Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Design and Development of SRIONTO: An Educational Ontology Representing Software Risk Identification Knowledge

International Conference and Workshop on Emerging Trends in Technology
© 2011 by IJCA Journal
Number 15 - Article 2
Year of Publication: 2011
C.R.Rene Robin

C.R.Rene Robin and G.V.Uma. Design and Development of SRIONTO: An Educational Ontology Representing Software Risk Identification Knowledge. IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET) (15):5-13, 2011. Full text available. BibTeX

	author = {C.R.Rene Robin and G.V.Uma},
	title = {Design and Development of SRIONTO: An Educational Ontology Representing Software Risk Identification Knowledge},
	journal = {IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET)},
	year = {2011},
	number = {15},
	pages = {5-13},
	note = {Full text available}


Knowledge can be captured and made available to both machines and humans by an ontology. Ontology can be served as a structured knowledge representation scheme, capable of assisting the construction of a personalized learning path. This paper describes the processes of conceptualization and specification, or building of, an ontology. The domain for which the ontology has been constructed is software risk identification. The required concepts, the semantic description of the concepts and the interrelationship among the concepts along with all other ontological components have been collected from various literatures and experience of the people from software industry. From which, a taxonomy has been constructed by using the property ‘isA’ and the design architecture for the required ontology has also been sketched out manually with nearly four different types of properties. In order to reduce implementation efforts, the Protégé platform, a scalable and integrated framework for ontological engineering, has been used to construct the ontology. The constructed ontology has been represented in owl format, which makes it more machine understandable. Then the semantic representation of the knowledge has been made using the OWL document generator, which automatically generates a set of documents from the ontology. In order to understand the knowledge in more detailed way again the ontology has been visualized using ontoviz tool.


  • Boyce, S., and Pahl, C. 2007, Developing Domain Ontologies for Course Content, Educational Technology & Society, 10 (3), 275-288.
  • Burton-Jones, A., Storey, V.C., Sugumaran, V., and Ahluwalia, P. 2005, “A semiotic metrics suite for assessing the quality of ontologies,” Data & Knowledge Engineering (55:1), PP. 84-102.
  • Christopher Brewster, Kieron O’Hara, 2007, Knowledge representation with ontologies: Present challenges—Future possibilities, Int. J. Human-Computer Studies, 65, 563–568.
  • Colin Batchelor. 2008, An Upper Level Ontology for Chemistry, Formal Ontology in Information Systems, Proceedings of the Fifth International Conference. FOIS, ISSN 0922-6389.
  • Daconta, M. C., Obrst, L. J., & Smith, K. T. 2003, The Semantic Web – a Guide to the Future of XML, Web Services, and Knowledge Management, Indianapolis, USA: Wiley & Sons.
  • Dean. M, G. Schreiber (eds), et al, “OWL Web Ontology Language Reference “
  • A. Grigoris, H.Frank van. 2003. Web Ontology Language: OWL. Handbook on Ontologies in Information Systems. Springer-Verlag.
  • Hong Zhu and Qingning Huo, 2004, Developing A Software Testing Ontology in UML for A Software Growth Environment of Web-Based Applications, available at
  • Huan Wang, Xing Jiang, Liang-Tien Chia and Ah-Hwee Tan, 2010. Wikipedia2Onto – Building Concept Ontology Automatically, Experimenting with Web Image Retrieval, Informatica, 34, 297-306.
  • Ling Jiang, Chengling Zhao, Haimei Wei, 2008. The Development of Ontology-Based Course for Computer Networks, International Conference on Computer Science and Software Engineering, Vol. 5, PP.487-490.
  • Marko Grobelnik, Janez Brank, Blaž Fortuna and Igor Mozetič, 2008, Contextualizing Ontologies with OntoLight: A Pragmatic Approach, Informatica, Vol. 32, PP 79–84.
  • Marvin. J.Carr, S. L. Konda, I. Monarch, F. C. Ulrich, C. F. Walker, 1993. Taxonomy-Based Risk Identification, Software Engineering Institute Technical Report, Carnegie Mellon University, Pittsburgh, Pennsylvania.
  • D. McGuinness and F. van Harmelen, 2003, OWL Web Ontology Language Overview, available at
  • Mizoguchi, R. & Bourdeau, J. 2000. Using ontological engineering to overcome common AI-ED problems. International Journal of Artificial Intelligence in Education, Vol. 11(2), PP 107-121.
  • P. Patel-Schneider, P. Hayes, I. Horrocks. 2003. OWL Web ontology Language Semantics and Abstract Syntax, available at
  • Pornpit Wongthongtham, Elizabeth Chang, Tharam Dillon, Ian Sommerville, 2009. Development of a Software Engineering Ontology for Multisite Software Development, IEEE Transactions on Knowledge and Data Engineering, Vol. 21, No. 8, PP. 1205-1217.
  • Rajiv Pandey and Sanjay Dwivedi, Ontology Description using OWL to Support Semantic Web Applications, International Journal of Computer Applications 14(4):30–33, January 2011, Published by Foundation of Computer Science.
  • C.R.Rene Robin, G.V.Uma, 2010. Ontology Based Semantic Knowledge Representation for Software Risk Management, International Journal of Engineering Science and Technology, Vol. 2, No.10, PP. 5611-5617.
  • Sergey Sosnovsky, Tatiana Gavrilova, 2005. Development of Educational Ontology for C-Programming, Proceeding of XI-th International Conference on Knowledge - Dialogue - Solution, Volume 1, Pg. 127-131.
  • M. Smith, C.Welty, D. McGuinness, 2003. OWL Web Ontology Language Guide, available at
  • Sowa, J. F. 2000. Knowledge Representation – Logical, Philosophical, and Computational Foundations, Pacific Grove, CA, USA: Brooks/Cole.
  • Stamper R., Liu K., Hafkamp M., and Ades Y. 2000. Understanding the role of signs and norms in organisations – a semiotic approach to information systems design, Behaviour & Information Technology (19:1), PP. 15-27.
  • Y.Wand, V.C.Storey, and R.Weber. 1999. An Ontological Analysis of the Relationship Construct in Conceptual Modeling, ACM Transaction on Database Systems, Vol. 24, No. 4, PP. 495-528.
  • Yoshihito Takahashi, Tomomi Abiko, Eriko Negishi, Goichi Itabashi, Yasushi Kato, Kaoru Takahashi, Norio Shiratori, 2005. An Ontology-Based e-Learning System for Network Security, 19th International Conference on Advanced Information Networking and Applications, Vol.1, PP.197-202.