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A Smart Ontology for Project Risk Management Based on PMI’s Framework

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Proceedings of Fifth International Congress on Information and Communication Technology (ICICT 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1183))

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Whenever Project Risk (PR) exists, there is complexity. The difficulty to make concerned decisions related to Project Risk Management (PRM) increases project complexity and even its failure. In order to assist practitioners and professionals to better study the potential impacts of their decisions and assess the PR as precisely as possible, this chapter put forward an ontological approach based on OWL ontology with SWRl rules, that provides the project team clear guidelines to effectively manage PR, and then make the appropriate decisions based on the right recommendations. This approach takes advantages of ontology semantic strengths as it represents a unified PRM knowledge relying on PMI’s frameworks. As well, through SWRL reasoning rules, the proposed ontology generates recommendations by which a team member ask for risk-related request more targeted. The proposed ontological approach was evaluated, in term of content and structure, achieving promising results based on the F-measure metric.

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  1. Palmer, C., et al.: An ontology supported risk assessment approach for the intelligent configuration of supply networks. J. Intel. Manuf. 29(5), 1005–1030 (2018)

    Google Scholar 

  2. Manotas-Niño, V., et al.: Towards a model of integration between risk management and lesson learning system for project management. In: 2015 International Conference on Industrial Engineering and Systems Management (IESM). IEEE (2015)

    Google Scholar 

  3. Pittl, B., Fill, H.-G., Honegger, G.: Enabling risk-aware enterprise modeling using semantic annotations and visual rules (2017)

    Google Scholar 

  4. El Yamami, A., et al.: Representing IT projects risk management best practices as a metamodel. Eng. Technol. Appl. Sci. Res. 7(5), 2062–2067 (2017)

    Google Scholar 

  5. de Gusmão, C.M.G., de Moura, H.P.: Multiple risk management process supported by ontology. In: International Conference on Product Focused Software Process Improvement. Springer, Berlin, Heidelberg (2006)

    Google Scholar 

  6. Dikmen, I., Talat Birgonul, M., Fidan, G.: Assessment of project vulnerability as a part of risk management in construction. In: Proceedings of Joint 2008 CIB W065/W055 Symposium (2008)

    Google Scholar 

  7. Fidan, G., et al.: Ontology for relating risk and vulnerability to cost overrun in international projects. J. Comput. Civil Eng. 25(4), 302–315 (2011)

    Google Scholar 

  8. Studer, R.V., Benjamins, R., Fensel, D.: Knowledge engineering: principles and methods. Data Knowl. Eng. 25(1–2), 161–197 (1998)

    Google Scholar 

  9. Wang, H.-H., Boukamp, F.: Ontology-based representation and reasoning framework for supporting job hazard analysis. J. Comput. Civil Eng. 25(6), 442–456 (2011)

    Article  Google Scholar 

  10. Zhong, Botao, Li, Yong: An ontological and semantic approach for the construction risk inferring and application. J. Intell. Rob. Syst. 79(3-4), 449–463 (2015)

    Article  Google Scholar 

  11. Wang, H., et al.: Research on ontology-based knowledge presentation and reasoning in civil aviation emergency decision. Comput. Eng. Sci. 33(4), 129–133 (2011)

    Google Scholar 

  12. Emmenegger, S., Laurenzini, E., Thönssen, B.: Improving supply-chain-management based on semantically enriched risk descriptions. In: KMIS (2012)

    Google Scholar 

  13. Fernández-López, M., Gómez-Pérez, A., Juristo, N.: Methontology: from ontological art towards ontological engineering (1997)

    Google Scholar 



  16. Sirin, E., et al.: Pellet: a practical owl-dl reasoner. Web Semantics: science, services and agents on the World Wide Web 5(2), 51–53 (2007)

    Google Scholar 

  17. Guo, B.H.W., Goh, Y.M.: Ontology for design of active fall protection systems. Autom. Const. 82, 138–153 (2017)

    Google Scholar 

  18. Brewster, C., et al.: Data driven ontology evaluation (2004)

    Google Scholar 

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Correspondence to Wiem Zaouga .

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Zaouga, W., Rabai, L.B.A. (2021). A Smart Ontology for Project Risk Management Based on PMI’s Framework. In: Yang, XS., Sherratt, R.S., Dey, N., Joshi, A. (eds) Proceedings of Fifth International Congress on Information and Communication Technology. ICICT 2020. Advances in Intelligent Systems and Computing, vol 1183. Springer, Singapore.

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  • Print ISBN: 978-981-15-5855-9

  • Online ISBN: 978-981-15-5856-6

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