• DocumentCode
    1791626
  • Title

    Department of energy strategic roadmap for Earth system science data integration

  • Author

    Williams, Dean N. ; Palanisamy, Giriprakash ; Shipman, Galen ; Boden, Thomas A. ; Voyles, Jimmy W.

  • Author_Institution
    Lawrence Livermore Nat. Lab., Livermore, CA, USA
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    772
  • Lastpage
    777
  • Abstract
    The U.S. Department of Energy (DOE) Office of Biological and Environmental Research (BER) Climate and Environmental Sciences Division (CESD) produces a diversity of data, information, software, and model codes across its research and informatics programs and facilities. This information includes raw and reduced observational and instrumentation data, model codes, model-generated results, and integrated data products. Currently, most of these data and information are prepared and shared for program specific activities, corresponding to CESD organization research. A major challenge facing BER CESD is how best to inventory, integrate, and deliver these vast and diverse resources for the purpose of accelerating Earth system science research. This paper provides a concept for a CESD Integrated Data Ecosystem and an initial roadmap for its implementation to address this integration challenge in the “Big Data” domain.
  • Keywords
    Big Data; data integration; geophysics computing; research and development; BER; CESD integrated data ecosystem; DOE; Earth system science data integration; US department of energy office; big data domain; biological and environmental research; climate and environmental sciences division; department of energy strategic roadmap; informatics programs; instrumentation data; integrated data products; model codes; model-generated results; observational data; Bit error rate; Communities; Data models; Data visualization; Earth; Meteorology; Standards;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004304
  • Filename
    7004304