Ontology in Requirements Software Development Method: A Systematic Literature Review
Abstract
The requirement process is one of the most critical factors in determining whether the software development process is successful. It is crucial to consider the function that ontology plays in the requirements of software engineering development. People and organizations can more easily utilize and share data, information, and knowledge with one another because of the implementation of ontology. During our systematic assessment of the literature published between 2011 and 2020, we came across twenty publications that discussed ontology in requirements and how it might be used in software development processes. To determine which studies were the most pertinent to our research endeavors, we developed and implemented inclusion and exclusion criteria in two separate rounds. The review identified the leading ontology in data software development challenges. We found various ways to do this in our selected papers with different systematics as well. However, our findings indicate that the ontology requirements in software development must be addressed by examining various software development methods apart from agile scrum and XP.
Downloads
References
Abdelghany, A. S., Darwish, N. R., & Hefni, H. A. (2019). An Agile Methodology for Ontology Development. International Journal of Intelligent Engineering and Systems, 12(2), 170-181. doi:https://doi.org/10.22266/ijies2019.0430.17
Abioye, T. E., Arogundade, O. T., Misra, S., Akinwale, A. T., & Adeniran, O. J. (2020). Toward ontology-based risk management framework for software projects: An empirical study. Journal of Software: Evolution and Process, 32(12). doi:https://doi.org/10.1002/smr.2269
Adnan, M., & Afzal, M. (2017). Ontology Based Multiagent Effort Estimation System for Scrum Agile Method. IEEE Access, 5, 25993-26005. doi:https://doi.org/10.1109/ACCESS.2017.2771257
Adnan, M., Afzal, M., & Asif, K. H. (2019). Ontology-Oriented Software Effort Estimation System for E-commerce Applications Based on Extreme Programming and Scrum Methodologies. The Computer Journal, 62(11), 1605–1624. doi:https://doi.org/10.1093/comjnl/bxy141
Alrumaih, H., Mirza, A., & Alsalamah, H. (2020). Domain Ontology for Requirements Classification in Requirements Engineering Context. IEEE Access, 8, 89899-89908. doi:https://doi.org/10.1109/ACCESS.2020.2993838
Alsanad, A. A., Chikh, A., & Mirza, A. (2019). A Domain Ontology for Software Requirements Change Management in Global Software Development Environment. IEEE Access, 7, 49352-49361. doi:https://doi.org/10.1109/ACCESS.2019.2909839
Beck, K. (2000). Extreme Programming Explained: Embrace Change. Addison-Wesley.
Bhatia, M. P., Kumar, A., Beniwal, R., & Malik, T. (2020). Ontology driven software development for automatic detection and updation of software requirement specifications. Journal of Discrete Mathematical Sciences and Cryptography, 23(1), 197-208. doi:https://doi.org/10.1080/09720529.2020.1721884
Biagetti, M. T. (2021). Ontologies as knowledge organization systems. (B. H. Gnoli, Ed.) Knowledge Organization, 48(2), 152-176. Retrieved from Knowledge Organization: https://www.isko.org/cyclo/ontologies
Bichier, M., & Lin, K.-J. (2006). Service-oriented computing. Computer, 39(3), 99-101. doi:https://doi.org/10.1109/MC.2006.102
Cao, L., & Ramesh, B. (2008). Agile Requirements Engineering Practices: An Empirical Study. IEEE Software, 25(1), 60-67. doi:https://doi.org/10.1109/MS.2008.1
Chaccour, C., Saad, W., Debbah, M., Han, Z., & Poor, H. V. (2024). Less Data, More Knowledge: Building Next Generation Semantic Communication Networks. IEEE Communications Surveys & Tutorials. doi:https://doi.org/10.1109/COMST.2024.3412852
Chen, R., Chen, C.-H., Liu, Y., & Ye, X. (2020). Ontology-based requirement verification for complex systems. Advanced Engineering Informatics, 46. doi:https://doi.org/10.1016/j.aei.2020.101148
