Steering data quality with visual analytics: The complexity challenge

Shixia Liu*, Gennady Andrienko, Yingcai Wu, Nan Cao, Liu Jiang, Conglei Shi, Yu-Shuen Wang, Seokhee Hong


研究成果: Review article同行評審

35 引文 斯高帕斯(Scopus)


Data quality management, especially data cleansing, has been extensively studied for many years in the areas of data management and visual analytics. In the paper, we first review and explore the relevant work from the research areas of data management, visual analytics and human-computer interaction. Then for different types of data such as multimedia data, textual data, trajectory data, and graph data, we summarize the common methods for improving data quality by leveraging data cleansing techniques at different analysis stages. Based on a thorough analysis, we propose a general visual analytics framework for interactively cleansing data. Finally, the challenges and opportunities are analyzed and discussed in the context of data and humans.

頁(從 - 到)191-197
期刊Visual Informatics
出版狀態Published - 12月 2018


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