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Activity Number: 79
Type: Contributed
Date/Time: Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Graphics
Abstract #311026
Title: Exploring Huge Collections of Scatterplots
Author(s): Leland Wilkinson*+ and Tuan Dang
Companies: Skytree and University of Illinois at Chicago
Keywords: scagnostics ; scatterplots ; EDA

We introduce a method and an application for interactive exploration of a huge corpus of scatterplots. The method is based on scagnostics - nine characterizations of the 2D distributions of orthogonal pairwise projections on a set of points in multidimensional Euclidean space. These characterizations include measures such as, density, skewness, shape, outliers, and texture. Working directly with these measures, we can locate anomalies for further analysis or search for similar distributions in a giant scatterplot matrix. We also present an extension of this technique that can be applied to huge collections of images.

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