• DocumentCode
    53498
  • Title

    Theory-Guided Data Science for Climate Change

  • Author

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

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Minnesota, Minneapolis, MN, USA
  • Volume
    47
  • Issue
    11
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    74
  • Lastpage
    78
  • 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
    climate mitigation; data handling; scientific information systems; statistical analysis; climate change; climate phenomena; data-science methods; physical nature; scientific insights; spatiotemporal nature; statistical analysis; theory-guided data science; Meteorology; Ocean temperature; Spatiotemporal phenomena; Temperature distribution; big data; climate change; data analysis; data mining; discovery analytics; scientific computing; theory-guided data science;
  • fLanguage
    English
  • Journal_Title
    Computer
  • Publisher
    ieee
  • ISSN
    0018-9162
  • Type

    jour

  • DOI
    10.1109/MC.2014.335
  • Filename
    6965271
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=53498