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Bulletin of Chinese Academy of Sciences (Chinese Version)

Keywords

big data; scientific big data; big earth data; data-intensive science

Document Type

Article

Abstract

Big data occupies the strategic high ground in the era of knowledge economies and also constitutes a new national and global strategic resource. It is a new pattern for scientific discovery with less dependence on causality and heavy dependence on data correlation. It has become a data-intensive scientific paradigm, following previous paradigms of empirical, theoretical and computational science. The paradigm has shifted the methodology of scientific research from theories and models based on causal analysis to comprehensive mechanistic scientific discovery including correlation analysis. As a branch of big data, scientific big data includes internal characteristics such as non-repeatability, high uncertainty, high dimensionality, and computational complexity. External characteristics include data type, data volume, data acquisition, and data analysis. All these characteristics bring new challenges for the techniques and methods of processing scientific big data. On the basis of the above analysis, we raise four recommendations:scientific cognition of scientific big data, construction of scientific big data infrastructure, establishment of a scientific data research center, and the structuring of a scientific big data academic platform.

First page

768

Last Page

773

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

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