Theory-guided data science for climate change

James H. Faghmous; Arindam Banerjee; Shashi Shekhar; Michael Steinbach; Vipin Kumar; Auroop R. Ganguly; Nagiza Samatova

doi:10.1109/MC.2014.335

Theory-guided data science for climate change

James H. Faghmous, Arindam Banerjee, Shashi Shekhar, Michael Steinbach, Vipin Kumar, Auroop R. Ganguly, Nagiza Samatova

Research output: Contribution to specialist publication › Article

27 Scopus citations

Abstract

To adequately address climate change, we need novel data-science methods that account for the spatiotemporal and physical nature of climate phenomena. Only then will we be able to move from statistical analysis to scientific insights.

Original language	English
Pages	74-78
Number of pages	5
Volume	47
No	11
Specialist publication	Computer
DOIs	https://doi.org/10.1109/MC.2014.335
State	Published - Nov 2014
Externally published	Yes

Keywords

big data
climate change
data analysis
data mining
discovery analytics
scientific computing
theory-guided data science

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10.1109/MC.2014.335

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title = "Theory-guided data science for climate change",

abstract = "To adequately address climate change, we need novel data-science methods that account for the spatiotemporal and physical nature of climate phenomena. Only then will we be able to move from statistical analysis to scientific insights.",

keywords = "big data, climate change, data analysis, data mining, discovery analytics, scientific computing, theory-guided data science",

author = "Faghmous, {James H.} and Arindam Banerjee and Shashi Shekhar and Michael Steinbach and Vipin Kumar and Ganguly, {Auroop R.} and Nagiza Samatova",

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year = "2014",

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doi = "10.1109/MC.2014.335",

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pages = "74--78",

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AU - Kumar, Vipin

AU - Ganguly, Auroop R.

AU - Samatova, Nagiza

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N2 - To adequately address climate change, we need novel data-science methods that account for the spatiotemporal and physical nature of climate phenomena. Only then will we be able to move from statistical analysis to scientific insights.

AB - To adequately address climate change, we need novel data-science methods that account for the spatiotemporal and physical nature of climate phenomena. Only then will we be able to move from statistical analysis to scientific insights.

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KW - data analysis

KW - data mining

KW - discovery analytics

KW - scientific computing

KW - theory-guided data science

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JF - Computer

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Theory-guided data science for climate change

Abstract

Keywords

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