A Study of Various Dimensions of Ontology Development Methodologies
Authors
-
Content Analysis and Knowledge Engineering, Yahoo Software Development India Private Limited, Bengaluru – 560071, Karnataka
Prashant Kumar Sinha -
Documentation Research and Training Centre, Indian Statistical Institute, Bengaluru – 560059, KarnatakaBiswanath Dutta
DOI:
https://doi.org/10.17821/srels/2025/v62i2/171809Keywords:
Ontologies, Ontology Development, Ontology Development Methodologies, Ontology Engineering, Ontology Engineering MethodologiesAbstract
Ontology Development Methodologies (ODMs) represent a systematic set of activities designed to support the structured creation of ontologies. Over the last 35 years, ODM research has evolved considerably, giving rise to a wide range of methodologies that have been applied across diverse domains such as biomedicine, finance, engineering, disaster management, and others. These methodologies have enabled the development of domain-specific ontologies tailored to meet various objectives. With ongoing technological advancements, the process of ontology development has transformed significantly. However, despite this progress, ontology engineering continues to face substantial complexity and unresolved challenges. To address these concerns, the present study offers a comprehensive review of the multifaceted dimensions of ODMs, organising them into a coherent taxonomy. The review covers key areas including ontology design approaches, ODM classification schemes, tools and technologies, evaluation methods, the integration of Large Language Models (LLMs), and the prevailing challenges in ODM research. Notably, this work consolidates and presents ten different classification schemes of ODMs, a comparative analysis of 11 Ontology Representation Languages (ORLs), 32 Ontology Development Environments (ODEs), 12 Ontology Evaluation Tools (OETs), and four ontology formalisms in one unified resource. Furthermore, the study brings together diverse evaluation approaches—some focused on specific categories such as agile methodologies, while others adopt a broader scope. Additionally, emerging research initiatives like OntoChat and DeepOnto are highlighted, showcasing how LLMs are now being leveraged to develop novel forms of ODMs. By offering a panoramic view of the ODM landscape, this study serves as a valuable resource for researchers, practitioners, and ODM developers, facilitating a deeper understanding of the current state, ongoing trends, and future directions in ontology development.
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References
Alatrish, E. S. (2012). Comparison of ontology editors. Management Information Systems, 8(2), 18-24.
Al-Baltah, I. A., Ghani, A. A. A., Rahman, W. N. W. A., & Atan, R. (2014). A comparative study on ontology development methodologies towards building semantic conflicts detection ontology for heterogeneous web services. Research Journal of Applied Sciences, Engineering and Technology, 7(13): 2674-2679. https://doi.org/10.19026/rjaset.7.584
Aminu, E. F., Oyefolahan, I. O., Abdullahi, M. B., & Salaudeen, M. T. (2020). A review on ontology development methodologies for developing ontological knowledge representation systems for various domains. International Journal of Information Engineering and Electronic Business, 12(2), 28-39. https://doi.org/10.5815/ijieeb.2020.02.05
Amith, M., Manion, F., Liang, C., Harris, M., Wang, D., He, Y., & Tao, C. (2019). Architecture and usability of OntoKeeper, an ontology evaluation tool. BMC Medical Informatics and Decision Making, 19(S4): Article 152. https:// doi.org/10.1186/s12911-019-0859-z PMid:31391056 PMCid:PMC6686219
Auer, S., & Herre, H. (2006). RapidOWL – An agile knowledge engineering methodology. International Andrei Ershov Memorial Conference on Perspectives of System Informatics, Springer Berlin Heidelberg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70881-0_36
Avila, C. V. S., Maia, G., Franco, W., Rolim, T. V., da Rocha Franco, A. D. O., & Vidal, V. M. P. (2019). OntoVal: A tool for ontology evaluation by domain specialists. ER 2019 – 38th International Conference on Conceptual Modeling.
Blomqvist, E., Hitzler, P., Janowicz, K., Krisnadhi, A., Narock, T., & Solanki, M. (2015). Considerations regarding ontology design patterns. Semantic Web, 7(1), 1-7. ttps://doi.org/10.3233/SW-150202
Bouiadjra, A. B., & Benslimane, S.-M. (2011). FOEval: Full ontology evaluation. 7th International Conference on Natural Language Processing and Knowledge Engineering. https://doi.org/10.1109/NLPKE.2011.6138244
Brank, J., Marko, G., & Dunja, M. (2005). A survey of ontology evaluation techniques. Proceedings of the Conference on Data Mining and Data Warehouses (SiKDD 2005), pp. 166170.
