Data Integration and Analysis System (DIAS) as a Platform for Data and Model Integration: Cases in the Field of Water Resources Management and Disaster Risk Reduction

Akiyuki Kawasaki,Eiji Ikoma,Masaru Kitsuregawa,Koji Ikeuchi,Petra Koudelova,Tosho Koike,Asanobu Kitamoto,Katsunori Tamakawa,Ryosuke Shibasaki

doi:10.5334/dsj-2018-029

Abstract

The development of data and model integration platforms has furthered scientific inquiry and helped to solve pressing social and environmental problems. While several e-infrastructure platforms have been developed, the concept of data and model integration remains obscure, and these platforms have produced few firm results. This article investigates data and model integration on the Data Integration and Analysis System (DIAS) platform, using three case projects from water-related fields. We provide concrete examples of data and model integration by analyzing the data transfer and analysis process, and demonstrate what platform functions are needed to promote the advantages of data and model integration. In addition, we introduce the Digital Object Identifier (DOI), a valuable tool for promoting data and model integration and science. Our investigation reveals that DIAS advances data and model integration in five main ways: it is a sophisticated and robust integration platform; has rich APIs, including a metadata management system, for high-quality data archive and utilization; functions as a core hydrological model; and promotes a collaborative R&D community and open science and data repositories. This article will appeal especially to researchers interested in new methods of analysis, and information technology experts responsible for developing e-infrastructure systems to support environmental and scientific research.

Highlights

We provide concrete examples of data and model integration by analyzing the data transfer and analysis process, and demonstrate what platform functions are needed to promote the advantages of data and model integration
By investigating three case projects taken from Data Integration and Analysis System (DIAS), we provide concrete examples of data and model integration by analyzing the data transfer and analysis process, and demonstrate what platform functions are needed to promote data and model integration
By investigating three case projects taken from DIAS, we provided concrete examples of data and model integration, and demonstrated what platform functions are needed to promote the advantages of data and model integration

Summary

Introduction

If global environmental challenges are to be addressed effectively, a coordinated international approach that plans, implements and manages data, analytics and e-infrastructures is required (Belmont Forum 2015; Yarime 2017a). Countries around the world are developing e-infrastructures that will facilitate the combination of digitally-based technology (hardware and software), resources (data, services, d igital libraries), and communications (protocols, access rights and networks). This, in turn, will support cutting-edge, collaborative research in a wide range of scholarly fields (RCUK 2010). The integration of natural scientific data and socio-economic data is especially important for solving social problems and supporting decision-making. We have gained a better understanding of the earth’s environment by integrating and analyzing different data, including satellite, in-situ, model output, socio-economic and geospatial data.

Objectives

Discussion

Conclusion