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Data schemas for multiple hazards, exposure and vulnerability

Richard J. Murnane (Global Facility for Disaster Reduction and Recovery, World Bank Group, Washington, District of Columbia, USA) (Kinetic Analysis Corporation, Garrett Park, Maryland, USA)
Giovanni Allegri (GeoSolutions, Massarosa, Italy)
Alphonce Bushi (Geological Survey of Tanzania, Dodoma, United Republic of Tanzania)
Jamal Dabbeek (University School for Advanced Studies Pavia, Pavia, Italy)
Hans de Moel (Institute for Environmental Studies, VU Amsterdam, Amsterdam, The Netherlands)
Melanie Duncan (British Geological Survey, Edinburgh, UK)
Stuart Fraser (Global Facility for Disaster Reduction and Recovery, World Bank Group, Washington, District of Columbia, USA)
Carmine Galasso (University College London, London, UK)
Cristiano Giovando (Global Facility for Disaster Reduction and Recovery, World Bank Group, Washington, District of Columbia, USA)
Paul Henshaw (Global Earthquake Model Foundation, Pavia, Italy)
Kevin Horsburgh (National Oceanography Centre, Liverpool, UK)
Charles Huyck (ImageCat Inc., Long Beach, California, USA)
Susanna Jenkins (Earth Observatory of Singapore, Nanyang Technological University, Singapore)
Cassidy Johnson (University College London, London, UK)
Godson Kamihanda (Geological Survey of Tanzania, Dodoma, United Republic of Tanzania)
Justice Kijazi (Tanzania Meteorological Agency, Dar es Salaam, United Republic of Tanzania)
Wilberforce Kikwasi (Tanzania Meteorological Agency, Dar es Salaam, United Republic of Tanzania)
Wilbard Kombe (Ardhi University, Dar es Salaam, United Republic of Tanzania)
Susan Loughlin (British Geological Survey – Edinburgh Office, Edinburgh, UK)
Finn Løvholt (Norwegian Geotechnical Institute, Oslo, Norway)
Alex Masanja (Geological Survey of Tanzania, Dodoma, United Republic of Tanzania)
Gabriel Mbongoni (Geological Survey of Tanzania, Dodoma, United Republic of Tanzania)
Stelios Minas (AIR Worldwide Corp., Singapore)
Michael Msabi (The University of Dodoma, Dodoma, United Republic of Tanzania)
Maruvuko Msechu (Geological Survey of Tanzania, Dodoma, United Republic of Tanzania)
Habiba Mtongori (Tanzania Meteorological Agency, Dar es Salaam, United Republic of Tanzania)
Farrokh Nadim (Norwegian Geotechnical Institute, Oslo, Norway)
Mhairi O’Hara (Humanitarian OpenStreetMap Team, Jakarta, Indonesia)
Marco Pagani (Global Earthquake Model Foundation, Pavia, Italy)
Emma Phillips (Global Facility for Disaster Reduction and Recovery, World Bank Group, Washington, District of Columbia, USA)
Tiziana Rossetto (University College London, London, UK)
Roberto Rudari (Centro Internazionale in Monitoraggio Ambientale, Savona, Italy)
Peter Sangana (The University of Dodoma, Dodoma, United Republic of Tanzania)
Vitor Silva (Global Earthquake Model Foundation, Pavia, Italy)
John Twigg (University College London, London, UK)
Guido Uhinga (Ardhi University, Dar es Salaam, United Republic of Tanzania)
Enrica Verrucci (University College London, London, UK)

Disaster Prevention and Management

ISSN: 0965-3562

Article publication date: 24 October 2019

Issue publication date: 11 November 2019

556

Abstract

Purpose

Using risk-related data often require a significant amount of upfront work to collect, extract and transform data. In addition, the lack of a consistent data structure hinders the development of tools that can be used with more than one set of data. The purpose of this paper is to report on an effort to solve these problems through the development of extensible, internally consistent schemas for risk-related data.

Design/methodology/approach

The consortia coordinated their efforts so the hazard, exposure and vulnerability schemas are compatible. Hazard data can be provided as either event footprints or stochastic catalogs. Exposure classes include buildings, infrastructure, agriculture, livestock, forestry and socio-economic data. The vulnerability component includes fragility and vulnerability functions and indicators for physical and social vulnerability. The schemas also provide the ability to define uncertainties and allow the scoring of vulnerability data for relevance and quality.

Findings

As a proof of concept, the schemas were populated with data for Tanzania and with exposure data for several other countries.

Research limitations/implications

The data schema and data exploration tool are open source and, if widely accepted, could become widely used by practitioners.

Practical implications

A single set of hazard, exposure and vulnerability schemas will not fit all purposes. Tools will be needed to transform the data into other formats.

Originality/value

This paper describes extensible, internally consistent, multi-hazard, exposure and vulnerability schemas that can be used to store disaster risk-related data and a data exploration tool that promotes data discovery and use.

Keywords

Citation

Murnane, R.J., Allegri, G., Bushi, A., Dabbeek, J., de Moel, H., Duncan, M., Fraser, S., Galasso, C., Giovando, C., Henshaw, P., Horsburgh, K., Huyck, C., Jenkins, S., Johnson, C., Kamihanda, G., Kijazi, J., Kikwasi, W., Kombe, W., Loughlin, S., Løvholt, F., Masanja, A., Mbongoni, G., Minas, S., Msabi, M., Msechu, M., Mtongori, H., Nadim, F., O’Hara, M., Pagani, M., Phillips, E., Rossetto, T., Rudari, R., Sangana, P., Silva, V., Twigg, J., Uhinga, G. and Verrucci, E. (2019), "Data schemas for multiple hazards, exposure and vulnerability", Disaster Prevention and Management, Vol. 28 No. 6, pp. 752-763. https://doi.org/10.1108/DPM-09-2019-0293

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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