Data Integration and Analysis System

The DIAS initiative aims to contribute to society’s adaptation policies for various time-spatial scales of climate change and weather events by combining climate big-data and information techniques.

The DIAS initiative offers values to the world to encourage local actions for global impact. While DIAS provides a collaboration platform for data integration and analysis, the DIAS initiative utilizes its platform to provide early warning programmes to enhance resilience for water and health. Integrating EO data and models, these programmes provide operational insights for local stakeholders for science-based decision making. The DIAS initiative also provides capacity development platforms to foster local science communicators who bridge the gap between science and society.

Over 10,000 users have a DIAS account to use applications and to download datasets, and ~10 prototyping research projects are ongoing to analyze climate data, develop application software, to make useful information for solving climate-related and/or weather-related problems. Early Warning Programme (South Africa) Malaria Infection Prediction Early Warning System: The model with climate forecast data and malaria patient count data from local municipalities and medical institutions, provides malaria outbreak predictions. The model predictions are used to prepare the malaria outlook during November/December, and the information is passed to the iDEWS bureau to contribute towards containment actions such as insecticide spray planning decision-making. Water related Programme (West Africa, Philippine, Sri Lanka) Online Synthesis System for Sustainability and Resilience (OSS-SR): This is an e-learning function to provide users with introductory lectures, examinations, and classes of hands-on training, widely covering issues in climate change, flood management, and disaster risk reduction. Those who complete their e-Learning training through the OSS-SR, are then capable of utilizing the data system to send out official water related early warning/alerts, analyze risks and create hazard maps, are assigned to a city districts or communities to facilitate discussions to local adaptation action and urban planning and design, such as evacuation, contingency and land use plans. In the case of the Philippines until 2022, OSS-SR has empowered 93 national and local stakeholders (e.g., Department of Science and Technology, Department of Public Works and Highways, Metropolitan Manila Development Authority, and so on) and the importance of the OSS-SR has been widely acknowledged by the communities.

Our activities contribute SDG13: climate action, SDG3: Good Health and Well-Being, SDG6: Clean Water and Sanitation SDG11: Sustainable Cities and Communities.

Climate Data and Application Platform: We provide the computational environment to analyze climate-related big-data as a testbed for co-design and co-design for climate scientists, impact assessment researchers, and other stakeholders.

Health related Programme (South Africa)

Malaria Infection Prediction Early Warning System:

Together with local institutional networks (the infectious Disease Early Warning System: iDEWS bureau*), DIAS utilizes climate prediction-based AI and Machine Learning-based Malaria Transmission Prediction model to predict malaria transmission for 3-4 months ahead.

• South African Weather Service, The National Institute For Communicable Diseases, Department of Health, South African Medical Research Council, DOH Limpopo, Tzaneen Malaria Institute

Water related Programme (West Africa, Philippine, Sri Lanka)

Online Synthesis System for Sustainability and Resilience (OSS-SR):

OSS-SR, a web-based knowledge integration system for water-related disaster risk reduction, resilience, and sustainability provides localized scientific knowledge such as regarding real-time flood forecasting and climate change impact assessment.