Analysing public transport data through the use of big data tecnhologies for urban mobility

Over the last years, new strategies focusing on mobility have been implemented, especially in big urban areas, in order to solve the mobility problems brought by the urban exodus. The demand for different mobility modes, leads to a complex transportation network that needs to adapt to different mobility requirements. The presented work analyses the current situation of the transportation network of Lisbon's area, where mobility means are provided by different transport operators, private and public, serving a population of around 4M people. The challenge addressed by this work, is to analyze the demand and supply side of the transportation network of Lisbon's metropolitan area, considering ticketing data transactions provided by different transportation operators, which until now, such analyses were essentially obtained through observation methods and questionnaires. This paper explores the ability of Big Data technologies to cope with data collected from transport operators, by inferring automatically and continuously complex mobility patterns in the form of insightful indicators (such as connections, transshipments or pendular movements).