Public transportation data is highly public in nature, and much of the public transportation services are operated by the public sector and private companies. Today, they are providing information services such as transfer guidance services based on timetables, and operational information services such as delays and service troubles. For buses, some operators are providing location information and operational information in real time by so-called bus location systems.
Tokyo and other mega-cities have huge and complicated networks of public transportation consisting of hundreds of railway stations, thousands of bus stops and routes, many operators, and so on. In this case, open data is the best and only approach for providing integrated information of the public transportation networks.
On the other hand, for monitoring real-time public transportation information such as location of trains and/or busses, we also need IoT technologies on top of open data. So, integrated public transportation information services are good use cases for using both open data technologies and IoT technologies. For example, in this project, we use an RDF model based on the LOD technology for the data model, ucode system developed by Ubiquitous ID Center, SPARQL and RESTful API with JSON format, and special new vocabulary for expression of public transportation data.
This use case trial shall be performed in Tokyo Area with the support of the “Consortium of Open Data for Public Transportation” (ODPT).
Two user interfaces will be provided: one for end users of the information service and one for software and service developers.
The end-user interface will be provided as a mobile web application. Figures 1 and 2 are prototype images of the end-user interface of our public transportation information services using open data and/or private data. Figure 3 shows a prototype of the developers’ web site.