Smart transportation systems have been providing more data over time (such as bus routes, users, smartphones, etc.). Such data provides a number of opportunities to identify various facets of user behavior and traffic trends. In this paper we address some of the urban mobility challenges (already discussed by the Brazilian Computer Society), from a number of different perspectives, including (i) pattern discovery, (ii) statistical analysis, (iii) data integration, and (iv) open and connected data. In particular, we present an exploratory data analysis with GIS for public transportation toward a case study in Curitiba, Brazil.