Worldwide Subway Systems: Data Extraction, Topology, and Resilience

Abstract

Understanding and improving urban transportation networks is one of the key challenges in the 21st century, since the economy of a region largely depends on its accessibility. Existing studies on urban transport usually collect data by hand or directly receive them from network operators; making the data inaccessible for other researchers. This has three consequences: First, researchers spend a significant amount of time to obtain the data. Second, experiments often cannot be reproduced without having the same dataset. Third, results obtained for one network cannot be transferred to other networks easily. In this study, we use public available data from Openstreetmap to extract the subway networks for more than 150 cities worldwide, and propose several techniques to solve data inconsistency problems. Moreover, we investigate the potential of this data for urban complex network research and provide a preliminary comparison of the topology and the resilience of subway networks. Our work contributes towards understanding and improving cities’ infrastructure from a complex network point of view.