MobVis: A Framework for Analysis and Visualization of Mobility Traces

Due to the increasing location-aware devices, mobility traces datasets have become an essential source for smart cities planning. Given this scenario, we propose MobVis, a framework to characterize mobility traces through different metrics, allowing comparisons between different mobility traces in a simplified way. Furthermore, MobVis can extract and visualize spatial, temporal, and social aspects of mobility data through a Web interface. MobVis architecture has five main components: input data; data preparation; data processing and analysis to extract mobility metrics; visualization; and a web interface. To demonstrate the framework's process, we created a use case analyzing the characteristics of two distinct traces (Taxi and IoT-Objects). Then, through different metrics, we evaluated the data in two aspects: i) descriptive, through a set of graphics and quantitative data that enables characterizing each trace; and ii) comparative, presenting the main differences between the traces.