Trees and Cushions

Jack van WijkEindhoven University of Technology

Treemap Workshop, May 31, 2001

HCIL, University of Maryland

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

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?

Cushion TreemapsVisualization of Hierarchical Information

Jarke J. van Wijk

Huub van de Wetering

Eindhoven University of Technology

IEEE InfoVis’99

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

Treemap (Shneiderman, 1992)

A16

B3 C3 D10

E1 F2 G2 H4I4

E1

F2

C3H4

I4

G2

Alternating directions, area represents size

1400 files

3060 employees

How to emphasize structure?

Color? Linewidth? Nesting? Shading?

Use shaded geometric model!

Ridges for more insight

Binary tree

Ridges

Ridge + rotated ridge = cushion

+ =

z = ax + bx + cy + dy + e2 2

Standard treemap

Cushion Treemap

H = 0.75level

H = 0.50level

Demo

www.win.tue.nl/sequoiaview

May 21 2001: 45,000 downloads

Squarified Treemaps

Mark Bruls

Kees Huizing

Jarke J. van Wijk

Eindhoven University of Technology

Vissym’00, Amsterdam

hard to compare sizes hard to point at waste of pixels inaccurate size

Thin rectangles

(small leaves high in hierarchy

e.g., .cshrc)

How to avoid thin rectangles?

(emphasize structure by other means)

drop the single direction layout

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)

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

Result of squarification

directory

Squarified organization

Shaded frames for structure

Frames for structure

no maze running for the viewer depth in structure as frame height “remote cousins” are visibly separated by

indent

Organization

Directory structure

Visualization of Generalized Voronoi Diagrams

Alex Telea, Jarke van Wijk

Vissym’01, Ascona

Cushions

Cushions help to understand hierarchical spatial tesselations of the plane

How about cushions to visualize Generalized Voronoi Diagrams?

Generalized Voronoi diagrams

Polygon = area where N seeds are closest

N = 1 N = 2

Cushions and bevels

Cushions, bevels, color

N= 3 Cushions, bevels, color

Generalized Voronoi Diagrams

Many other types (different distance measures)

Applications

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

Standard visualizations

Enridged height field ...

f(x, y)

height(f(x, y))

linear mapping

non-linear mapping

Height field

Soft, convex ridges

Strong, convex ridges

Soft,concave ridges

Climate (January)

Color: Temperature; Height: Precipitation

Climate (July)

Color: Temperature; Height: Precipitation

Dense contours (equid. in space)

With ridges...

Hierarchical ridges

Back to Trees:Botanical Visualization of

Huge Hierarchies

Ernst Kleiberg, Huub van de Wetering, Jarke van Wijk

InfoVis’01, San Diego

Idea

Botanical trees are easy to understand, yet contain a lot of branches and leaves

Can we use ideas from botanical modeling for InfoVis?

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

Naive result...

Three problems

Continuing branches are hard to see Long, thin branches emerge Leaves are messy

Smoothed continuing branches

Contract long branches

Files: Phi-balls (Lintermann,99)

One big file Many small files

Botanical modeling

Compact, natural visualization Phyllotaxis = magic! Many treasures to be discovered Usability? Botanical treemaps?

My treemap to-do list

Non-rectangular shapes/subdivisions• circles, polygons?

Multivariate data• color, texture?

Applications• genealogy, data mining?

Evaluation