SemanticSefaz: An ontology-based semantic portal for the government spending

  • Tulio V. Rolim UFC
  • Vânia P. Vidal UFC
  • Caio Viktor S. Avila UFC
  • Matheus M. L. da Cruz UFC
  • Matheus G. P. Barrio UFC
  • Daniel Queiroz UFC


Supervision in the public procurement process is considered essential for society as a means of promoting greater security and control against possible fraud and illegal actions. However, the data available on government procurement alone does not allow for the identification of possible signed contracts or bidding processes won by unfit or suspended companies, making it difficult to analyze and supervise by employees of tax agencies such as SEFAZ. In addition, data are often not available in the same common format and differ in their vocabulary, making it difficult for these professionals to find interesting information. As a means of solving these problems, the present work presents SemanticSefaz, a semantic portal for integration between heterogeneous bases focused on the domain of public procurement through a homogeneous view, allowing for semantic queries and subsequent discovery of information that priori were not possible. As a case study, the databases with data on government procurement (SIASG), unhealthy and suspenseful companies (CEIS) and punished companies (CNEP) were used to construct semantic integration. Subsequently, queries of interest to the tax domain were conducted through SemanticSefaz, demonstrating its efficiency for performing faceted queries and semantic navigation. In the end, SemanticSefaz is characterized as a timely tool for integration, visualization, discovery of knowledge to facilitate the work of tax professionals.
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ROLIM, Tulio V.; VIDAL, Vânia P.; AVILA, Caio Viktor S.; CRUZ, Matheus M. L. da; BARRIO, Matheus G. P.; QUEIROZ, Daniel. SemanticSefaz: An ontology-based semantic portal for the government spending. In: SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 25. , 2019, Rio de Janeiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 493-496.