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All-hazards dataset mined from the US National Incident Management System 1999–2014

This paper describes a new dataset mined from the public archive (1999–2014) of the U.S. National Incident Management System/Incident Command System Incident Status Summary Form (a total of 124,411 reports for 25,083 incidents, including 24,608 wildfires). This system captures detailed information o...

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Autores principales: St. Denis, Lise A., Mietkiewicz, Nathan P., Short, Karen C., Buckland, Mollie, Balch, Jennifer K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7035274/
https://www.ncbi.nlm.nih.gov/pubmed/32081906
http://dx.doi.org/10.1038/s41597-020-0403-0
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author St. Denis, Lise A.
Mietkiewicz, Nathan P.
Short, Karen C.
Buckland, Mollie
Balch, Jennifer K.
author_facet St. Denis, Lise A.
Mietkiewicz, Nathan P.
Short, Karen C.
Buckland, Mollie
Balch, Jennifer K.
author_sort St. Denis, Lise A.
collection PubMed
description This paper describes a new dataset mined from the public archive (1999–2014) of the U.S. National Incident Management System/Incident Command System Incident Status Summary Form (a total of 124,411 reports for 25,083 incidents, including 24,608 wildfires). This system captures detailed information on incident management costs, personnel, hazard characteristics, values at risk, fatalities, and structural damage. Most (98.5%) of the reports are fire-related, followed in decreasing order by other, hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use due to multiple record formats, inconsistent free-form fields, and no bridge between individual reports and high-level incident analysis. Here, we describe this improved dataset and the open, reproducible methods used, including merging records across three versions of the system, cleaning and aligning with the current system, smoothing values across reports, and supporting incident-level analysis. This integrated record offers the opportunity to explore the daily progression of the most costly, damaging, and deadly events in the U.S., particularly for wildfires.
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spelling pubmed-70352742020-03-04 All-hazards dataset mined from the US National Incident Management System 1999–2014 St. Denis, Lise A. Mietkiewicz, Nathan P. Short, Karen C. Buckland, Mollie Balch, Jennifer K. Sci Data Data Descriptor This paper describes a new dataset mined from the public archive (1999–2014) of the U.S. National Incident Management System/Incident Command System Incident Status Summary Form (a total of 124,411 reports for 25,083 incidents, including 24,608 wildfires). This system captures detailed information on incident management costs, personnel, hazard characteristics, values at risk, fatalities, and structural damage. Most (98.5%) of the reports are fire-related, followed in decreasing order by other, hurricane, hazardous materials, flood, tornado, search and rescue, civil unrest, and winter storms. The archive, although publicly available, has been difficult to use due to multiple record formats, inconsistent free-form fields, and no bridge between individual reports and high-level incident analysis. Here, we describe this improved dataset and the open, reproducible methods used, including merging records across three versions of the system, cleaning and aligning with the current system, smoothing values across reports, and supporting incident-level analysis. This integrated record offers the opportunity to explore the daily progression of the most costly, damaging, and deadly events in the U.S., particularly for wildfires. Nature Publishing Group UK 2020-02-21 /pmc/articles/PMC7035274/ /pubmed/32081906 http://dx.doi.org/10.1038/s41597-020-0403-0 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
St. Denis, Lise A.
Mietkiewicz, Nathan P.
Short, Karen C.
Buckland, Mollie
Balch, Jennifer K.
All-hazards dataset mined from the US National Incident Management System 1999–2014
title All-hazards dataset mined from the US National Incident Management System 1999–2014
title_full All-hazards dataset mined from the US National Incident Management System 1999–2014
title_fullStr All-hazards dataset mined from the US National Incident Management System 1999–2014
title_full_unstemmed All-hazards dataset mined from the US National Incident Management System 1999–2014
title_short All-hazards dataset mined from the US National Incident Management System 1999–2014
title_sort all-hazards dataset mined from the us national incident management system 1999–2014
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7035274/
https://www.ncbi.nlm.nih.gov/pubmed/32081906
http://dx.doi.org/10.1038/s41597-020-0403-0
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