Transportation: An Overview from Open Data Approach

Abstract

The increasing urban population sets new demands for mobility solutions. The impacts of traffic congestions or inefficient transit connectivity directly affect public health (emissions, stress, for example) and the city economy (deaths in road accidents, productivity, commuting, etc). In parallel, the advance of technology has made it easier to obtain data about the systems which make up the city information systems. The result of this scenario is a large amount of data, growing every day and requiring effective handling in order to be transformed into integrated and useful information. This article aims to analyze the urban public transportation from the perspective of open data and data science. We focus on data integration challenges for smart city applications and present an use case of data usage to speed limit enforcement. We also present an initial comparative analysis of New York and Curitiba data collection and processing approaches. The results unveil challenges to overcome regarding file formats, reference systems, precision, accuracy and data quality, among others, that still need effective approaches to easy open data exploitation for new services. We discuss data characteristics that can possibly be used to optimize public transportation systems aiming at standards for transportation data worldwide.