General Research
RESEARCH
KOTI - Korea Transport institute
Studies on Developing Transport Big Data Platform and its Application
- Date
November 30 2017
- Page(s)
page(s)
Transport big data platform is a physical and virtual environment in which one user could share transport and transport-related big data with other users. In the platform, big data from one source are collected, processed, analyzed and integrated with big data from other sources. Given that a transport big data platform facilitates the utilization of public and private data and improves the efficiency of data analysis, it could be a powerful platform for data ecosystems.
To begin with, transport big data platforms have an advantage over existing data platforms in that they could induce the integration of public data in transport and transport-related sectors. In Korea, it is true to say that there are many data platforms which are separately operated and not connected with other ones. If those platforms are connected and integrated into one system in which big data could be collected, processed, analyzed and utilized, it is expected that data sharing will be easier and quicker. This would make data fusion and convergence more effective.
In addition, transport big data platforms are needed to be sure of data in private sectors. Data from navigation devices, smart phones, and transit cards are the most frequently mentioned and utilized, and also largely produced and collected in the private sector. As there is a cognizance that such data are looked upon as the property or asset of a private company, it is not easy to persuade private companies to share data managed by them. Furthermore, because some data are traded expensively, general public who have low purchasing power are usually restricted from accessing private data. To tackle this obstacle, the public sector including government agencies in an agreement with private companies could purchase private data and share it within a transport big data platform.
Last but not least, the true and valuable insights from big data are a result of data convergence, and data standardization is a prerequisite for this convergence. Data which are produced by different agencies inevitably have a variety of features in terms of type and content. The inconsistency from those sets could lead to increasing the time and cost of data processing. If data standardization is considered and executed in the stage of data collection and storage, the time and cost of data processing might be reduced, resulting in the improvment data utilization efficiency. It is expected that data standardization is naturally achieved within transport big data platforms in which data are treated as one.
To begin with, transport big data platforms have an advantage over existing data platforms in that they could induce the integration of public data in transport and transport-related sectors. In Korea, it is true to say that there are many data platforms which are separately operated and not connected with other ones. If those platforms are connected and integrated into one system in which big data could be collected, processed, analyzed and utilized, it is expected that data sharing will be easier and quicker. This would make data fusion and convergence more effective.
In addition, transport big data platforms are needed to be sure of data in private sectors. Data from navigation devices, smart phones, and transit cards are the most frequently mentioned and utilized, and also largely produced and collected in the private sector. As there is a cognizance that such data are looked upon as the property or asset of a private company, it is not easy to persuade private companies to share data managed by them. Furthermore, because some data are traded expensively, general public who have low purchasing power are usually restricted from accessing private data. To tackle this obstacle, the public sector including government agencies in an agreement with private companies could purchase private data and share it within a transport big data platform.
Last but not least, the true and valuable insights from big data are a result of data convergence, and data standardization is a prerequisite for this convergence. Data which are produced by different agencies inevitably have a variety of features in terms of type and content. The inconsistency from those sets could lead to increasing the time and cost of data processing. If data standardization is considered and executed in the stage of data collection and storage, the time and cost of data processing might be reduced, resulting in the improvment data utilization efficiency. It is expected that data standardization is naturally achieved within transport big data platforms in which data are treated as one.