Brusa, G., Caliusco, M. L., & Chiotti, O. (2008). Towards ontological engineering: A process for building a domain ontology from scratch in public administration. Expert Systems, 25(5), 484-503. https://doi.org/10.1111/j.14680394.2008.00471.x
Buitelaar, P., & Cimiano, P. (2008). Ontology learning and population: Bridging the gap between text and knowledge. Frontiers in Artificial Intelligence and Applications. IOS Press.
Calbimonte, J. P., Dubosson, F., Hilfiker, R., Cotting, A. & Schumacher, M. (2017). The MedRed ontology for representing clinical data acquisition metadata. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10588 LNCS, pp. 38-47. https://doi.org/10.1007/978-3-31968204-4_4
Chimienti, M., Dassisti, M., De Nicola, A. & Missikoff, M. (2009). Evaluation of ontology building methodologies – A method based on balanced scorecards. International Conference on Knowledge Engineering and Ontology Development, Vol. 2, Scitepress, pp. 141-146. https://doi.org/10.5220/0002287001410146
Corcho, O., Fernandez-Lopez, M., & Gomez-Perez, A. (2003). Methodologies, tools and languages for building ontologies. Where is their meeting point? Data and Knowledge Engineering, 46(1): 41-64. https://doi.org/10.1016/S0169023X(02)00195-7
Corcho, O., Fernández-López, M., & Gómez-Pérez, A. (2006). Ontological engineering: Principles, methods, tools and languages. Ontologies for Software Engineering and Software Technology, Springer. https://doi.org/10.1007/3-540-345183_1
d’Aquin, M., & Lewen, H. (2009). Cupboard – A place to expose your ontologies to applications and the community. In L. Aroyo, P. Traverso, F. Ciravegna, P. Cimiano, T. Heath, E. Hyvönen, R …, E. Simperl (Eds.), The semantic web: Research and Applications, Vol. 5554 (pp. 913-918). Springer Berlin Heidelberg.
De Nicola, A., & Missikoff, M. (2016). A lightweight methodology for rapid ontology engineering. Communications of the ACM, 59(3): 79-86. https://doi.org/10.1145/2818359
De Nicola, A., Missikoff, M., & Navigli, R. (2009). A software engineering approach to ontology building. Information Systems, 34(2), 258-275. https://doi.org/10.1016/j.is.2008.07.002
Debnath, N. C. & Patel, A. (2023). Ontology evaluation tools: Current and future research. Recent Advances in Computer Science and Communications, 16(6), Article e110422203361. https://doi.org/10.2174/2666255815666220411081837
Doumanas, D., Bouchouras, G., Soularidis, A., Kotis, K., & Vouros, G. (2024). From human-to LLM-centered collaborative ontology engineering. Applied Ontology, 1(34).
Doumanas, D., Soularidis, A., Spiliotopoulos, D., Vassilakis, C., & Kotis, K. (2025). Fine-tuning large language models for ontology engineering: A comparative analysis of GPT-4 and mistral. Applied Sciences, 15(4), Article 2146. https://doi.org/10.3390/app15042146
Duque-Ramos, A., Fernandez-Breis, J. T., Stevens, R., & Aussenac-Gilles, N. (2011). OQuaRE: A SQuaRE-based approach for evaluating the quality of ontologies. Journal of Research and Practice in Information Technology, 43(2), 159-176.
Dutta, B. (2017). Examining the interrelatedness between ontologies and linked data. Library Hi Tech, 35(2), 312-331. https://doi.org/10.1108/LHT-10-2016-0107
Dutta, B., & Sinha, P. K. (2018). A bibliometric analysis of automatic and semi-automatic ontology construction processes. Annals of Library and Information Studies, 65(2), 112-121.
