Three levels of data-driven science

International Meeting on High-Dimensional Data-Driven Science 2015

Igarashi, Yasuhiko^1 ; Nagata, Kenji^1 ; Kuwatani, Tatsu^2 ; Omori, Toshiaki^3 ; Nakanishi-Ohno, Yoshinori^1 ; Okada, Masato^1,4

Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba

277-8561, Japan^1

Department of Solid Earth Geochemistry, Japan Agency for Marine-Earth Science and Technology, 2-15 Natsushima-cho, Yokosuka

237-0061, Japan^2

Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Hyogo, Kobe

657-8501, Japan^3

ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, 2-1 Hirosawa, Wako, Saitama

351-0198, Japan^4

关键词: Computational theories;    Data driven;    Hierarchical structures;    High dimensional data;    Sparse modeling;    Spectral deconvolution;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/699/1/012001/pdf
DOI  :  10.1088/1742-6596/699/1/012001

来源: IOP

【 摘 要 】

A research project, called "the Initiative for High-dimensional Data-Driven Science through Deepening of Sparse Modeling" is introduced. A concept, called the three levels of data-driven science, is proposed to untie the complicated relation between many fields and many methods. This concept claims that any problem of data analysis should be discussed at different three levels: computational theory, modeling, and representation/algorithm. Based on the concept, how to choose a suitable method among several candidates is discussed through our study on spectral deconvolution. In addition, how to find a universal problem across the disciplines is presented by explaining our proposed ES-SVM method. Moreover, it is illustrated that the hierarchical structure of data analysis should be visualized and shared. From these discussions, we believe that data-driven science is mother of science, namely, a scientific framework that drives many fields of science.