Abstract Bike-sharing systems are a popular mode of public transportation, increasing in number and size around the world. Public bike-sharing systems attend to the needs of a large number of commuters while synchronizing to the rhythm of big cities. To better understand the usage of such systems, we introduce an interactive visualization system to explore the dynamics of public bike-sharing systems by profiling its historical dataset. By coordinating a pixel-oriented timeline with a map, and introducing a scheme of partial reordering of time series, our design supports the identification of several patterns in temporal and spatial domains. We take New York City׳s bike-sharing program, Citi Bike, as a use case and implement a prototype to show changes in the system over a period of ten months, ranking stations by different properties, using any time interval in daily and monthly timelines. Different analyses are presented to validate the visualization system as a useful operational tool that can support the staff of bike-sharing programs of big cities in the exploration of such large datasets, in order to understand the commuting dynamics to overcome management problems and provide a better service to commuters.