• DocumentCode
    140963
  • Title

    iCoDA: Interactive and exploratory data completeness analysis

  • Author

    Ruilin Liu ; Guan Wang ; Wang, W.H. ; Korn, Flip

  • Author_Institution
    Dept. of Comput. Sci., Stevens Inst. of Technol., Hoboken, NJ, USA
  • fYear
    2014
  • fDate
    March 31 2014-April 4 2014
  • Firstpage
    1226
  • Lastpage
    1229
  • Abstract
    The completeness of data is vital to data quality. In this demo, we present iCoDA, a system that supports interactive, exploratory data completeness analysis. iCoDA provides algorithms and tools to generate tableau patterns that concisely summarize the incomplete data under various configuration settings. During the demo, the audience can use iCoDA to interactively explore the tableau patterns generated from incomplete data, with the flexibility of filtering and navigating through different granularity of these patterns. iCoDA supports various visualization methods to the audience for the display of tableau patterns. Overall, we will demonstrate that iCoDA provides sophisticated analysis of data completeness.
  • Keywords
    data acquisition; data analysis; data visualisation; data completeness analysis; data quality; data visualization methods; iCoDA; interactive completeness data analysis; tableau pattern generation; Data visualization; Detectors; Image color analysis; Loss measurement; Monitoring; Roads; Temperature sensors; Data completeness; exploratory pattern analysis; graph tableau discovery; pattern visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering (ICDE), 2014 IEEE 30th International Conference on
  • Conference_Location
    Chicago, IL
  • Type

    conf

  • DOI
    10.1109/ICDE.2014.6816747
  • Filename
    6816747