Big Data in Transport

Deliverable 1.1 Understanding and Mapping Big Data in Transport Sector

European Union’s Transport policy’s pivotal aim is to strengthen the existing Transport infrastructure, which is crucial to economic development. The improvement in the transport sector should provide efficient logistics of goods, better travel and commuting facilities, and accessibility of the European region. This report, as part of the first phase of the Leveraging Big Data to Manage Transport Operations (LeMO) project, provides an introduction to big data in the transport sector. It identifies untapped opportunities and challenges and describes numerous data sources. This report is a part of WP1 which is a cornerstone of the LeMO project. It aims to generate a shared understanding of current big data landscape in transport and identifies a holistic view on opportunities, challenges, and limitations. The remainder of this report is structured as follows: Chapter 2 explores the characteristic of big data and highlights the big data challenges in the transport sector. It covers six transportation modes (air, rail, road, urban, water and multimodal) and two transportation sectors (passenger and freight). Chapter 3 identifies several opportunities and challenges of big data in transportation, by using: several subject matter expert interviews, nineteen applied cases, and a literature review. It also indicates that the combination of different means and approaches will enhance the opportunities for successful big data services in the transport sector. Chapter 4 offers an intensive survey of the various data sources, data producers, and service providers. In addition, cartography was modeled to visualize data flows intuitively. Cartography demonstrates where data originated from and where it is flowing to. Chapter 5 summarizes all findings and provides a conclusion