Corcho, O., Fernández-López, M., Gómez-Pérez, A., & López-Cima, A. (2005). Building Legal Ontologies with METHONTOLOGY and WebODE. In L. N. Science, Law and the Semantic Web (Vol. 3369, pp. 142–157). Berlin, Heidelberg: Springer. doi:https://doi.org/10.1007/978-3-540-32253-5_9
Cristani, M., & Cuel, R. (2005). A Survey on Ontology Creation Methodologies. International Journal on Semantic Web and Information Systems (IJSWIS), 1(2), 49-69. doi:https://doi.org/10.4018/jswis.2005040103
Davis, A. M. (1990). Software requirements: analysis and specification. United States: Prentice Hall Press. Retrieved from https://dl.acm.org/doi/abs/10.5555/78225
De Nicola, A., & Villani, M. L. (2021). Smart City Ontologies and Their Applications: A Systematic Literature Review. Sustainability, 13(10). doi:https://doi.org/10.3390/su13105578
Dzung, D. V., & Ohnishi, A. (2013). Evaluation of Ontology-Based Checking of Software Requirements Specification. 2013 IEEE 37th Annual Computer Software and Applications Conference. 37, pp. 425-430. Kyoto, Japan: IEEE. doi:https://doi.org/10.1109/COMPSAC.2013.70
Eng, N. L., Bracewell, R. H., & Clarkson, P. J. ( 2009). Concept Diagramming Software for Engineering Design Support: A Review and Synthesis of Studies. ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, (pp. 1221-1234). San Diego, California, USA. doi:https://doi.org/10.1115/DETC2009-86840
Farghaly, K., Soman, R. K., & Zhou, S. A. (2023). The evolution of ontology in AEC: A two-decade synthesis, application domains, and future directions. Journal of Industrial Information Integration, 36. doi:https://doi.org/10.1016/j.jii.2023.100519
Fauzan, R., Siahaan, D., Rochimah, S., & Triandini, E. (2018). Class Diagram Similarity Measurement: A Different Approach. 2018 3rd International Conference on Information Technology, Information System and Electrical Engineering (ICITISEE). 3, pp. 215-219. Yogyakarta, Indonesia: IEEE. doi:https://doi.org/10.1109/ICITISEE.2018.8721021
Fauzan, R., Siahaan, D., Solekhah, M., Saputra, V. W., Bagaskara, A. E., & Karimi, M. I. (2023). A Systematic Literature Review of Student Assessment Framework in Software Engineering Courses. Journal of Information Systems Engineering and Business Intelligence, 9(2), 264-275. doi:https://doi.org/10.20473/jisebi.9.2.264-275
Fernández-López, M., Gómez-Pérez, A., & Juristo Juzgado, N. (1997). METHONTOLOGY: From Ontological Art Towards Ontological Engineering. Proceedings of the Ontological Engineering AAAI-97 Spring Symposium Series (pp. 33-40). Stanford, California, United States: AAAI. Retrieved from https://oa.upm.es/5484/?trk=public_post_main-feed-card-text
Fraga, A. L., Vegetti, M., & Leone, H. P. (2020). Ontology-based solutions for interoperability among product lifecycle management systems: A systematic literature review. Journal of Industrial Information Integration, 20. doi:https://doi.org/10.1016/j.jii.2020.100176
Fu, C., Jiang, H., & Chen, X. (2022). RETRACTED ARTICLE: Modeling of an Enterprise Knowledge Management System Based on Artificial Intelligence. Knowledge Management Research & Practice, 1–13. doi:https://doi.org/10.1080/14778238.2020.1854632
Guizzardi, G. (2005). Ontological foundations for structural conceptual models. Enschede, Netherlands: University of Twente. Retrieved from https://research.utwente.nl/en/publications/ontological-foundations-for-structural-conceptual-models/
Guizzardi, G., & Guarino, N. (2024). Explanation, semantics, and ontology. Data & Knowledge Engineering, 153. doi:https://doi.org/10.1016/j.datak.2024.102325
Guizzardi, G., Halpin, T., & Halpin, T. (2008). Ontological foundations for conceptual modelling. Applied Ontology, 3(1-2), 1-12. doi:https://doi.org/10.3233/AO-2008-0049
Guyatt, G. H., & Rennie, D. (1993). Users' Guides to the Medical Literature. JAMA, 270(17), 2096–2097. doi:https://doi.org/10.1001/jama.1993.03510170086037
Guyatt, G., Rennie, D., Meade, M., & Cook, D. (2014). Users' Guides to the Medical Literature: Essentials of Evidence-Based Clinical Practice. McGraw Hill Education.
