Open Data Extraction, Transformation, and Loading as a Tool for Supporting 2018 Elections' Voters

Autor: Hendrik T. Macedo, Gilton José Ferreira da Silva, Leonardo Nogueira Matos, Bruno O. Prado, Ariel F. Rodrigues, Nélson Rangel Santos Passos
Rok vydání: 2019
Předmět:
Zdroj: SBSI
DOI: 10.1145/3330204.3330232
Popis: Democracy is a political regime based on the majority's choice. However, people can only make conscious decisions if they have access to high quality information. This paper aimed to join data from different sources and to transform them in knowledge to Brazilians voters. It applied ETL (Extract, Transform, Load) methods on open and property data to build a process that covers data gathering and transformation, dataset generation, database modeling and population, public APIs development, and a mobile app as the knowledge's visualization model. As a result, for 2018 Brazil's general elections, it processed almost two million candidacies, half a million deputies' tasks and five thousand court lawsuits. Furthermore, the products released by this research reached good performance indicators: the access logs recorded more than three million hits for the public API and twelve thousand downloads for the mobile app in the last week of the first-round's political campaign.
Databáze: OpenAIRE