This paper presents a cloud service-oriented approach for managing and analysing big data required by transport applications. Big data analytics brings new insights and useful correlations of large data collections providing undiscovered knowledge. Applying it to transport systems brings better understanding to the transport networks revealing unexpected choking points in cities. This facility is still largely inaccessible to small companies due to their limited access to computational resources. A cloud-oriented architecture opens new perspectives for providing efficient and personalised big data management and analytics services to (small) companies.

The authors would like to thank the region Rhône-Alpes who finances the thesis work of Gavin Kemp by means of the ARC seven programs (http://www.arc7-territoires-mobilites.rhonealpes.fr/).

intelligent transport system,big data,cloud services,NoSQL

• Ciências da Computação e da Informação - Ciências Naturais
• Engenharia Eletrotécnica, Eletrónica e Informática - Engenharia e Tecnologia