KOTI - Korea Transport institute

Big data and its analysis methodology are widespread for supporting decision-making in various fields. This report will cover how big data is applied in general and how it would be applied in the transport field to support transportation policy and decision making. Big data does not mean predefined data structure or analytic methodology. Instead it would imply different methodology to produce new values by relating or fusing the data in diverse fields. As a result, big data could be applied for future prediction and preparation, productivity and efficiency improvement of the organization, or the development of a new system that has never been experienced. New technologies to connect between primitive big data and highly-customized real-time services are rapidly developed and evolved in real life. In the area of transport, smartcard usage and trip information from GPS units such as SK T map real-time information could be regarded as big data in the transport field. But this data has limitations as it is inherited information for private or location issues. To reduce these limitations a revision of public data law might need discussion: privately collected data that has the potential to be used for public purpose. In this research, smart card data and vehicle GPS data are analyzed and reviewed to improve transport policies. Rather than being the goal, big data is a new methodology or tool for resolving social issues. Therefore it is necessary to redefine transport issues macroscopically with an insightful eye and fuse big data of diverse fields to extract new perspectives. Traditional traffic data collected by the public or private sector is used for a dedicated purpose and then disposed of. Now it is necessary to collect and archive this data, to develop specialists to process and analyze this data, and to establish a data center to coordinate these tasks