HCIL-2003-45

Eaton, C., Plaisant, C., Drizd, T.
December 2003
In Visualization 2003 Conference poster abstract compendium, IEEE, (2003) 40-41
HCIL-2003-45, CS-TR-4673
Although clear recognition of missing and uncertain data is essential for accurate data analysis, most visualization techniques do not adequately support these significant data set attributes. After reviewing the sources of missing and uncertain data we propose three categories of visualization techniques based on the impact that missing data has on the display. Finally, we propose a set of general techniques that can be used to handle missing and uncertain data.
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