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

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

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

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

Media Preference, Information Needs, and the Language Proficiency of Foreigners in Japan after the 2011 Great East Japan Earthquake

After the 2011 Great East Japan Earthquake, the Japanese government identified the lack of proficiency in the Japanese language as one characteristic of foreigners that should be considered in disaster prevention planning. This article seeks to understand how proficiency in a local language affects disaster information gathering behavior by using the results of a questionnaire survey conducted after the 2011 Great East Japan Earthquake. Respondents were categorized based on their Japanese and English language abilities. Their media mode, language preferences, information importance, and information-gathering difficulties also were examined. It was found that foreigners skilled in Japanese demonstrated similar information gathering behavior as Japanese respondents, but foreigners unskilled in Japanese showed little usage of Japanese-language media. This group also encountered difficulties due to a lack of Japanese proficiency, but many members were able to acquire some level of Japanese-language information through Internet-based methods. To address language proficiency in disaster prevention planning, information provision in languages other than Japanese should be increased, and Japanese information should be shared in a way that facilitates translation. Although this survey was significant in its scope, the results should be considered within the limitations of the Internet-based response collection and focus only on the less-affected area of Japan

River flood inundation mapping in the Bago River Basin, Myanmar

Flood inundation maps were generated in the Bago River Basin, Myanmar. Although the design of our study was not new, it is one of very few to have analyzed a flood inundation area in Myanmar. Nine flood events were applied to calibrate and validate the results. The flood-inundated area was validated with satellite image for the year 2006. The flood inundation maps with different return periods were delineated. Considering the 50- and 100-year return period flood scenario, the highest depth of inundation may affect the urban area of Bago. The information derived from this study can contribute to assessments of potential flood damage for the local region and for other locations where data is limited

Estimating the level of income in individual buildings using data from household interview surveys and satellite imagery: case study in Myanmar and Nicaragua

ABSTRACTLeaving no one behind is a worldwide goal, but it is difficult to make policy to address this issue because we do not have a thorough knowledge of where poverty exists and in what forms due to lack of data, particularly in developing countries. Household interview surveys are the common way to collect such information, but conducting large-scale surveys frequently is difficult from the perspective of cost and time. Here, we show a novel method for estimating income levels of individual building in urban and peri-urban rural areas. The combination of high-resolution satellite imagery and household interview survey data obtained by visiting households on the ground makes it possible to estimate income levels at a detailed scale for the first time. These data are often handled in different academic disciplines and are rarely used in combination. Using the results, we can determine the number and location of poor people at the local scale. We can also identify areas with particularly high concentrations of poor people. This information enables planning and policy making for more effective poverty reduction and disaster prevention measures tailored to local conditions. Thus, the results of this study will help developing countries to achieve sustainable development

The growing role of web-based geospatial technology in disaster response and support

This paper examines changes in disaster response and relief efforts and recent web-based geospatial technological developments through an evaluation of the experiences of the Center for Geographic Analysis, Harvard University, of the Sichuan (2008) and Haiti (2010) earthquake responses. This paper outlines how conventional GIS (geographic information systems) disaster responses by governmental agencies and relief response organisations and the means for geospatial data-sharing have been transformed into a more dynamic, more transparent, and decentralised form with a wide participation. It begins by reviewing briefly at historical changes in the employment of geospatial technologies in major devastating disasters, including the Sichuan and Haiti earthquakes (case studies for our geospatial portal project). It goes on to assess changes in the available dataset type and in geospatial disaster responders, as well as the impact of geospatial technological changes on disaster relief effort. Finally, the paper discusses lessons learned from recent responses and offers some thoughts for future development.Other Research Uni

Design and Implementation of a Training Course on Big Data Use in Water Management

Big Data has great potential to be applied to research in the field of geosciences. Motivated by the opportunity provided by the Data Integration and Analysis System (DIAS) of Japan, we organized an intensive two-week course that aims to educate participants on Big Data and its exploitation to solve water management problems. When developing and implementing the Program, we identified two main challenges: (1) assuring that the training has a lasting effect and (2) developing an interdisciplinary curriculum suitable for participants of diverse professional backgrounds. To address these challenges, we introduced several distinctive features. The Program was based on experiential learning – the participants were required to solve real problems and worked in international and multidisciplinary teams. The lectures were strictly relevant to the case-study problems. Significant time was devoted to hands-on exercises, and participants received immediate feedback on individual assignments to ensure skills development. Our evaluation of the two occasions of the Program in 2015 and 2016 indicates significant positive outcomes. The successful completion of the individual assignments confirmed that the participants gained key skills related to the usage of DIAS and other tools. The final solutions to the case-study problems showed that the participants were able to integrate and apply the obtained knowledge, indicating that the Program’s format and curriculum were effective. We found that participants used DIAS in subsequent studies and work, thus suggesting that the Program had long-lasting effects. Our experience indicates that despite time constraints, short courses can effectively encourage researchers and practitioners to explore opportunities provided by Big Data