• DocumentCode
    1919531
  • Title

    Fast Data Analysis with Integrated Statistical Metadata in Scientific Datasets

  • Author

    Liu, Jialin ; Chen, Yong

  • Author_Institution
    Comput. Sci. Dept., Texas Tech Univ., Lubbock, TX, USA
  • fYear
    2012
  • fDate
    10-13 Sept. 2012
  • Firstpage
    602
  • Lastpage
    603
  • Abstract
    Scientific datasets, such as HDF5 and PnetCDF, have been used widely in many scientific applications. These data formats and libraries provide essential support for data analysis in scientific discovery and innovations. In this research, we present an approach to boost data analysis, namely Fast Analysis with Statistical Metadata (FASM), via data sub setting and integrating a small amount of statistics into datasets. We discuss how the FASM can improve data analysis performance. It is currently evaluated with the PnetCDF on synthetic and real data, but can also be implemented in other libraries. The FASM can potentially lead to a new dataset design and can have an impact on data analysis.
  • Keywords
    data analysis; libraries; meta data; statistical analysis; FASM; PnetCDF; data analysis; data formats; integrated statistical metadata; libraries; real data; scientific datasets; synthetic data; Atmospheric modeling; Computational modeling; Computer science; Data analysis; Libraries; Runtime; Temperature distribution; FASM; big data; data intensive computing; high performance computing; statistical techniques;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing Workshops (ICPPW), 2012 41st International Conference on
  • Conference_Location
    Pittsburgh, PA
  • ISSN
    1530-2016
  • Print_ISBN
    978-1-4673-2509-7
  • Type

    conf

  • DOI
    10.1109/ICPPW.2012.89
  • Filename
    6337537