Clarifying the transition of workload for victims life reconstruction support programs in affected local governments using the victims master database - Comparison between the 2007 Chuetsu-oki earthquake and the 2016 Kumamoto Earthquake

Munenari Inoguchi; Keiko Tamura; Kei Horie; Haruo Hayashi

doi:10.1109/BigData.2017.8258470

Clarifying the transition of workload for victims life reconstruction support programs in affected local governments using the victims master database - Comparison between the 2007 Chuetsu-oki earthquake and the 2016 Kumamoto Earthquake

Munenari Inoguchi, Keiko Tamura, Kei Horie, Haruo Hayashi

Civil Design and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

To realize an effective disaster response, the entire picture of the damage situation must be grasped. which is time consuming, especially after a huge disaster. After the 2011 East Japan Earthquake, it took about six months for local responders to grasp the general damage situation because they inspected the degree of damage for each building and certified the degree of damage for each victim. This study aims to clarify how much work occurs at an actual disaster site. We selected the 2016 Kumamoto Earthquake and the 2007 Chuetsu-oki Earthquake as case studies, and collected work logs from affected municipalities to determine the transition in the work volume. These logs were analyzed chronologically. It took about three months to certify the degree of building damage for each victim regardless of the severity of damage and area characteristics.

Original language	English
Title of host publication	Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Editors	Jian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4384-4388
Number of pages	5
ISBN (Electronic)	9781538627143
DOIs	https://doi.org/10.1109/BigData.2017.8258470
State	Published - 2017/07/01
Event	5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States Duration: 2017/12/11 → 2017/12/14

Publication series

Name	Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume	2018-January

Conference

Conference	5th IEEE International Conference on Big Data, Big Data 2017
Country/Territory	United States
City	Boston
Period	2017/12/11 → 2017/12/14

Keywords

Chronological Analysis
Victims Life Reconstruction
Victims Master Database
Work Volume

ASJC Scopus subject areas

Computer Networks and Communications
Hardware and Architecture
Information Systems
Information Systems and Management
Control and Optimization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/BigData.2017.8258470

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Inoguchi, M., Tamura, K., Horie, K., & Hayashi, H. (2017). Clarifying the transition of workload for victims life reconstruction support programs in affected local governments using the victims master database - Comparison between the 2007 Chuetsu-oki earthquake and the 2016 Kumamoto Earthquake. In J.-Y. Nie, Z. Obradovic, T. Suzumura, R. Ghosh, R. Nambiar, C. Wang, H. Zang, R. Baeza-Yates, R. Baeza-Yates, X. Hu, J. Kepner, A. Cuzzocrea, J. Tang, & M. Toyoda (Eds.), Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017 (pp. 4384-4388). (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2017.8258470

Inoguchi, Munenari ; Tamura, Keiko ; Horie, Kei et al. / Clarifying the transition of workload for victims life reconstruction support programs in affected local governments using the victims master database - Comparison between the 2007 Chuetsu-oki earthquake and the 2016 Kumamoto Earthquake. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. editor / Jian-Yun Nie ; Zoran Obradovic ; Toyotaro Suzumura ; Rumi Ghosh ; Raghunath Nambiar ; Chonggang Wang ; Hui Zang ; Ricardo Baeza-Yates ; Ricardo Baeza-Yates ; Xiaohua Hu ; Jeremy Kepner ; Alfredo Cuzzocrea ; Jian Tang ; Masashi Toyoda. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 4384-4388 (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017).

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abstract = "To realize an effective disaster response, the entire picture of the damage situation must be grasped. which is time consuming, especially after a huge disaster. After the 2011 East Japan Earthquake, it took about six months for local responders to grasp the general damage situation because they inspected the degree of damage for each building and certified the degree of damage for each victim. This study aims to clarify how much work occurs at an actual disaster site. We selected the 2016 Kumamoto Earthquake and the 2007 Chuetsu-oki Earthquake as case studies, and collected work logs from affected municipalities to determine the transition in the work volume. These logs were analyzed chronologically. It took about three months to certify the degree of building damage for each victim regardless of the severity of damage and area characteristics.",

keywords = "Chronological Analysis, Victims Life Reconstruction, Victims Master Database, Work Volume",

author = "Munenari Inoguchi and Keiko Tamura and Kei Horie and Haruo Hayashi",

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Inoguchi, M, Tamura, K, Horie, K & Hayashi, H 2017, Clarifying the transition of workload for victims life reconstruction support programs in affected local governments using the victims master database - Comparison between the 2007 Chuetsu-oki earthquake and the 2016 Kumamoto Earthquake. in J-Y Nie, Z Obradovic, T Suzumura, R Ghosh, R Nambiar, C Wang, H Zang, R Baeza-Yates, R Baeza-Yates, X Hu, J Kepner, A Cuzzocrea, J Tang & M Toyoda (eds), Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 4384-4388, 5th IEEE International Conference on Big Data, Big Data 2017, Boston, United States, 2017/12/11. https://doi.org/10.1109/BigData.2017.8258470

Clarifying the transition of workload for victims life reconstruction support programs in affected local governments using the victims master database - Comparison between the 2007 Chuetsu-oki earthquake and the 2016 Kumamoto Earthquake. / Inoguchi, Munenari; Tamura, Keiko; Horie, Kei et al.
Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. ed. / Jian-Yun Nie; Zoran Obradovic; Toyotaro Suzumura; Rumi Ghosh; Raghunath Nambiar; Chonggang Wang; Hui Zang; Ricardo Baeza-Yates; Ricardo Baeza-Yates; Xiaohua Hu; Jeremy Kepner; Alfredo Cuzzocrea; Jian Tang; Masashi Toyoda. Institute of Electrical and Electronics Engineers Inc., 2017. p. 4384-4388 (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Tamura, Keiko

AU - Horie, Kei

AU - Hayashi, Haruo

PY - 2017/7/1

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KW - Victims Master Database

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BT - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017

A2 - Nie, Jian-Yun

A2 - Obradovic, Zoran

A2 - Suzumura, Toyotaro

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PB - Institute of Electrical and Electronics Engineers Inc.

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Inoguchi M, Tamura K, Horie K, Hayashi H. Clarifying the transition of workload for victims life reconstruction support programs in affected local governments using the victims master database - Comparison between the 2007 Chuetsu-oki earthquake and the 2016 Kumamoto Earthquake. In Nie JY, Obradovic Z, Suzumura T, Ghosh R, Nambiar R, Wang C, Zang H, Baeza-Yates R, Baeza-Yates R, Hu X, Kepner J, Cuzzocrea A, Tang J, Toyoda M, editors, Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 4384-4388. (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017). doi: 10.1109/BigData.2017.8258470