Journal cover Journal topic
Proceedings of the ICA
Journal topic
Volume 2
Proc. Int. Cartogr. Assoc., 2, 116, 2019
https://doi.org/10.5194/ica-proc-2-116-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Proc. Int. Cartogr. Assoc., 2, 116, 2019
https://doi.org/10.5194/ica-proc-2-116-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  10 Jul 2019

10 Jul 2019

The Development of Open Source Based Citizen Collaboration Applications for Infrastructure Management: My City Report

Toshikazu Seto1, Yoshihide Sekimoto2, Hiroshi Omata2, Hiroya Maeda2, Takehiro Kashiyama2, Shusaku Higashi3, Masato Fujii3, and Haruyuki Seki3 Toshikazu Seto et al.
  • 1Center for Spatial Information Science, The University of Tokyo, Japan
  • 2Institute of Industrial Science, The University of Tokyo, Japan
  • 3Georepublic Japan

Keywords: Open Government, Open Source, Road Management, Citizen Complaints, Citizen Collaboration

Abstract. This paper describes the development of the “My City Report” open source platform as a tool to encourage citizens to solve problems themselves as well as actively hearing and carefully considering citizens’ opinions. This was accomplished by conducting demonstration experiments utilizing data from several domestic municipalities. The development was done by prototyping and its efficacy was tested in different population sizes from 15 local governments during a period of three years. These discussions showed a functional improvement based on over 300 positive feedback comments. Furthermore, the developed applications and systems were tested on a public cloud during the same period, and some municipalities received long-term submissions from citizens and road administrators. This paper details the current arrival points and issues concerning civil collaboration and management efficiency targeting roads based on data driving. We discuss the current goals and issues concerning citizens’ collaboration and management efficiency for roads based on data driving.

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