Haris, M. S., Kurniawan, T. A., & Ramdani, F. (2020). Automated Features Extraction from Software Requirements Specification (SRS) Documents as The Basis of Software Product Line (SPL) Engineering. JITeCS (Journal of Information Technology and Computer Science), 5(3), 279-292. doi:https://doi.org/10.25126/jitecs.202053219
Helmy, Y. M., Abdelgaber, S., Fahmy, H., & Montasser, H. S. (2020). A conceptual ontological framework for managing the social business process to enhance customer experience. Knowledge and Process Management, 27(4), 262-271. doi:https://doi.org/10.1002/kpm.1652
Hlomani, H., & Stacey, D. (2014). Approaches, methods, metrics, measures, and subjectivity in ontology evaluation: A survey. Undefined, 1, 1–5. Retrieved from https://semantic-web-journal.net/system/files/swj657.pdf
Husáková, M., & Bureš, V. (2020). Formal Ontologies in Information Systems Development: A Systematic Review. Information, 11(2). doi:https://doi.org/10.3390/info11020066
Inayat, I., Salim, S. S., Marczak, S., Daneva, M., & Shamshirband, S. (2015). A systematic literature review on agile requirements engineering practices and challenges. Computers in Human Behavior, 51, 915-929. doi:https://doi.org/10.1016/j.chb.2014.10.046
Innab, N., Kayed, A., & Sajeev, A. S. (2012). An ontology for software requirements modelling. 2012 IEEE International Conference on Information Science and Technology (pp. 485-490). Wuhan, China: IEEE. doi:https://doi.org/10.1109/ICIST.2012.6221694
Iqbal, R., Murad, M. 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. Retrieved from https://pdfs.semanticscholar.org/c017/bfc3d6c2b7fb3f6d2042b6cd483a63efce87.pdf
Jiang, D., Wu, Z., Hsie, C.-Y., Chen, G., Liao, B., Wang, Z., . . . Hou, T. (2021). Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models. Journal of Cheminformatics, 13(12). doi:https://doi.org/10.1186/s13321-020-00479-8
Jiang, N., & Tiwari, R. S. (2022). The Design of Mental Health Information Data Management System Under the Background of Informationization. Cyber Security Intelligence and Analytics (CSIA 2022). 123, pp. 303–310. Cham: Springer. doi:https://doi.org/10.1007/978-3-030-96908-0_38
Jing, X., Min, H., Gong, Y., Sittig, D. F., Biondich, P., Robinson, D., . . . Gimbel, R. (2022, May 11). medRxiv. doi:https://doi.org/10.1101/2022.05.11.22274984
Johnson, L. A. (1998). DO-178B, "Software Considerations in Airborne. Crosstalk, (pp. 11-20). Retrieved from http://www.dcs.gla.ac.uk/~johnson/teaching/safety/reports/schad.html
Kendall, E. F., & McGuinness, D. L. (2019). Ontology Engineering: Synthesis Lectures on the Semantic Web: Theory and Technology. Morgan & Claypool.
Kitchenham, B., Charters, S., Budgen, D., Brereton, P., Turner, M., Linkman, S., . . . Visaggio, G. (2007). Guidelines for performing Systematic Literature Reviews in Software Engineering. Durham, UK & Staffordshire, UK: Keele University & University of Durham.
