, Hanoi, Viet Nam, 1/07/24. https://doi.org/10.1007/978-3-031-64608-9_18

Maintaining the quality of evolving ontologies in the agriculture domain: challenges and a specialised evaluation tool. / Wilson, Shyama; Ginige, Athula; Goonetillake, Jeevani.
Computational Science and Its Applications – ICCSA 2024: 24th International Conference, Hanoi, Vietnam, July 1–4, 2024, Proceedings, Part II. ed. / Osvaldo Gervasi; Beniamino Murgante; Chiara Garau; David Taniar; Ana Maria A. C. Rocha; Maria Noelia Faginas Lago. Switzerland: Springer, 2024. p. 273-292 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14814 LNCS).

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

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T2 - International Conference on Computational Science and Its Applications

AU - Wilson, Shyama

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AU - Goonetillake, Jeevani

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N2 - The development of well-engineered quality ontologies is crucial to ensure capabilities of ontologies such as enhanced communication, knowledge reuse, and knowledge analytical capabilities. Ontology engineers conduct comprehensive evaluations to ensure ontology quality by utilising multiple tools and approaches. However, the ontology evaluators encountered challenges in choosing appropriate evaluation tools and approaches, especially in the context of a decision support system where knowledge accuracy, completeness and relevancy are highly required. This study discusses the challenges encountered when assessing ontology quality, primarily considering the agriculture domain and highlights anomalies in the existing evaluation tools. Consequently, the study developed a tool which addresses the identified limitations in the existing tools. This tool includes measures for assessing crucial quality characteristics related to agriculture ontologies, such as complexity, completeness, consistency, modularity, and comprehensibility. Further, it supports developers in gaining valuable insights to mitigate the issues associated with these key quality characteristics of ontologies.

AB - The development of well-engineered quality ontologies is crucial to ensure capabilities of ontologies such as enhanced communication, knowledge reuse, and knowledge analytical capabilities. Ontology engineers conduct comprehensive evaluations to ensure ontology quality by utilising multiple tools and approaches. However, the ontology evaluators encountered challenges in choosing appropriate evaluation tools and approaches, especially in the context of a decision support system where knowledge accuracy, completeness and relevancy are highly required. This study discusses the challenges encountered when assessing ontology quality, primarily considering the agriculture domain and highlights anomalies in the existing evaluation tools. Consequently, the study developed a tool which addresses the identified limitations in the existing tools. This tool includes measures for assessing crucial quality characteristics related to agriculture ontologies, such as complexity, completeness, consistency, modularity, and comprehensibility. Further, it supports developers in gaining valuable insights to mitigate the issues associated with these key quality characteristics of ontologies.

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Wilson S, Ginige A, Goonetillake J. Maintaining the quality of evolving ontologies in the agriculture domain: challenges and a specialised evaluation tool. In Gervasi O, Murgante B, Garau C, Taniar D, C. Rocha AMA, Faginas Lago MN, editors, Computational Science and Its Applications – ICCSA 2024: 24th International Conference, Hanoi, Vietnam, July 1–4, 2024, Proceedings, Part II. Switzerland: Springer. 2024. p. 273-292. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-64608-9_18

Maintaining the quality of evolving ontologies in the agriculture domain: challenges and a specialised evaluation tool

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Keywords

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