Modelo para análise visual de dados multivariados no contexto geoespacial

• Autor(a) principal: Signoretti, Wagner Golçalves
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da PUC_RS
• Texto Completo: http://tede2.pucrs.br/tede2/handle/tede/8916
• topic: Visualização de Dados; Dados Geoespaciais; Dados Multivariados; Data Visualization; Geospatial Data; Multivariate Data; CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO

With the popularity of mobile phones, GPS and other technologies, we observe an increase in the amount of geospatial data that are daily generated. We can find datasets with several attributes associated to specific geographic coordinates, such as open government, meteorological and social network data. The visualization of geospatial data facilitates to communicate how different variables correlate to geographical locations by layering these variables over maps. However, the visualization of several variables associated with a specific location is not a trivial task. Thus, we need alternatives to contribute to the data analysis and knowledge discovery. The main goal of this work is to present a new model for visual analysis of geospatial multivariate data, which integrates a map with clustered charts and coordinated multiple views representing the values of each different attribute. This model offers a way to interactively apply different filters and analyze several attributes, updating all the related visual representations. Our main contribution is this new model proposition and its application to different open government datasets.