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

Clicks: 275
ID: 154777
2018
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Ranked #143 of 292 articles by views in Proceedings of the National Academy of Sciences of the United States of America

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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 open 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.
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kawasaki2018datadata Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Akiyuki Kawasaki;Petra Koudelova;Katsunori Tamakawa;Asanobu Kitamoto;Eiji Ikoma;Koji Ikeuchi;Ryosuke Shibasaki;Masaru Kitsuregawa;Toshio Koike
Journal Proceedings of the National Academy of Sciences of the United States of America
Year 2018
DOI
10.5334/dsj-2018-029
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