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Exploring High-D Spaces with Multiform Matrices and Small Multiples by Alan MacEachren etc. Presenter: Xu Liu Ming Luo

Outline Contribution Main ideas Demos Critiques

Contribution GeoVISTA development environment A general framework, ready for combination of any information visualization forms Dynamically visualize information with user interaction Explore high dimension by univariate and bivariate relations between attributes Find most significant relations between attributes

Multiform Bivariate small Multiple

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Multiform Bivariate Matrix

Multiform Bivariate Small Multiple and Matrix Multiple and matrix are designed as generic JavaBean components, providing a Java interface through which any bivariate representation form (instantiated as a JavaBean) can communicate. Visualization is updated dynamically with the user’s interaction

Find most significant relations between attributes Maximum conditional entropy between each pair of attributes Generate an ordering of attributes, which keeps a hierarchical clustering Select subspace interactively or automatically

Generate an ordering of attributes A node is an attribute An edge is the maximum conditional entropy between two attributes

Generate an ordering of attributes A node is an attribute An edge is the maximum conditional entropy between two attributes

Select subspace

Critiques Grid-based space-filling display It can not show more information than a simple scatterplot (maybe worse) Color legend needs training Rare visualization tools for more than 2 variables

Demo Basic Usage Conditioning Bi-variable: you see it’s hard to select colors Bi-variable PCP: a good alternation for multi variable scatter plot PCP Bad example: who can tell me what’s going on here? Bad example

THANKS! You may find the demo at vistastudio/studiodemo1.zip vistastudio/studiodemo1.zip Enjoy!