Data schemas for multiple hazards, exposure and vulnerability

Richard J. Murnane, Giovanni Allegri, Alphonce Bushi, Jamal Dabbeek, Hans de Moel, Melanie Duncan, Stuart Fraser, Carmine Galasso, Cristiano Giovando, Paul Henshaw, Kevin Horsburgh, Charles Huyck, Susanna Jenkins, Cassidy Johnson, Godson Kamihanda, Justice Kijazi, Wilberforce Kikwasi, Wilbard Kombe, Susan Loughlin, Finn Løvholt & 17 others Alex Masanja, Gabriel Mbongoni, Stelios Minas, Michael Msabi, Maruvuko Msechu, Habiba Mtongori, Farrokh Nadim, Mhairi O’Hara, Marco Pagani, Emma Phillips, Tiziana Rossetto, Roberto Rudari, Peter Sangana, Vitor Silva, John Twigg, Guido Uhinga, Enrica Verrucci

Research output: Contribution to JournalArticleAcademicpeer-review

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.

Original languageEnglish
Pages (from-to)752-763
Number of pages12
JournalDisaster Prevention and Management: An International Journal
Volume28
Issue number6
DOIs
Publication statusPublished - 4 Nov 2019

Fingerprint

vulnerability
hazard
Forestry
Tanzania
Livestock
Disasters
Agriculture
Uncertainty
Economics
Research
exposure
transform
footprint
forestry
livestock
disaster
building
infrastructure
Data Accuracy
Datasets

Keywords

  • Damage
  • Disaster risk
  • Exposure
  • Fragility
  • Multi-hazard
  • Natural hazards
  • Vulnerability

Cite this

Murnane, Richard J. ; Allegri, Giovanni ; Bushi, Alphonce ; Dabbeek, Jamal ; de Moel, Hans ; Duncan, Melanie ; Fraser, Stuart ; Galasso, Carmine ; Giovando, Cristiano ; Henshaw, Paul ; Horsburgh, Kevin ; Huyck, Charles ; Jenkins, Susanna ; Johnson, Cassidy ; Kamihanda, Godson ; Kijazi, Justice ; Kikwasi, Wilberforce ; Kombe, Wilbard ; Loughlin, Susan ; Løvholt, Finn ; Masanja, Alex ; Mbongoni, Gabriel ; Minas, Stelios ; Msabi, Michael ; Msechu, Maruvuko ; Mtongori, Habiba ; Nadim, Farrokh ; O’Hara, Mhairi ; Pagani, Marco ; Phillips, Emma ; Rossetto, Tiziana ; Rudari, Roberto ; Sangana, Peter ; Silva, Vitor ; Twigg, John ; Uhinga, Guido ; Verrucci, Enrica. / Data schemas for multiple hazards, exposure and vulnerability. In: Disaster Prevention and Management: An International Journal. 2019 ; Vol. 28, No. 6. pp. 752-763.
@article{256cb096845645898d9b6f82fe6a1727,
title = "Data schemas for multiple hazards, exposure and vulnerability",
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 = "Damage, Disaster risk, Exposure, Fragility, Multi-hazard, Natural hazards, Vulnerability",
author = "Murnane, {Richard J.} and Giovanni Allegri and Alphonce Bushi and Jamal Dabbeek and {de Moel}, Hans and Melanie Duncan and Stuart Fraser and Carmine Galasso and Cristiano Giovando and Paul Henshaw and Kevin Horsburgh and Charles Huyck and Susanna Jenkins and Cassidy Johnson and Godson Kamihanda and Justice Kijazi and Wilberforce Kikwasi and Wilbard Kombe and Susan Loughlin and Finn L{\o}vholt and Alex Masanja and Gabriel Mbongoni and Stelios Minas and Michael Msabi and Maruvuko Msechu and Habiba Mtongori and Farrokh Nadim and Mhairi O’Hara and Marco Pagani and Emma Phillips and Tiziana Rossetto and Roberto Rudari and Peter Sangana and Vitor Silva and John Twigg and Guido Uhinga and Enrica Verrucci",
year = "2019",
month = "11",
day = "4",
doi = "10.1108/DPM-09-2019-0293",
language = "English",
volume = "28",
pages = "752--763",
journal = "Disaster prevention and management",
issn = "0965-3562",
publisher = "Emerald Group Publishing Ltd.",
number = "6",

