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
Link To Document :
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