Evaluating the Efficiency of Nuclear Medicine Ontology in Knowledge Representation and Concepts Retrieval by Ontometric approach

Document Type : Original Article

Authors

1 Ph.D., Student, Department of Knowledge and Information Science, Tehran North Branch, Islamic Azad University, Tehran, Iran

2 Associate Professor, Department of Knowledge and Information Science, Tehran North Branch, Islamic Azad University, Tehran, Iran

3 Assosiate Professor, Department of Terminology and Ontology, Iranian Research Institute for Information Science and Technology (IranDoc), Tehran, Iran

Abstract

Purpose: This study aims to evaluate the efficiency of the Nuclear Medicine Ontology (NucMedOnt) based on the ontometric method with the criteria of content display, content, user understanding of content, search, and retrieval of concepts.
Methods: The current research is of applied type. Evaluation of NucMedOnt ontology was carried out with a qualitative approach in the form of a usability study using the usability test followed by a questionnaire survey, constructed with an Ontometric approach and Likert scale (Fathian, 2010). The sample population consisted of 10 faculty members and subject specialists in the Nuclear Medicine field, selected by using the Purposive sampling method from 26 specialists in Physics, Radiological Engineering, Nuclear Pharmacology, and Medical Physics fields, working in the specialized center with experience using the INIS Thesaurus and announced their cooperation. For evaluation, 10 randomly selected concepts in the field of nuclear medicine were provided to the participants.
Findings: 94% of the users were satisfied with the performance of content display criteria, 100% with concepts criteria, 98% with relationships criteria, 93% with the instance criteria, 98% with the users' content perception criteria, and 89% of the users were satisfied with the content search and retrieval criteria of the Nuclear Medicine Ontology (NucMedOnt) and evaluated their effectiveness as desirable and appropriate.
Also, there was no significant difference between the opinions of experts in the user’s content perception criteria, content criteria, content display criteria, and content search and retrieval criteria in the Nuclear Medicine Ontology (NucMedOnt).
Conclusions: Nuclear Medicine Ontology (NucMedOnt) is an effective tool for knowledge representation and upgrading the databases of the Nuclear Medicine field. The results show the high satisfaction of the participants with the efficiency of knowledge representation and concepts search and retrieval in the Nuclear Medicine Ontology (NucMedOnt). The rich set of basic concepts and also the citation on the publishing information resources of the Nuclear Medicine Field in the documentation of the Persian equivalents for the English concepts were among the reasons for the high satisfaction of the Nuclear Medicine specialists and the high score in their evaluation.
 

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References

Alishan Karami, N. (2017). A Feasibility Study on Design and Engineering of Epilepsy Ontology and its Performance in Semantic Information Retrieval. Ph.D. Thesis. Department of Information Science and Epistemology, Faculty of Literature and Human Sciences, Imam Reza International University. [in persian]
Berners-Lee, T. (1998). What the Sematic Web can represent. Available Available at:             
https://www.w3.org/DesignIssues/Semantic.html
Berners-Lee, T., Hendler, J. & Lassila, O. (2001). The Semantic Web: a new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Scientific American, 284: 34-43.
Brank, J., Grobelnic, M. & Mladenic, D. (2005). A survey of Ontology evaluation techniques. In: Proceedings of the Conference on Data Mining and Data Warehouses. (SiKDD 2005(. Ljubljana, Slovenia.
Bravo, M., Hoyos-Reyes, L.F. & Reyes Ortiz, J.A. (2019). Methodology for Ontology Design and Construction. Contaduria y Administracion, 64(4): 1-24. DOI: 10.22266/ijies2019.0430.17.
Brewster, C., Alani, H., Dasmahapatra, S. & Wilks, Y. (2004). Data Driven Ontology Evaluation. In: Proceedings of Int. Conf. on Language Resources and Evaluation, Lisbon.
Fathian Dastgerdi, A. (2010). The comparison of thesaurus and ontology efficiency in knowledge representation. M.A. Thesis. Knowledge and information science, Faculty of education and psychology, Ferdowsi University. [in persian]
Fathian Dastgerdi, A. (2012). Ontology Evaluation: Consideration of Criteria, Approaches and Layers. Iranian Journal of Information Processing and Management, 27(2): 3-25. [in persian]
Jamali Mahmoui, H.R. (2004). Semantic Web: An evolving way. Informology, 1(2): 49-66.
[in persian]
Lozano-Tello, A. & Gomez-Perez, A. (2004). Ontometric: a method to choose the appropriate ontology. J. Database Manag, 15: 1-18. DOI: 10.4018/jdm.2004040101
Maedche, A. & Staab, S. (2002). Measuring similarity between ontologies. In: Proc. CIKM 2002: 2473.
Nowroozi, M. (2015). The comparison of thesaurus and ontology efficiency in semantic concepts and relations representation (case study: ASIS thesaurus and designed ontology(. M.A. Thesis. Faculty of education and psychology, Shiraz University. [in persian]
Porzel, R. & Malaka, R. (2004). A task-based approach for ontology evaluation. In: ECAI 2004 Workshop Ont. Learning and Population.
Reyes-Peña, C. & Tovar-Vidal, M. (2019). Ontology: Components and Evaluation: A Review. Research on computing science, 14: 257-265. DOI: 10.13053/rcs-148-3-21
Sanatjoo, A. & Fathian Dastgerdi, A. (2011). The comparison of thesaurus and ontology efficiency in knowledge representation. Library and Information Science Research, 1(1): 219-240.
[in persian]
Sawsaa, A. (2013). A Generic Model of Ontology to Visualize Information Science Domain (OIS). Ph.D. Thesis, University of Huddersfield.
Zardari, S. (2016). Ontology engineering of knowledge and information science based on library and information encyclopedia. P.hD. thesis. Faculty of Education and Psychology. Shahid Chamran University. [in persian]
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Sciences and Techniques of Information Management
Volume 9, Issue 1
May 2023
Pages 253-278

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