Kitchenham, B., Pretorius, R., Budgen, D., Brereton, O. P., Turner, M., Niazi, M., & Linkman, S. (2010). Systematic literature reviews in software engineering – A tertiary study. Information and Software Technology, 52(8), 792-805. doi:https://doi.org/10.1016/j.infsof.2010.03.006
Kop, C. (2012). Checking feasible completeness of domain models with natural language queries. APCCM '12: Proceedings of the Eighth Asia-Pacific Conference on Conceptual Modelling. 130, pp. 33 - 42. Melbourne, Australia: Australian Computer Society. Retrieved from https://dl.acm.org/doi/abs/10.5555/2523782.2523787
Kumar, S. A., & Kumar, T. A. (2011). Study the impact of requirements management characteristics in global software development projects: an ontology based approach. International Journal of Software Engineering & Applications (IJSEA), 2(4). doi:https://doi.org/10.5121/ijsea.2011.2410
Lee, Y.-C., Eastman, C. M., & Solihin, W. (2016). An ontology-based approach for developing data exchange requirements and model views of building information modeling. Advanced Engineering Informatics, 30(3), 354-367. doi:https://doi.org/10.1016/j.aei.2016.04.008
Mukhopadhyay, A., & Ameri, F. (2016). An ontological approach to engineering requirement representation and analysis. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 30(4), 337-352. doi:https://doi.org/10.1017/S0890060416000330
Murtazina, M. S., & Avdeenko, T. V. (2018). Ontology-Based Approach to the Requirements Engineering in Agile Environment. 2018 XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE). 14, pp. 496-501. Novosibirsk, Russia: IEEE. doi:https://doi.org/10.1109/APEIE.2018.8546144
Murtazina, M., & Avdeenko, T. (2019). An Ontology-Based Approach to the Agile Requirements Engineering. Perspectives of System Informatics. 11964, pp. 205–213. Cham: Springer. doi:https://doi.org/10.1007/978-3-030-37487-7_17
Mustaffa, S. N., Sallim, J. B., & Mohamed, R. B. (2021). Semi – Automated Software Requirement Specification (SRS) Document Generator: The Guideline to Novice System Analyst. 2021 International Conference on Software Engineering & Computer Systems and 4th International Conference on Computational Science and Information Management (ICSECS-ICOCSIM) (pp. 80-85). Pekan, Malaysia: IEEE. doi:https://doi.org/10.1109/ICSECS52883.2021.00022
Olan, F., Arakpogun, E. O., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145, 605-615. doi:https://doi.org/10.1016/j.jbusres.2022.03.008
Ortega-Ordoñez, W. A., Pardo-Calvache, C. J., & Pino-Correa, F. J. (2019). OntoAgile: an ontology for agile software development processes. Dyna, 86(209), 79-90. doi:http://doi.org/10.15446/dyna.v86n209.76670
Osman, M. A., Noah, S. A., & Saad, S. (2022). Ontology-Based Knowledge Management Tools for Knowledge Sharing in Organization—A Review. IEEE Access, 10, 43267-43283. doi:https://doi.org/10.1109/ACCESS.2022.3163758
Peroni, S. (2017). A Simplified Agile Methodology for Ontology Development. OWL: Experiences and Directions – Reasoner Evaluation (OWLED 2016, ORE 2016) (pp. 55–69). Cham: Springer. doi:https://doi.org/10.1007/978-3-319-54627-8_5
Pileggi, S. F. (2021). Knowledge interoperability and re-use in Empathy Mapping: an ontological approach. Expert Systems with Applications, 180. doi:https://doi.org/10.1016/j.eswa.2021.115065
Pliatsios, A., Kotis, K., & Goumopoulos, C. (2023). A systematic review on semantic interoperability in the IoE-enabled smart cities. Internet of Things, 22. doi:https://doi.org/10.1016/j.iot.2023.100754
Poveda-Villalón, M., Fernández-Izquierdo, A., Fernández-López, M., & García-Castro, R. (2022). LOT: An industrial oriented ontology engineering framework. Engineering Applications of Artificial Intelligence, 111. doi:https://doi.org/10.1016/j.engappai.2022.104755
Said, A., Zhao, Y., Derr, T., Shabbir, M., Abbas, W., & Koutsoukos, X. (2023, Aug 23). A Survey of Graph Unlearning. doi:https://doi.org/10.48550/arXiv.2310.02164
Schön, E.-M., Thomaschewski, J., & Escalona, M. J. (2017). Agile Requirements Engineering: A systematic literature review. Computer Standards & Interfaces, 49, 79-91. doi:https://doi.org/10.1016/j.csi.2016.08.011
Schwaber, K. (2004). Agile Project Management with Scrum. Microsoft Press.
