14 - 19 OCTOBER, 2012. SEATTLE, WASHINGTON, USA

Feature-Enhanced Map for 2D Multivariate Data with Uncertainty

Contributors: 
Keqin Wu, Song Zhang
Description
We present our method to solve the challenge of visualizing multivariate data with uncertainty in a single image. First, layers of spots enhanced with contour patterns are designed to encode multivariate information. Second, star glyphs are adapted to encode uncertainty information with each branch representing the uncertainty of an individual variable. Layers of sparse and similar glyphs allow for an easy and accurate interpretation of uncertainty. Distinct shapes and colors of spots and stars reduce the interference between the individual variables and their uncertainties. This feature enhancement allows the major features of individual variables to stand out in a sea of information.