[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5391/IJFIS.2015.15.4.289

Saliency Score-Based Visualization for Data Quality Evaluation

Kim, Yong Ki (Department of Computer Science, Chungbuk National University)
Lee, Keon Myung (Department of Computer Science, Chungbuk National University)

Publication Information

International Journal of Fuzzy Logic and Intelligent Systems / v.15, no.4, 2015 , pp. 289-294 More about this Journal

Abstract

Data analysts explore collections of data to search for valuable information using various techniques and tricks. Garbage in, garbage out is a well-recognized idiom that emphasizes the importance of the quality of data in data analysis. It is therefore crucial to validate the data quality in the early stage of data analysis, and an effective method of evaluating the quality of data is hence required. In this paper, a method to visually characterize the quality of data using the notion of a saliency score is introduced. The saliency score is a measure comprising five indexes that captures certain aspects of data quality. Some experiment results are presented to show the applicability of proposed method.

Keywords

Data analysis; Visualization; Data quality analysis; Data quality metrics;

Citations & Related Records

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