Dutta, B., & Sinha, P. K. (2023). An ontological data model to support urban flood disaster response. Journal of Information Science. https://doi.org/10.1177/01655515231167297
Dutta, B., Chatterjee, U., & Madalli, D. P. (2015). YAMO: Yet another methodology for large-scale faceted ontology construction. Journal of Knowledge Management, 19(1), 6-24. https://doi.org/10.1108/JKM-10-2014-0439
Escórcio, A., & Cardoso, J. (2007). Editing tools for ontology creation. Semantic Web Services: Theory, Tools and Applications, IGI Global (pp. 71-95). https://doi.org/10.4018/978-1-59904-045-5.ch004
Farquhar, A., Fikes, R., & Rice, J. (1997). The ontolingua server: A tool for collaborative ontology construction. International Journal of Human-Computer Studies, 46(6), 707-727. https://doi.org/10.1006/ijhc.1996.0121
Fernández-López, M., & Gómez-Pérez, A. (2002). Overview and analysis of methodologies for building ontologies. The Knowledge Engineering Review, 17(2), 129-156. https://doi.org/10.1017/S0269888902000462
Fernandez-Lopez, M., Gomez-Perez, A., & Juristo, N. (1997). METHONTOLOGY: From ontological art towards ontological engineering. Proceedings of the AAAI Spring Symposium Series, AAAI Press, Menlo Park, CA.
Garijo, D., Poveda-Villalón, M., Amador-Domínguez, E., Wang, Z., García-Castro, R., & Corcho, O. (2022). LLMs for ontology engineering: A landscape of tasks and benchmarking challenges. ISWC’24, Special Session on LLMs, Maryland, USA.
Garrido, J., & Requena, I. (2012). Towards summarizing knowledge: Brief ontologies. Expert Systems with Applications, 39(3), 3213-3222. https://doi.org/10.1016/j.eswa.2011.09.008
Giunchiglia, F., Dutta, B., & Maltese, V. (2014). From knowledge organization to knowledge representation. Knowledge Organization, 41(1), 44-56. https://doi.org/10.5771/09437444-2014-1-44
Gobin B. (2014a). A quantitative framework for assessing agile ontology engineering methodologies. Conference: International Conference on Web and Information Systems 2014, Hammamet, Tunisia.
Gobin B. A. (2014b). Assessing the suitability of existing Agile Ontology Engineering Methodologies for ontology module development. Conference: International Conference on Web and Information Systems 2014.
Gobin B. A. (2014c). Using the 4-DAT tool to evaluate agile ontology engineering methodologies. Conference: International Conference on Web and Information Systems 2014.
Gómez-Pérez, A., & Rojas-Amaya, M.D. (1999). Ontological reengineering for reuse. International Conference on Knowledge Engineering and Knowledge Management. Springer, Berlin Heidelberg. https://doi.org/10.1007/3-54048775-1_9
Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), 199200. https://doi.org/10.1006/knac.1993.1008
Gruninger, M. & Fox, M. S. (1995). Methodology for the design and evaluation of ontologies. Workshop on Basic Ontological Issues in Knowledge Sharing (IJCAI-95), Montreal.
Guarino, N., & Welty, C. A. (2004). An overview of OntoClean. In S. Staab, & R. Studer, Handbook on ontologies (pp. 151-171), Springer, Berlin Heidelberg. https://doi.org/10.1007/978-3540-24750-0_8
Hakkarainen S., Strasunskas D., Hella L., & Tuxen S. (2005). Weighted evaluation of ontology building methods. CAiSE Short Paper Proceedings.
He, Y., Chen, J., Dong, H., Horrocks, I., Allocca, C., Kim, T., & Sapkota, B. (2024). DeepOnto: A Python package for ontology engineering with deep learning. Semantic Web, 15(5), 1991-2004. https://doi.org/10.3233/SW-243568
Holsapple, C. W., & Joshi, K. D. (2002). A collaborative approach to ontology design. Communications of the ACM, 45(2), 42-47. https://doi.org/10.1145/503124.503147
Iqbal, R., Murad, M. A. A., Mustapha, A., & Sharef, N. M. (2013). An analysis of ontology engineering methodologies: A literature review. Research Journal of Applied Sciences, Engineering and Technology, 6(16), 2993-3000. https://doi.org/10.19026/rjaset.6.3684
Islam, N., Abbasi, A. Z., & Shaikh, Z. A. (2010). Semantic web: choosing the right methodologies, tools and standards. International Conference on Information and Emerging Technologies. https://doi.org/10.1109/ICIET.2010.5625736 PMid:20046163
Kassel, G. (2002). OntoSpec: Une méthode de spécification semi-informelle d’ontologies. Actes de IC (pp. 75-87).
