Uma abordagem de integração semântica para o observatório de dados abertos do sertão dos Crateús

Abstract

Access to information is a fundamental right, and government transparency is an essential element to ensure citizen participation in public management. Brazil’s Access to Information Law guarantees the constitutional right to access information, where the provision of information through open data is a requirement for compliance with this legislation. In the western region of the state of Ceará, there is the Observatório de Dados Abertos do Sertão dos Crateús, an initiative under development at the Universidade Federal do Ceará, which aims to increase transparency and social control of public data from the cities that make up the region. However, the data provided by the sources used in the Observatory are structured in a heterogeneous manner, making their understanding and reuse difficult. Therefore, the creation of a unified structure that facilitates the interpretation and reuse of data is the main objective of this research. To achieve this objective, a methodology was implemented to integrate the heterogeneous data of the Observatory through Semantic Web, where ontology expansion, data collection and processing, mapping to the expanded ontology, and data integration and correlation were components of the approach. The data used in this research come from distinct and external databases used by the Observatory, related to COVID-19 cases and mortality rates according to the International Classification of Diseases (ICD-10). Beyond the integration of information, this research sought to verify the correlation of COVID-19 cases with the mortality rates recorded in 2020 from other respiratory diseases. After applying the methodology and integrating the information, statistical analysis using Pearson’s correlation coefficient revealed a very weak correlation between the number of COVID-19 cases and mortality from other respiratory diseases in the analyzed scenarios. With the results obtained, it is concluded that the semantic integration of data, through the methodology used, is feasible and can promote greater transparency of public information and reveal the correlation of integrated data in other Open Data Observatories.