• DocumentCode
    3609310
  • Title

    A Guide to Earth Science Data: Summary and Research Challenges

  • Author

    Karpatne, Anuj ; Liess, Stefan

  • Volume
    17
  • Issue
    6
  • fYear
    2015
  • Firstpage
    14
  • Lastpage
    18
  • Abstract
    Recent growth in the scale and variety of Earth science data has provided unprecedented opportunities to big data analytics research for understanding the Earth´s physical processes. An upsurge of Earth science datasets in the past few decades are being continually collected using various modes of acquisition, at different scales of observation, and in diverse data types and formats. Earth science datasets, however, exhibit some unique characteristics (such as adherence to physical properties and spatiotemporal constraints) that present challenges to traditional data-centric approaches. In this article, the authors briefly introduce the different categories of Earth science datasets and further describe some of the major data-centric challenges in analyzing Earth science data.
  • Keywords
    Big Data; data analysis; geophysics computing; Earth science data; big data analytics research; data-centric approaches; Atmospheric modeling; Data models; Meteorology; Ocean temperature; Remote sensing; Sea surface; Earth science data; climate data; scientific computing;
  • fLanguage
    English
  • Journal_Title
    Computing in Science Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCSE.2015.127
  • Filename
    7310923