Demo awarded 2nd Place at the DataSpark Mobility Challenge organized by the International Conference on Information and Knowledge Management (CIKM) - Singapore, Nov. 2017
Background: The availability of massive datasets describing human mobility offer the possibility to monitor and improve the resilience of transportation systems to traumatic events such as disasters of natural or anthropocentric origin. In this perspective, we propose a visual, data-driven and network-based simulation tool based on a multiplex network representation of mobility data, where every layer describes movement of people’s with a given trans- portation mode. We then develop a visual analytics tool which provides an easy-to-use interface to explore the mobility uxes and the connectivity of every urban zone in a city. Our visual analytics tool allows the user to visualize changes in the transportation system resulting from the addition or removal of transportation modes, urban zones and single stops. We show how our visual system can be used to explore mobility in Singapore, by using data provided by the CIKM challenge 2017 and Singapore mobility data obtained from external sources. e system allows to simulate the reaction to changes in the Singapore’s public trans- portation system, such as closing/adding transportation modes or subway/bus stops.