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!