trees and cushions jack van wijk eindhoven university of technology treemap workshop, may 31, 2001...
TRANSCRIPT
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Trees and Cushions
Jack van WijkEindhoven University of Technology
Treemap Workshop, May 31, 2001
HCIL, University of Maryland
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InfoVis at Eindhoven
Started 1998 Focus:
• Trees and graphs• Large data sets• Use of computer graphics knowledge
(textures, geometry, shading) to generate more effective visualizations
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Trees (T) and Cushions (C)
T+C: Cushion treemaps (InfoVis’99) T+C: Squarified treemaps (Vissym’00) C: Voronoi diagrams (Vissym’01) C: Enridged contour maps (Vis’01) T: Botanical vis (InfoVis’01) What next?
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Cushion TreemapsVisualization of Hierarchical Information
Jarke J. van Wijk
Huub van de Wetering
Eindhoven University of Technology
IEEE InfoVis’99
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Insight in structure of large trees
Why is my disk full? What is our product portfolio? How is this university organized?
Fuzzy questions: Visualization needed
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Treemap (Shneiderman, 1992)
A16
B3 C3 D10
E1 F2 G2 H4I4
E1
F2
C3H4
I4
G2
Alternating directions, area represents size
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1400 files
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3060 employees
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How to emphasize structure?
Color? Linewidth? Nesting? Shading?
Use shaded geometric model!
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Ridges for more insight
Binary tree
Ridges
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Ridge + rotated ridge = cushion
+ =
z = ax + bx + cy + dy + e2 2
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Standard treemap
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Cushion Treemap
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H = 0.75level
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H = 0.50level
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Demo
www.win.tue.nl/sequoiaview
May 21 2001: 45,000 downloads
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Squarified Treemaps
Mark Bruls
Kees Huizing
Jarke J. van Wijk
Eindhoven University of Technology
Vissym’00, Amsterdam
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hard to compare sizes hard to point at waste of pixels inaccurate size
Thin rectangles
(small leaves high in hierarchy
e.g., .cshrc)
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How to avoid thin rectangles?
(emphasize structure by other means)
drop the single direction layout
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Squarification algorithm
1. Start placing recs in one row
2. stop when aspect ratio stops getting better
3. repeat with remaining area and recs
Recursive per level (just like standard treemap algorithm)
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6
6
6
Squarification algorithm
66
aspect ratio: 8/3 3/2 4/1
6
6
4
9/4
4
9/2
6
64 3
49/27
6
6 4 32
etc.
6
6
4
3
2
2
1
6
6 4 3
2 2 1
25/9
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Result of squarification
directory
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Squarified organization
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Shaded frames for structure
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Frames for structure
no maze running for the viewer depth in structure as frame height “remote cousins” are visibly separated by
indent
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Organization
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Directory structure
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Visualization of Generalized Voronoi Diagrams
Alex Telea, Jarke van Wijk
Vissym’01, Ascona
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Cushions
Cushions help to understand hierarchical spatial tesselations of the plane
How about cushions to visualize Generalized Voronoi Diagrams?
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Generalized Voronoi diagrams
Polygon = area where N seeds are closest
N = 1 N = 2
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Cushions and bevels
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Cushions, bevels, color
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N= 3 Cushions, bevels, color
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Generalized Voronoi Diagrams
Many other types (different distance measures)
Applications
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Enridged Contour Maps
Van Wijk & Telea, Vis’01, San Diego
Given: Height field f(x,y) Required:
• Qualitative (where are the ridges) and • Quantitative (how high is this peak) info
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Standard visualizations
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Enridged height field ...
f(x, y)
height(f(x, y))
linear mapping
non-linear mapping
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Height field
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Soft, convex ridges
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Strong, convex ridges
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Soft,concave ridges
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Climate (January)
Color: Temperature; Height: Precipitation
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Climate (July)
Color: Temperature; Height: Precipitation
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Dense contours (equid. in space)
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With ridges...
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Hierarchical ridges
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Back to Trees:Botanical Visualization of
Huge Hierarchies
Ernst Kleiberg, Huub van de Wetering, Jarke van Wijk
InfoVis’01, San Diego
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Idea
Botanical trees are easy to understand, yet contain a lot of branches and leaves
Can we use ideas from botanical modeling for InfoVis?
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Strand model (Holton, 1994)
Mimics vascular system Each leaf is connected to one strand Branch = bundle of strands Rules define when a branch is split
First try: Each directory is a branch Each file is a leaf
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Naive result...
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Three problems
Continuing branches are hard to see Long, thin branches emerge Leaves are messy
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Smoothed continuing branches
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Contract long branches
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Files: Phi-balls (Lintermann,99)
One big file Many small files
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Botanical modeling
Compact, natural visualization Phyllotaxis = magic! Many treasures to be discovered Usability? Botanical treemaps?
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My treemap to-do list
Non-rectangular shapes/subdivisions• circles, polygons?
Multivariate data• color, texture?
Applications• genealogy, data mining?
Evaluation