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Trees and Cushions Jack van Wijk Eindhoven University of Technology Treemap Workshop, May 31, 2001 HCIL, University of Maryland

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InfoVis at Eindhoven l Started 1998 l 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) l T+C: Cushion treemaps (InfoVis’99) l T+C: Squarified treemaps (Vissym’00) l C: Voronoi diagrams (Vissym’01) l C: Enridged contour maps (Vis’01) l T: Botanical vis (InfoVis’01) l What next?

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Cushion Treemaps Visualization 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 l Why is my disk full? l What is our product portfolio? l How is this university organized? Fuzzy questions: Visualization needed

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Treemap (Shneiderman, 1992) A16 B3C3D10 E1F2G2H4I4 E1 F2 C3 H4 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? l Color? l Linewidth? l Nesting? l 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 + e 2 2

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Standard treemap

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Cushion Treemap

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H = 0.75 level

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H = 0.50 level

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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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l hard to compare sizes l hard to point at l waste of pixels l 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 6 6 aspect ratio: 8/33/2 4/1 6 6 4 9/4 4 9/2 6 6 43 49/27 6 6 4 3 2 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 l no maze running for the viewer l depth in structure as frame height l “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 l Cushions help to understand hierarchical spatial tesselations of the plane l How about cushions to visualize Generalized Voronoi Diagrams?

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Generalized Voronoi diagrams Polygon = area where N seeds are closest N = 1N = 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 l Many other types (different distance measures) l Applications

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Enridged Contour Maps Van Wijk & Telea, Vis’01, San Diego l Given: Height field f(x,y) l 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 l Botanical trees are easy to understand, yet contain a lot of branches and leaves l Can we use ideas from botanical modeling for InfoVis?

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Strand model (Holton, 1994) l Mimics vascular system l Each leaf is connected to one strand l Branch = bundle of strands l Rules define when a branch is split First try: l Each directory is a branch l Each file is a leaf

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Naive result...

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Three problems l Continuing branches are hard to see l Long, thin branches emerge l 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 l Compact, natural visualization l Phyllotaxis = magic! l Many treasures to be discovered l Usability? l Botanical treemaps?

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My treemap to-do list l Non-rectangular shapes/subdivisions circles, polygons? l Multivariate data color, texture? l Applications genealogy, data mining? l Evaluation

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