Abstract
Smart cities evolution forces auto adjustments. A constant change that difficult methodologies and tools development aimed to measure and evaluate the huge number of variables involved. The Smart City metrics model is composed by its determined key performed indicators (KPI); with different aims a number of models have been proposed by different organizations, which difficult its comparison. In this paper, we propose a framework to apply Data Science to KPIs from Open Data. This framework is organized by a set of tools: a KPI tree structure; a JSON document; a web app with non-supervised or supervised knowledge for the models evaluation; and the infrastructure for reports reception and attention. In such a way that this framework creates an infrastructure that goes from the treatment of Open Data to models evaluation and its management.
The original version of this chapter was revised: The author name “Graciela López Lara” has been changed to “Graciela Lara López”. The correction to this chapter is available at https://doi.org/10.1007/978-3-030-01171-0_27
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02 December 2018
In the original version of the book, the following belated correction have been incorporated:
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Estrada, E., Maciel, R., Peña Pérez Negrón, A., Lara López, G., Larios, V., Ochoa, A. (2019). Framework for the Analysis of Smart Cities Models. In: Mejia, J., Muñoz, M., Rocha, Á., Peña, A., Pérez-Cisneros, M. (eds) Trends and Applications in Software Engineering. CIMPS 2018. Advances in Intelligent Systems and Computing, vol 865. Springer, Cham. https://doi.org/10.1007/978-3-030-01171-0_24
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DOI: https://doi.org/10.1007/978-3-030-01171-0_24
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