A visual analytics design for studying crowd movement rhythms from public transportation data

Human lives involve various daily movements in a space-time context, which exhibit high regularity that typically forms circadian rhythms. Understanding the rhythms for human daily movements of massive crowds can be highly beneficial for a variety of applications, such as traffic demand management and urban planning. In this paper, we propose an interactive visual data analysis approach, which provides not only quantitative analyses, including frequent human movement rhythms identification, but also visualization supported with a family of user interactions. We also devise a set of interactive visual query methods for users to easily explore the movement rhythms over space and time. Case studies with real-world massive urban public transportation data in Singapore, and interviews with transportation researches are carried out to demonstrate the effectiveness and usefulness of our system.