Visualizing Missing Data: Classification and Empirical Study (01 Mar 2005)
Most visualization tools fail to provide support for missing data. We identify sources of missing, and categorize data visualization techniques based on the impact missing data have on the display: region dependent, attribute dependent, and neighbor dependent. We then report on a user study with 30 participants that compared three design variants. A between-subject graph interpretation study provides strong evidence for the need of indicating the presence of missing information, and some direction for addressing the problem.
Article URL: ftp://ftp.cs.umd.edu/pub/hcil/Reports-Abstracts-Bibliography/2005-05html/2005-05.htm
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Next Article: Jef Raskin passed away peacefully on Saturday February 26th, 2005
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