Shahzad, B., Javed, I., Shaikh, A., Sulaiman, A., Abro, A., & Memon, M. A. (2021). Reliable Requirements Engineering Practices for COVID-19 Using Blockchain. Sustainability, 13(12). doi:https://doi.org/10.3390/su13126748
Shrivastava, A., Jaggi, I., Katoch, N., Gupta, D., & Gupta, S. (2021). A Systematic Review on Extreme Programming. Journal of Physics: Conference Series, 1969. doi:https://doi.org/10.1088/1742-6596/1969/1/012046
Sitthithanasakul, S., & Choosri, N. (2016). Using ontology to enhance requirement engineering in agile software process. 10th International Conference on Software, Knowledge, Information Management & Applications (SKIMA). 10, pp. 181-186. Chengdu, China: IEEE. doi:https://doi.org/10.1109/SKIMA.2016.7916218
Smirnov, A., Levashova, T., Ponomarev, A., & Shilov, N. (2021). Methodology for Multi-Aspect Ontology Development: Ontology for Decision Support Based on Human-Machine Collective Intelligence. IEEE Access, 9, 135167-135185. doi:https://doi.org/10.1109/ACCESS.2021.3116870
Sousa, K., Vanderdonckt, J., Henderson-Sellers, B., & Gonzalez-Perez, C. (2012). Evaluating a graphical notation for modelling software development methodologies. Journal of Visual Languages & Computing, 23(4), 195-212. doi:https://doi.org/10.1016/j.jvlc.2012.04.001
Srivastava, A., Bhardwaj, S., & Saraswat, S. (2017). SCRUM model for agile methodology. 2017 International Conference on Computing, Communication and Automation (ICCCA) (pp. 864-869). Greater Noida, India: IEEE. doi:https://doi.org/10.1109/CCAA.2017.8229928
Sundaramoorthy, S. (2022). UML Diagramming: A Case Study Approach (1st ed ed.). Auerbach Publications. doi:https://doi.org/10.1201/9781003287124
Tan, H., Adlemo, A., Tarasov, V., & Johansson, M. E. (2017). Evaluation of an Application Ontology. Proceedings of the Joint Ontology Workshops 2017 Episode 3: The Tyrolean Autumn of Ontology. Bozen-Bolzano, Italy: DiVA. Retrieved from https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1185058&dswid=9486
Tan, H., Ismail, M., Tarasov, V., Adlemo, A., & Johansson, M. (2016). Development and Evaluation of a Software Requirements Ontology. Proceedings of the 7th International Workshop on Software Knowledge (IC3K 2016) - SKY. 1, pp. 11-18. Porto, Portugal: SciTePress. doi:https://doi.org/10.5220/0006079300110018
Triandini, E., Fauzan, R., Siahaan, D. O., Rochimah, S., Suardika, I. G., & Karolita, D. (2022). Software similarity measurements using UML diagrams: A systematic literature review. Register: Jurnal Ilmiah Teknologi Sistem Informasi, 8(1), 10-23. doi:https://doi.org/10.26594/register.v8i1.2248
Tsai, W.-T., Wu, B., Jin, Z., Huang, Y., & Li, W. (2013). Ontology patterns for service-oriented software development. Software: Practice and Experience, 43(7), 867-883. doi:https://doi.org/10.1002/spe.1132
Tudorache, T. (2020). Ontology engineering: Current state, challenges, and future directions. Semantic Web, 11(1), 125-138. doi:https://doi.org/10.3233/SW-190382
Wang, J., Mendori, T., & Xiong, J. (2014). A language learning support system using course-centered ontology and its evaluation. Computers & Education, 78, 278-293. doi:https://doi.org/10.1016/j.compedu.2014.06.009
Yangui, S., Goscinski, A., Drira, K., Tari, Z., & Benslimane, D. (2021). Future generation of service-oriented computing systems. Future Generation Computer Systems, 118, 252-256. doi:https://doi.org/10.1016/j.future.2021.01.019
Ye, K., Ni, W., Krieger, M., Ma'ayan, D., Wise, J., Aldrich, J., . . . Crane, K. (2020). Penrose: from mathematical notation to beautiful diagrams. ACM Transactions on Graphics, 39(4), 144:1 - 144:16. doi:https://doi.org/10.1145/3386569.3392375
Ye, X. (2023). A method of computer library information data management based on network analysis. Journal of Computational Methods in Sciences and Engineering, 23(2), 759-771. doi:https://doi.org/10.3233/JCM-226579
Yuan, X., & Zhang, X. ( 2015). An ontology-based requirement modeling for interactive software customization. 2015 IEEE International Model-Driven Requirements Engineering Workshop (MoDRE) (pp. 1-10). Ottawa, ON, Canada: IEEE. doi:https://doi.org/10.1109/MoDRE.2015.7343872
Zakaria, Z., Kasim, S., Hasbullah, N. H., Azadin, A. A., Ahmar, A. S., & Hidayat, R. (2018). The Development of Personality Ontology Based on the Methontology Approach. International Journal of Engineering & Technology, 7(2.5), 73-76. doi:http://dx.doi.org/10.14419/ijet.v7i2.5.13955
Copyright (c) 2025 The Authors

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright Notice based on COPE (Committee on Publication Ethics) for JITCS: Journal of Information Technology and Cyber Security
-
Ownership and Copyright:
- JITCS: Journal of Information Technology and Cyber Security respects the intellectual property rights of authors. The copyright for individual articles published in JITCS is retained by the respective authors, unless otherwise specified.
