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The Public Transportation System and its operation management require the processing of large amount of data (like bus routes, user data and bus schedules). In particular, origin-destination data serves to indicate citizens’ travel patterns, providing insights related to the dynamic of the urban space occupation. Given this scenario, this paper presents a prototype of origin-destination data visualization, maintaining the spatial and temporal context. The novelty relies on visualization through clustering of georreferenced data, allowing the analysis of different regions of interests (neighborhood, regionals or mathematical regions using K-means algorithm). We demonstrate the prototype through several scenarios, and interviews done to local citizens.Challenges related to meaningful presentation of results are discussed under the perspective of visualization and analytics.