}

Murnane, RJ, 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 & Verrucci, E 2019, 'Data schemas for multiple hazards, exposure and vulnerability' Disaster Prevention and Management: An International Journal, vol. 28, no. 6, pp. 752-763. https://doi.org/10.1108/DPM-09-2019-0293

Data schemas for multiple hazards, exposure and vulnerability. / Murnane, Richard J.; Allegri, Giovanni; Bushi, Alphonce; Dabbeek, Jamal; de Moel, Hans; Duncan, Melanie; Fraser, Stuart; Galasso, Carmine; Giovando, Cristiano; Henshaw, Paul; Horsburgh, Kevin; Huyck, Charles; Jenkins, Susanna; Johnson, Cassidy; Kamihanda, Godson; Kijazi, Justice; Kikwasi, Wilberforce; Kombe, Wilbard; Loughlin, Susan; Løvholt, Finn; Masanja, Alex; Mbongoni, Gabriel; Minas, Stelios; Msabi, Michael; Msechu, Maruvuko; Mtongori, Habiba; Nadim, Farrokh; O’Hara, Mhairi; Pagani, Marco; Phillips, Emma; Rossetto, Tiziana; Rudari, Roberto; Sangana, Peter; Silva, Vitor; Twigg, John; Uhinga, Guido; Verrucci, Enrica.

In: Disaster Prevention and Management: An International Journal, Vol. 28, No. 6, 04.11.2019, p. 752-763.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Data schemas for multiple hazards, exposure and vulnerability

AU - Murnane, Richard J.

AU - Allegri, Giovanni

AU - Bushi, Alphonce

AU - Dabbeek, Jamal

AU - de Moel, Hans

AU - Duncan, Melanie

AU - Fraser, Stuart

AU - Galasso, Carmine

AU - Giovando, Cristiano

AU - Henshaw, Paul

AU - Horsburgh, Kevin

AU - Huyck, Charles

AU - Jenkins, Susanna

AU - Johnson, Cassidy

AU - Kamihanda, Godson

AU - Kijazi, Justice

AU - Kikwasi, Wilberforce

AU - Kombe, Wilbard

AU - Loughlin, Susan

AU - Løvholt, Finn

AU - Masanja, Alex

AU - Mbongoni, Gabriel

AU - Minas, Stelios

AU - Msabi, Michael

AU - Msechu, Maruvuko

AU - Mtongori, Habiba

AU - Nadim, Farrokh

AU - O’Hara, Mhairi

AU - Pagani, Marco

AU - Phillips, Emma

AU - Rossetto, Tiziana

AU - Rudari, Roberto

AU - Sangana, Peter

AU - Silva, Vitor

AU - Twigg, John

AU - Uhinga, Guido

AU - Verrucci, Enrica

PY - 2019/11/4

Y1 - 2019/11/4

N2 - 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.

AB - 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.

KW - Damage

KW - Disaster risk

KW - Exposure

KW - Fragility

KW - Multi-hazard

KW - Natural hazards

KW - Vulnerability

UR - http://www.scopus.com/inward/record.url?scp=85074408038&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85074408038&partnerID=8YFLogxK

U2 - 10.1108/DPM-09-2019-0293

DO - 10.1108/DPM-09-2019-0293

M3 - Article

VL - 28

SP - 752

EP - 763

JO - Disaster prevention and management

JF - Disaster prevention and management

SN - 0965-3562

IS - 6

ER -