Abstract
Prevention is a pervasive phenomenon. It is about blocking an effect before it happens or stopping it as it unfolds: vaccines prevent (the unfolding of) diseases; seat belts prevent events causing serious injuries; circuit breaks prevent the manifestation of overcurrents. Many disciplines in the information sciences deal with modeling and reasoning about prevention. Examples include risk and security management as well as medical and legal informatics. Having a proper conceptualization of this phenomenon is crucial for devising proper modeling mechanisms and tools to support these disciplines. Forming such a conceptualization is a matter of Formal Ontology. In fact, prevention and related notions have become a topic of interest in this area. In this paper, with the support of Unified Foundational Ontology (UFO), we conduct an ontological analysis of this and other related notions, namely, the notions of countermeasures and countermeasure mechanisms, including the notion of antidotes. As a result of this conceptual clarification process, we propose an ontology-based reusable module extending UFO and capturing the relations between these elements. Finally, we employ this module to address a few cases in risk management.
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Notes
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It also includes a reference to another semi-saturated type South-Tyrolean City.
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According to our model, vulnerabilities, capacities and intentions of a certain type are mutual activation partners!.
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A single virus cannot infect anyone; infectibility is a disposition of a virus collective.
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UFO does not make such a commitment. The reasons are related to the fact that dispositions and qualities interact in different levels. For instance, the crystalline structure of sugar is itself grounded on the disposition of the molecules constituting sugar to bind a specific way. Moreover, as discussed before, the distinction between qualitative/categorical and disposition properties is not settled in the literature.
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Work supported by Accenture Israel Cybersecurity Labs.
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Baratella, R., Fumagalli, M., Oliveira, Í., Guizzardi, G. (2022). Understanding and Modeling Prevention. In: Guizzardi, R., Ralyté, J., Franch, X. (eds) Research Challenges in Information Science. RCIS 2022. Lecture Notes in Business Information Processing, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-031-05760-1_23
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