Abstract

The interactive visualization system bikesharingatlas.org supports the explorative data analysis of more than 460 bike-sharing networks worldwide. Being increasingly digitized, these networks nowadays produce data that can reveal interesting insights, not only into patterns of bicycle usage but also underlying spatio-temporal dynamics of a city. We recorded this data from several hundred networks worldwide, over a period of 17 months, and made it publicly accessible through a common web platform. The application leverages a multi-coordinated view approach and innovative interaction techniques can help, for instance, to expose capacity bottlenecks, commuting patterns, and other network characteristics. Our broader goal was to illustrate how visual analysis can be used for exploring distributed, heterogeneous data from smart cities.