Abstract
This paper evaluates the use of Business Intelligence(BI)technologies as a viable approach to the efficient engineering, update and evolution of Multipurpose Technical Cadastres (MTC) in the context of Land Information Systems (LIS). For this, the MTC of a small Brazilian city named Ouro Preto, located in the Minas Gerais state, has been built as a spatiotemporal data warehouse and BI tools have been used to developing the LIS. The system architecture, conceptual data model and tools are presented. Evaluation experiments have shown that, in two months, 92% of 3,037 realties registered in the study area have been correctly georeferenced and associated to legated information systems. We estimate that fifty percent of project investments will be recovered in the first year in which the LIS will be used to collect taxes and tributes.
Resumo. Este artigo avalia o uso de tecnologias de Inteligência de Negócios (BI) como uma abordagem viável para a construção, atualização e evolução eficiente de um Cadastro Técnico Multifnalitário (CTM) no contexto de Sistemas de Informação Territorial (SIT). Para isso, o CTM do município Ouro Preto, MG, foi construído como um armazém de dados espaço-temporal e ferramentas de BI foram utilizadas para o desenvolvimento do SIT. A arquitetura, modelos conceitual de dados e ferramentas desenvolvidas são apresentadas. Análises mostram que, em dois meses, 92% dos 3.037 imóveis registrados na área de estudo foram corretamente georreferenciados e associados a informações de sistemas legados. Estima-se que os investimentos no projeto sejam recuperados após o primeiro ano de uso para cobranças de taxas e impostos.
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Silva, J.T.C. et al. (2012). SIGHabitar – Business Intelligence Based Approach for the Development of Land Information Systems: The Multipurpose Technical Cadastre of Ouro Preto, Brazil. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31075-1_23
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DOI: https://doi.org/10.1007/978-3-642-31075-1_23
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