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On the Semantics of Risk Propagation
Conference proceeding   Peer reviewed

On the Semantics of Risk Propagation

Mattia Fumagalli, G Engelberg, Tiago Prince Sales, Italo José Da Silva Oliveira, D Klein, P Soffer, Riccardo Baratella and Giancarlo Guizzardi
Research Challenges in Information Science: Information Science and the Connected World: 17th International Conference, RCIS 2023, Corfu, Greece, May 23–26, 2023, Proceedings, Vol.476, pp.69-86
Lecture Notes in Business Information Processing, 476
17th International Conference on Research Challenges in Information Science (RCIS 2023) (Corfu, 23/05/2023–26/05/2023)
2023
Handle:
https://hdl.handle.net/10863/51489

Abstract

Ontological Analysis Risk modeling Risk propagation
Risk propagation encompasses a plethora of techniques for analyzing how risk “spreads” in a given system. Albeit commonly used in technical literature, the very notion of risk propagation turns out to be a conceptually imprecise and overloaded one. This might also explain the multitude of modeling solutions that have been proposed in the literature. Having a clear understanding of what exactly risk is, how it be quantified, and in what sense it can be propagated is fundamental for devising high-quality risk assessment and decision-making solutions. In this paper, we exploit a previous well-established work about the nature of risk and related notions with the goal of providing a proper interpretation of the different notions of risk propagation, as well as revealing and harmonizing the alternative semantics for the links used in common risk propagation graphs. Finally, we discuss how these results can be leveraged in practice to model risk propagation scenarios.
url
https://doi.org/10.1007/978-3-031-33080-3_5View

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