Keet, M. (2018). An introduction to ontology engineering, College Publications, London.
Kolozali, S., Elsaleh, T., & Barnaghi, P. (2014). A validation tool for the W3C SSN ontology based sensory semantic knowledge. Conference: Joint Proceedings of the 6th International Workshop on the Foundations, Technologies and Applications of the Geospatial Web and 7th International Workshop on Semantic Sensor Networks, Riva del Garda, Trentino, Italy, Vol 1401.
Kassel, G. (2002). OntoSpec: Une méthode de spécification semi-informelle d’ontologies. Actes de IC (pp. 75-87).
Keet, M. (2018). An introduction to ontology engineering, College Publications, London.
Kotis, K. & Vouros, G. A. (2006). Human-centered ontology engineering: The HCOME methodology. Knowledge and Information Systems, 10(1), 109-131. https://doi.org/10.1007/s10115-005-0227-4
Kotis, K. I., Vouros, G. A., & Spiliotopoulos, D. (2020). Ontology engineering methodologies for the evolution of living and reused ontologies: Status, trends, findings and recommendations. The Knowledge Engineering Review, 35, Article e4. https://doi.org/10.1017/S0269888920000065
Law, N. L. L. M. F., Mahmoud, M. A., Tang, A. Y., Lim, F. C., Kasim, H., Othman, M., & Yong, C. (2019). A review of ontology development aspects. International Journal of Advanced Computer Science and Applications, 10(7), 290298. https://doi.org/10.14569/IJACSA.2019.0100740
Lehmann, J., & Völker, J. (2014). Perspectives on ontology learning. Studies on the semantic web, Vol. 18, IOS Press.
Lenat, D., & Guha, R. V. (1990). Cyc: A midterm report. AI Magazine, 11(3): 32-59.
Lippolis, A. S., Saeedizade, M. J., Keskisärkkä, R., Zuppiroli, S., Ceriani, M., Gangemi, A. & Nuzzolese, A. G. (2025). Ontology generation using large language models. arXiv preprint arXiv:2503.05388.
Lozano-Tello, A., & Gomez-Perez, A. (2004). ONTOMETRIC: A method to choose the appropriate ontology. Journal of Database Management, 15(2): 1-18. https://doi.org/10.4018/ jdm.2004040101
Lenat, D., & Guha, R. V. (1990). Cyc: A midterm report. AI Magazine, 11(3): 32-59.
Martínez-Romero, M., Jonquet, C., O’connor, M. J., Graybeal, J., Pazos, A., & Musen, M. A. (2017). NCBO ontology recommender 2.0: An enhanced approach for biomedical ontology recommendation. Journal of Biomedical Semantics, 8, Article 21. https://doi.org/10.1186/s13326-017-0128-y PMid:28592275 PMCid:PMC5463318
Mars, N., de Jong, H., Speel, P. H. W. M., ter Stal, W. G., & van der Vet, P. E. (1994). Semi-automatic knowledge acquisition in Plinius: An engineering approach. 8th Banff Knowledge Acquisition for Knowledge Based Systems Workshop, KAW 1994, University of Twente. Banff.
Mateiu, P., & Groza, A. (2023). Ontology engineering with large language models. 25th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). https://doi.org/10.1109/SYNASC61333.2023.00038
Nguyen, B. A., & Yang, D.-L. (2011). A preliminary study on semi-automatic construction of Vietnamese ontology. IEEE International Conference on Systems, Man, and Cybernetics. https://doi.org/10.1109/ICSMC.2011.6084195 PMid:21997471 PMCid:PMC3891926
Noy, N. F., and McGuinness, D. L. (2001). Ontology development 101: A guide to creating your first ontology, stanford knowledge systems laboratory, Stanford University, Stanford, Technical Report SMI-2001-0880.
