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Data Integration and Analysis System (DIAS) Contributing to Climate Change Analysis and Disaster Risk Reduction

Authors :
Akiyuki Kawasaki
Akio Yamamoto
Petra Koudelova
Ralph Acierto
Toshihiro Nemoto
Masaru Kitsuregawa
Toshio Koike
Source :
Data Science Journal, Vol 16 (2017)
Publication Year :
2017
Publisher :
Ubiquity Press, 2017.

Abstract

In 2015, global attempts were made to reconcile the relationship between development and environmental issues. This led to the adoption of key agreements such as the Sustainable Development Goals. In this regard, it is important to identify and evaluate under-recognized disaster risks that hinder sustainable development: measures to mitigate climate change are the same as those that build resilience against climate-related disasters. To do this we need to advance scientific and technical knowledge, build data infrastructure that allows us to predict events with greater accuracy, and develop data archives. For this reason we have developed the Data Integration and Analysis System (DIAS). DIAS incorporates analysis, data and models from many fields and disciplines. It collects and stores data from satellites, ground observation stations and numerical weather prediction models; integrates this data with geographical and socio-economic information; then generates results for crisis management of global environmental issues. This article gives an overview of DIAS and summarizes its application to climate change analysis and disaster risk reduction. As the article shows, DIAS aims to initiate cooperation between different stakeholders, and contribute to the creation of scientific knowledge. DIAS provides a model for sharing transdisciplinary research data that is essential for achieving the goal of sustainable development.

Details

Language :
English
ISSN :
16831470
Volume :
16
Database :
Directory of Open Access Journals
Journal :
Data Science Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.4242432d3d346ce92f07f913de78bc8
Document Type :
article
Full Text :
https://doi.org/10.5334/dsj-2017-041