Never forget your primary wealth, your and your family’s health, it will be your hope and your family’s hope for ever.

Exploring High-D Spaces with Multiform Matrices and Small

Multiplesby 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

Multiform Bivariate small Multiple

O O

O

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 PCP: a good alternation for multi variable

scatter plot Bad example: who can tell me what’s

going on here?

THANKS! You may find the demo at

http://unc.dl.sourceforge.net/sourceforge/geovistastudio/studiodemo1.zip

Enjoy!