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

Akiyuki Kawasaki,Toshio Koike,Ralph Acierto,Petra Koudelova,Toshihiro Nemoto,Akio Yamamoto,Masaru Kitsuregawa

doi:10.5334/dsj-2017-041

Akiyuki Kawasaki, Toshio Koike + Show 5 more

Open Access

https://doi.org/10.5334/dsj-2017-041

Copy DOI

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.

Highlights

Humans have needs – food, water, energy, health, security – and development is required to provide for these needs
With regard to research on the global environment, Data Integration and Analysis System (DIAS) is involved in all aspects of the data lifecycle— measurement, retrieval, analysis, archiving, and sharing of information
There are other specialized data measurement/management infrastructure systems, DIAS is distinctive in the way it integrates the infrastructure system, application development, and research and development (R&D) community to facilitate interdisciplinary and transdisciplinary research and support solution development with a broad cross-sectorial approach

Summary

Introduction

Humans have needs – food, water, energy, health, security – and development is required to provide for these needs. DIAS applications and tools consist of software and services that implement data storage/search, analysis, visualization, and other functions developed by domain scientists and IT experts working together to find concrete solutions to global and local environmental and social issues.

Results

Conclusion