Authors:
Ruba Al Khalaf
1
;
Anna Bernasconi
1
and
Alberto García S.
2
Affiliations:
1
Politecnico di Milano, Milan, Italy
;
2
Universitat Politècnica de València, Valencia, Spain
Keyword(s):
Ontological Analysis, OntoUML, SARS-CoV-2, Variants Impacts.
Abstract:
The SARS-CoV-2 virus continuously accumulates genetic variation through mutations; mutations are the virus’ way to achieve viral adaptation. Although the huge amount of information accumulated on the virus during the COVID-19 pandemic, the knowledge that contributes to explaining and supporting the research related to SARS-CoV-2 characteristics and evolution is not currently organized, nor systematized. Here, we present OntoEffect, an ontology that captures and represents such information systematically. Specifically, we aim to represent the dimensions of the virus and its mutations, discussing their impacts on the virus itself, as well as on public health, prevention, and treatment protocols. Aiming to obtain ontological clarity in such a complex domain, OntoEffect was built using OntoUML, an ontology-driven conceptual modeling language, grounded on the Unified Foundational Ontology (UFO). In the highly specialized context of virology, we show the powerful ability of ontological mod
els to provide clear and precise explanations of a domain and allow its shared understanding among stakeholders.
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