- The articles published in JITCS are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0), which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial, and no modifications or adaptations are made.
- JITCS serves as the initial publisher of the articles, providing them with the first publication platform.
-
Permissions and Usage:
- Distribution for Non-Commercial Purposes: Permitted: Users are allowed to distribute the article for non-commercial purposes, provided the original work is properly cited and no modifications or adaptations are made.
- Distribution for Commercial Purposes: Not Permitted: The article may not be distributed for any commercial purposes without obtaining prior written permission from the author(s).
- Inclusion in a Collective Work (e.g., Anthology) for Non-Commercial Purposes: Permitted: Users are allowed to include the article in a collective work, such as an anthology, as long as the use is non-commercial and the work remains unchanged.
- Inclusion in a Collective Work for Commercial Purposes: Not Permitted: The article may not be included in any collective work or anthology intended for commercial purposes without prior permission from the author(s).
- Creation and Distribution of Revised Versions, Adaptations, or Derivative Works (e.g., Translation) for Non-Commercial Purposes: Not Permitted: Users may not create or distribute revised versions, adaptations, or derivative works, including translations, for non-commercial purposes.
- Creation and Distribution of Revised Versions, Adaptations, or Derivative Works for Commercial Purposes: Not Permitted: Users may not create or distribute revised versions, adaptations, or derivative works, including translations, for commercial purposes.
- Text or Data Mining for Non-Commercial Purposes: Permitted: Users are permitted to engage in text or data mining of the article for non-commercial research purposes, provided the original work is properly attributed.
- Text or Data Mining for Commercial Purposes: Not Permitted: Users may not engage in text or data mining of the article for commercial purposes without obtaining explicit permission from the author(s).
-
Attribution and Citation:
- Proper attribution and citation of the published work should be provided when using or referring to content from JITCS. This includes clearly indicating the authors, the title of the article, the journal name (JITCS), the volume/issue number, the publication year, and the article's DOI (Digital Object Identifier) when available.
- When adapting or modifying the published content, proper attribution to the original source should be given, and the adapted or modified content should be shared under the same CC BY-NC-ND 4.0 license.
-
Plagiarism and Copyright Infringement:
- JITCS considers plagiarism and copyright infringement as serious ethical violations. Authors are responsible for ensuring that their submitted work is original and does not infringe upon the copyright or intellectual property rights of others.
- Any allegations of plagiarism or copyright infringement will be investigated promptly and thoroughly. If proven, appropriate actions, including rejection of the manuscript, retraction of the published article, or other corrective measures, will be taken.
-
Open Access Licensing:
- JITCS supports open access publishing and encourages authors to consider publishing their work under the CC BY-NC-ND 4.0 license to promote the dissemination and use of knowledge in the field of information technology and cyber security.
- The specific terms and conditions of the CC BY-NC-ND 4.0 license will be clearly indicated on the published articles.
-
Policy Review: This Copyright Notice will be periodically reviewed and updated to ensure its continued relevance and compliance with copyright laws, ethical standards, and open access principles in scholarly publishing. Any updates or revisions to the notice will be communicated to the relevant stakeholders.
By adhering to this Copyright Notice, JITCS aims to protect the rights of authors, promote proper attribution and citation practices, and facilitate the responsible and legal use of the published content in accordance with the CC BY-NC-ND 4.0 license.