Ohta, M., Kozaki, K., & Mizoguchi, R. (2011). A quality assurance framework for ontology construction and refinement. In E. Mugellini, P. S. Szczepaniak, M. C. Pettenati, & M. Sokhn. Advances in Intelligent Web Mastering – 3 (pp. 207-216), Springer Berlin Heidelberg. 2011. https://doi.org/10.1007/978-3-642-18029-3_21
Otero-Cerdeira, L., Rodríguez-Martínez, F. J., & GómezRodríguez, A. (2015). Ontology matching: A literature review. Expert Systems with Applications, 42(2), 949-971.
Patel, A., Debnath, C. N., Mishra, A., & Jain, S. (2021). Covid19-IBO: A Covid19-impact-on-Indian-banking ontology along with an efficient schema matching approach. New Generation Computing, 39(3-4), 647676. https://doi.org/10.1007/s00354-021-00136-0 PMid:34667368 PMCid:PMC8517947
Peroni, S. (2016). A simplified agile methodology for ontology development. International Experiences and Directions Workshop on OWL (pp. 55-69). Cham: Springer International Publishing. Springer. https://doi.org/10.1007/978-3-31954627-8_5
Pinto, H. S., & Martins, J. P. (2004). Ontologies: How can they be built? Knowledge and Information Systems, 6(4), 441464. https://doi.org/10.1007/s10115-003-0138-1
Poveda-Villalón, M., Gómez-Pérez, A., & Suárez-Figueroa, M. C. (2014). OOPS! (OntOlogy Pitfall Scanner!): An on-line tool for ontology evaluation. International Journal on Semantic Web and Information Systems, 10(2), 7-34. https://doi.org/10.4018/ijswis.2014040102
Qu, C., Liu, F., Yu, H., Yuan, R., & Wang, A. (2016). User oriented semi-automatic method of constructing domain ontology. In K. Li, J. Li, Y. Liu, & A. Castiglione, Computational Intelligence and Intelligent Systems (pp. 553-561). Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_58
Rebele, T., Suchanek, F. M., Hoffart, J., Biega, J., Kuzey, E., & Weikum, G. (2016). YAGO: A multilingual knowledge base from Wikipedia, Wordnet, and Geonames. The Semantic Web - {ISWC} 2016 - 15th International Semantic Web Conference, Kobe, Japan, Proceedings, Part {II}. https://doi.org/10.1007/978-3-319-46547-0_19
Roldan-Molina, G. R., Mendez, J. R., Yevseyeva, I., & BastoFernandes, V. (2020). Ontology fixing by using software engineering technology. Applied Sciences, 10(18), Article 6328. https://doi.org/10.3390/app10186328
Saeedizade, M. J., & Blomqvist, E. (2024). Navigating ontology development with large language models. European Semantic Web Conference, Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-60626-7_8
Sattar, A., Surin, E. S. M., Ahmad, M. N., Ahmad, M., & Mahmood, A. K. (2020). Comparative analysis of methodologies for domain ontology development: A systematic review. International Journal of Advanced Computer Science and Applications, 11(5), 99-108. https://doi.org/10.14569/IJACSA.2020.0110515
Schlenoff, C. (2009). Ontology formalisms: What is appropriate for different applications? Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems. https://doi.org/10.1145/1865909.1865947
Shvaiko, P., & Euzenat, J. (2011) Ontology matching: State of the art and future challenges. IEEE Transactions on Knowledge and Data Engineering, 25(1), 158-176. https://doi.org/10.1109/TKDE.2011.253
Simperl, E., & Luczak-Rösch, M. (2014). Collaborative ontology engineering: A survey. The Knowledge Engineering Review, 29(1), 101-131. https://doi.org/10.1017/S0269888913000192
Sinha, P. K., Dutta, B., & Varadarajan, U. (2022). Ranking the ontology development methodologies using the weighted decision matrix. Data Technologies and Applications, 56(5), 686-719. https://doi.org/10.1108/DTA-05-2021-0123
Sinha, P. K., Gajbe, S. B., Debnath, S., Sahoo, S., Chakraborty, K., & Mahato, S. S. (2021). A review of data mining ontologies. Data Technologies and Applications, 56(2): 172-204. https://doi.org/10.1108/DTA-04-2021-0106
Sinha, P. K., & Dutta, B. (2020). A systematic analysis of flood ontologies: A parametric approach. KO Knowledge Organization, 47(2), 138-159. https://doi.org/10.5771/09437444-2020-2-138
