ONTOVID - Uma Abordagem para Construção de Grafos de Conhecimento Semântico com Enfoque em Notificações e Óbitos Relacionados ao Novo Coronavírus (COVID-19)
Abstract
Brazilian municipalities face many difficulties in obtaining strategic information that enables decision-making due to the decentralized management model and the lack of interoperable systems that allow complex analyses. With the novel coronavirus (COVID-19) pandemic, obtaining data quickly and reliably has become even more necessary due to the escalation of the disease and the need for rapid interventions. Therefore, this work, through the construction of Semantic Knowledge Graphs (SGG), which integrated the SIM databases (MIS Mortality Information System) and the e-SUS System (COVID Notifications), had as its main objective to mitigate the deficiencies arising from the extraction of important indicators on deaths, vaccinations, and hospitalizations. For the construction of ONTOVID, the NeOn methodology and the OBDI (Ontology-Based Data Integration) approach were used to integrate the bases. As a way of evaluating the accuracy of this automatic approach, the data obtained in the integration were presented and validated by the managers of the Camaçari Health Department, who identified some divergences not detected by the manual process of collecting information previously carried out by the team.
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