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JDR Vol.16 No.4 pp. 676-683
(2021)
doi: 10.20965/jdr.2021.p0676

Paper:

Interdisciplinary and Industry-Academia Collaboration Research for Enhancing Social Resilience to Natural Disasters in the Tokyo Metropolitan Area –DEKATSU Activity–

Takashi Furuya and Naoshi Hirata

Research Center for Enhancing Metropolitan Resilience, National Research Institute for Earth Science and Disaster Resilience (NIED)
3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan

Corresponding author

Received:
October 5, 2020
Accepted:
November 4, 2020
Published:
June 1, 2021
Keywords:
disaster resilience, integrated multi-disciplinary research, Data Use and Application Council for Resilience (DEKATSU), Industry-Government-Academia-Private Linkage, Tokyo Metropolitan area
Abstract

In 2007, we initiated a 5-year-research project named the “Tokyo Metropolitan Resilience Project.” This project is intended to improve the resilience to natural disasters, particularly earthquakes, in the Tokyo metropolitan area. For this purpose, we have organized multi-disciplinary research including social sciences, natural sciences such as seismology, and civil engineering, with a focus on earthquake engineering. In addition, we facilitate mutual communication between industry and academia. We established the “Data Use and Application Council for Resilience” (Japanese abbreviation: DEKATSU) to organize private and public stakeholders. The DEKATSU council consists of four sectors: industry, government, NPO/NGOs, and academia. The policy promoted to the participating organizations is “When we make organizations resilient, the Tokyo metropolitan area also becomes resilient.” To date, 67 organizational members and 13 personal members have joined, and the targeted idea is becoming accepted but not fully implemented in society.

Cite this article as:
T. Furuya and N. Hirata, “Interdisciplinary and Industry-Academia Collaboration Research for Enhancing Social Resilience to Natural Disasters in the Tokyo Metropolitan Area –DEKATSU Activity–,” J. Disaster Res., Vol.16 No.4, pp. 676-683, 2021.
Data files:
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