[Big Data] Advanced Application Technologies to Boost Big Data Utilization for Multiple-Field Scientific Discovery and Social Problem Solving

※ Affiliations and titles are as of the end of the research activity.

Strategic Objective

Creation, advancement, and systematization of innovative information technologies and their underlying mathematical methodologies for obtaining new knowledge and insight from use of big data across different fields

Research Supervisor

Yuzuru Tanaka (Professor Emeritus, Hokkaido University)


Along with the penetration of ICT in society and the advance and spread of sensors, measurement instruments and observation equipment for gathering information in the real world, the amount of data obtained from various fields has grown exponentially and continues to become more diverse. Advanced integration and use of big data are expected to bring about science and technology innovation and the creation of intellectual value through new scientific discoveries, with development of the resulting knowledge leading to creation of social and economic value as well as improvement and optimization of services.

In this research area, studies will be carried out in cooperation with information science and mathematical science field, and various research fields (application fields) in which the use of big data can bring about a great social impact. In order to make scientific discoveries, solve challenging social and economic problems and achieve innovative value creation, large-scale and diverse relevant data which could not be accumulated by individual researchers or organizations will be mutually related and subjected to a high level of integrated analysis. In this way empirical research and development will be carried out on extraction and creation of the innovative knowledge and value that are hidden in big data. To this end the research area will aim for the empirical creation and sophistication of the necessary next-generation application technologies.

Specifically, by means of innovative technologies for high-level integration and use of big data, the research will empirically realize innovative value creation, solutions to challenging social and economic problems, and/or various scientific discoveries in areas such as life science, materials science, health and medical care, society and economy, urban infrastructure systems, disaster prevention and mitigation, agriculture, forestry and fisheries industry, outer space, and the earth’s environment. The purpose is not simply creating knowledge and value by applying existing core technologies. Rather, the aims are new empirical creation and sophistication of next-generation application technologies necessary for achieving the objectives, and establishment of comprehensive and integrated big data analytics system technology adapted to the characteristics of application fields.

Moreover, in this research area collaboration will be encouraged with the related research area, Advanced Core Technology for Big Data Integration, including the sharing and use of next-generation core technologies developed in that area.

Research Area Advisors

・Hajime Amano
President, ITS Japan

・Ryosuke Shibasaki
Professor, The University of Tokyo

・Masafumi Shimoda
Board Member, Mibyoshakai no Shindangijutsu Kenkyukai

・Ryosuke Suzuki
Consultant, Representative Director, Koyurugi Research Institute

・Koichi Takeda
Professor, Graduate School of Informatics / Director, Future Value Creation Research Center
Nagoya University

・Yasumasa Nishiura
Professor Emeritus, Hokkaido University

・Tomoko Matsui
Professor, The Institute of Statistical Mathematics

・Satoru Miyano
Designaten Professor, M&D Data Science Center, Tokyo Medical and Dental University

※Affiliations and titles are as of March 31, 2021.

International Advisors

・Costantino Thanos
Research Director, Institute of Information Science and Technologies

・Norbert Graf
Professor, Doctor, Director, Saarland University Hospital

・Nicolas Spyratos
Professor Emeritus, University of Paris Sud 11

・Nigel Waters
Professor Emeritus, University of Calgary

・Randolph Goebel
Professor, University of Alberta

※Affiliations and titles are as of March 31, 2021.

Year Started : 2013

Development of a knowledge-generating platform driven by big data in drug discovery through production processes.

Research Director:
Kimito Funatsu(Professor, The University of Tokyo)

Innovating “Big Data Assimilation” technology for revolutionizing very-short-range severe weather prediction

Research Director:
Takemasa Miyoshi(Team Leader, RIKEN)

Year Started : 2014

Establishing the most advanced disaster reduction management system by fusion of real-time disaster simulation and big data assimilation

Research Director:
Shunichi Koshimura(Professor, International Research Institute of Disaster Science, Tohoku University)

Exploring etiologies, sub-classification, and risk prediction of diseases based on big-data analysis of clinical and whole omics data in medicine

Research Director:
Tatsuhiko Tsunoda(Professor, Graduate School of Science, The University of Tokyo)

Detecting premonitory signs and real-time forecasting of pandemic using big biological data

Research Director:
Hiroshi Nishiura(Professor, Graduate School of Medicine, Kyoto University)

Statistical Computational Cosmology with Big Astronomical Imaging Data

Research Director:
Naoki Yoshida(Professor, Department of Physics / Kavli IPMU, The University of Tokyo)

Year Started : 2015

Data-driven analysis of the mechanism of animal development

Research Director:
Shuichi Onami(Team Leader, Center for Biosystems Dynamics Research, RIKEN)

Knowledge Discovery by Constructing AgriBigData

Research Director:
Masayuki Hirafuji(Project Professor, Graduate School of Agricultural and Life Sciences, The University of Tokyo)

Knowledge Discovery through Structural Document Understanding

Research Director:
Yuji Matsumoto(Team Leader, Center for Advanced Intelligence Project, RIKEN)

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