WOVOdat – the global volcano unrest database aimed at improving eruption forecasts
Purpose: The purpose of this paper is to highlight the importance of a comprehensive global database on volcanic unrest (WOVOdat) as a resource to improve eruption forecasts, hazard evaluation and mitigation actions. Design/methodology/approach: WOVOdat is a centralized database that hosts multi-par...
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Format: | Journal Article |
Language: | English |
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2021
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Online Access: | https://hdl.handle.net/10356/146627 |
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author | Costa, Fidel Widiwijayanti, Christina Nang, Thin Zar Win Fajiculay, Erickson Espinosa-Ortega, Tania Newhall, Christopher |
author2 | Asian School of the Environment |
author_facet | Asian School of the Environment Costa, Fidel Widiwijayanti, Christina Nang, Thin Zar Win Fajiculay, Erickson Espinosa-Ortega, Tania Newhall, Christopher |
author_sort | Costa, Fidel |
collection | NTU |
description | Purpose: The purpose of this paper is to highlight the importance of a comprehensive global database on volcanic unrest (WOVOdat) as a resource to improve eruption forecasts, hazard evaluation and mitigation actions. Design/methodology/approach: WOVOdat is a centralized database that hosts multi-parameter monitoring data sets from unrest and eruption episodes of volcanoes worldwide. Its online interface (https://wovodat.org/) allows interactive data analysis and comparison between volcanoes and eruption styles, which is needed during volcanic crises, as well as to perform basic research on pre-eruption processes, teaching and outreach. Findings: WOVOdat aims to standardize and organize the myriad of monitoring data types at the global scale. Users can compare changes during a crisis to past unrest episodes, and estimate probabilities of outcomes using evidence-based statistics. WOVOdat will be to volcanology as an epidemiological database is to medicine. Research limitations/implications: The success of eruption forecast relies on data completeness, and thus requires the willingness of observatories, governments and researchers to share data across the volcano community. Practical implications: WOVOdat is a unique resource that can be studied to understand the causes of volcanic unrest and to improve eruption forecasting. Originality/value: WOVOdat is the only compilation of standardized and multi-parameter volcano unrest data from around the world, and it is freely and easily accessible through an online interface. |
first_indexed | 2024-10-01T04:48:26Z |
format | Journal Article |
id | ntu-10356/146627 |
institution | Nanyang Technological University |
language | English |
last_indexed | 2024-10-01T04:48:26Z |
publishDate | 2021 |
record_format | dspace |
spelling | ntu-10356/1466272022-04-07T07:19:29Z WOVOdat – the global volcano unrest database aimed at improving eruption forecasts Costa, Fidel Widiwijayanti, Christina Nang, Thin Zar Win Fajiculay, Erickson Espinosa-Ortega, Tania Newhall, Christopher Asian School of the Environment Earth Observatory of Singapore Science::Geology::Volcanoes and earthquakes Database Eruption Forecast Purpose: The purpose of this paper is to highlight the importance of a comprehensive global database on volcanic unrest (WOVOdat) as a resource to improve eruption forecasts, hazard evaluation and mitigation actions. Design/methodology/approach: WOVOdat is a centralized database that hosts multi-parameter monitoring data sets from unrest and eruption episodes of volcanoes worldwide. Its online interface (https://wovodat.org/) allows interactive data analysis and comparison between volcanoes and eruption styles, which is needed during volcanic crises, as well as to perform basic research on pre-eruption processes, teaching and outreach. Findings: WOVOdat aims to standardize and organize the myriad of monitoring data types at the global scale. Users can compare changes during a crisis to past unrest episodes, and estimate probabilities of outcomes using evidence-based statistics. WOVOdat will be to volcanology as an epidemiological database is to medicine. Research limitations/implications: The success of eruption forecast relies on data completeness, and thus requires the willingness of observatories, governments and researchers to share data across the volcano community. Practical implications: WOVOdat is a unique resource that can be studied to understand the causes of volcanic unrest and to improve eruption forecasting. Originality/value: WOVOdat is the only compilation of standardized and multi-parameter volcano unrest data from around the world, and it is freely and easily accessible through an online interface. 2021-03-03T06:56:51Z 2021-03-03T06:56:51Z 2019 Journal Article Costa, F., Widiwijayanti, C., Nang, T. Z. W., Fajiculay, E., Espinosa-Ortega, T., & Newhall, C. (2019). WOVOdat – the global volcano unrest database aimed at improving eruption forecasts. Disaster Prevention and Management, 28(6), 738-751. doi:10.1108/DPM-09-2019-0301 0965-3562 0000-0002-1409-5325 0000-0001-8505-5200 https://hdl.handle.net/10356/146627 10.1108/DPM-09-2019-0301 2-s2.0-85075077099 6 28 738 751 en Disaster Prevention and Management © 2019 Emerald Publishing Limited. All rights reserved. |
spellingShingle | Science::Geology::Volcanoes and earthquakes Database Eruption Forecast Costa, Fidel Widiwijayanti, Christina Nang, Thin Zar Win Fajiculay, Erickson Espinosa-Ortega, Tania Newhall, Christopher WOVOdat – the global volcano unrest database aimed at improving eruption forecasts |
title | WOVOdat – the global volcano unrest database aimed at improving eruption forecasts |
title_full | WOVOdat – the global volcano unrest database aimed at improving eruption forecasts |
title_fullStr | WOVOdat – the global volcano unrest database aimed at improving eruption forecasts |
title_full_unstemmed | WOVOdat – the global volcano unrest database aimed at improving eruption forecasts |
title_short | WOVOdat – the global volcano unrest database aimed at improving eruption forecasts |
title_sort | wovodat the global volcano unrest database aimed at improving eruption forecasts |
topic | Science::Geology::Volcanoes and earthquakes Database Eruption Forecast |
url | https://hdl.handle.net/10356/146627 |
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