Slimani, T. (2015). Ontology development: A comparing study on tools, languages and formalisms. Indian Journal of Science and Technology, 8(24), 1-12. https://doi.org/10.17485/ijst/2015/v8i34/54249
Spoladore, D., & Pessot, E. (2021). Collaborative ontology engineering methodologies for the development of decision support systems: Case studies in the healthcare domain. Electronics, 10(9): Article 1060. https://doi.org/10.3390/electronics10091060
Spoladore, D., Pessot, E., & Trombetta, A. (2023). A novel agile ontology engineering methodology for supporting organizations in collaborative ontology development. Computers in Industry, 151, Article 103979. https://doi.org/10.1016/j.compind.2023.103979
Spoladore, D., & Pessot, E. (2022). An evaluation of agile ontology engineering methodologies for the digital transformation of companies. Computers in Industry, 140, Article 103690. https://doi.org/10.1016/j.compind.2022.103690
Spyns, P., Tang, Y., & Meersman, R. (2007). A model theory inspired collaborative ontology engineering methodology. Journal of Applied Ontology, 4(1). https://doi.org/10.3233/AO-2008-0047
Suarez-Figueroa, M. C., Gomez-Perez, A., & Fernandez-Lopez, M. (2015). The NeOn methodology framework: A scenario-based methodology for ontology development. Applied Ontology, 10(2):107-145. https://doi.org/10.3233/AO-150145
Suárez-Figueroa, M. C., García-Castro, R., Villazón-Terrazas, B., & Gómez-Pérez, A. (2011). Essentials in ontology engineering: Methodologies, languages, and tools. Proceedings of the 2nd Workshop Organized by the eeb Data Models Community-CIB, Sophia Antipolis, France.
Sure, Y., Staab, S., & Studer, R. (2004). On-To-Knowledge Methodology (OTKM). Handbook on Ontologies (pp. 117–132), Springer, Berlin/Heidelberg, Germany. https://doi.org/10.1007/978-3-540-24750-0_6
Tartir, S., Arpinar, I. B., Moore, M., Sheth, A. P., & Aleman-Meza, B. (2005). OntoQA: Metric-based ontology quality analysis. IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources.
Tempich, C., Pinto, H. S., Sure, Y., Vrandecic, D., Casellas, N., & Casanovas, P. (2005). Evaluating DILIGENT ontology engineering in a legal case study. Proceedings of the IVR 22nd World Congress–Law and Justice in a Global Society. International Association for Philosophy of Law and Social Philosophy.
Tudorache, T. (2020). Ontology engineering: Current state, challenges, and future directions. Semantic Web, 11(1): 125-138. https://doi.org/10.3233/SW-190382
Uschold, M., & Gruninger, M. (1996). Ontologies: Principles, methods and applications. The Knowledge Engineering Review, 11(2): 93-136. https://doi.org/10.1017/S0269888900007797
Uschold, M., & King, M. (1995). Towards a methodology for building ontologies (pp. 1-13). Edinburgh, Artificial Intelligence Applications Institute, University of Edinburgh.
Uschold, M., King, M., Moralee, S. & Zorgios, Y. (1995). The enterprise ontology. The Knowledge Engineering Review, 13(1), 31-89. https://doi.org/10.1017/S0269888998001088
Vrandecic, D., Pinto, S., Tempich, C., & Sure, Y. (2005). The DILIGENT knowledge processes. Journal of Knowledge Management, 9(5), 85-96. https://doi.org/10.1108/13673270510622474
Zhang, B., Carriero, V. A., Schreiberhuber, K., Tsaneva, S., González, L. S., Kim, J., & de Berardinis, J. (2024). OntoChat: A framework for conversational ontology engineering using language models (pp. 102-121). European Semantic Web Conference. Cham: Springer Nature, Switzerland. https://doi.org/10.1007/978-3-031-78952-6_10
Zheng, Y., He, Q., Qian, P., & Li, Z. (2012). Construction of the ontology-based agricultural knowledge management system. Journal of Integrative Agriculture, 11(5), 700-709. https://doi.org/10.1016/S2095-3119(12)60059-8
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