Tree-Maps: A Space-Filling Approach to the Visualization of Hierarchical Information Structures Brian Johnson Ben Shneiderman (HCIL TR 91-06) Steve Betten February 14, 2001

Outline of Paper Introduction Comparison of methods Example: directory tree Treemap method Algorithms Coping with size Future research directions

Introduction Motivation: large hierarchical data Methods Spatial versus textual methods Interactive versus static methods Objectives Efficient space utilization, interactivity, comprehension, aesthetics Hierarchical data: structure and content Treemap emphasis on structure and leaves

Comparison of Methods Motivating example Viewing large file system hierarchies Existing methods Listings, outlines, tree diagrams General problems Navigational difficulty Hidden content information Text display of content information Treemap

Comparison: Existing Methods Listings (e.g. Unix ls, DOS dir ) Good: detailed content information Bad: navigation difficulty with explicit paths or manual traversal Outlines (e.g., Unix du, Windows explorer ) Good: display of both structure and content Bad: navigation difficulty; only a few lines of nodes show at a time Listing and Outlines Bad: required display space is linearly proportional to number of nodes

Comparison: Existing Methods (Continued) Tree diagrams Good Effectiveness and pleasantness for small hierarchies Bad Inefficient space utilization Connections between nodes 50% of display is background Only partial success of zooming and panning Lack of content information in large hierarchies Cluttering from text For visual cues, insufficient size of nodes

Comparison: Treemap Good Efficient utilization of display area Implicit display of structure No need to draw separate internal nodes More space for leaves and visual content cues Overview of entire hierarchy Rapid movement to any node Preservation of context Required display space is proportional to square root of number of nodes

Example: Directory Tree Problems with existing methods Outline (Windows explorer): too many lines Tree diagram (Open Windows File Manager): wasted space Venn diagram: wasted space Treemap (nested and non-nested) Easy identification of largest files on entire file system Easy identification of application, system, text, picture, and archive files

Treemap Method Structural information: partitioning Weight (degree of interest) for each node Properties Node overlap only with ancestors or descendents Node display area proportional to weight Node weight  sum of children's weights Structural information Implicitness via slice-and-dice Explicitness via additional nesting

Treemap Method (Continued) Content information Visual cues: color, texture, blinking Popup windows that display content Auditory cues that precede popup windows User control of properties that decreases on-screen complexity

Algorithms Drawing of treemap Tracking of cursor movement Interactive display of node details

Coping with Size Average case analysis: pixels per file Problem of small nodes not displaying Possible solutions: magnification, zooming Insignificance (can usually ignore them)

Future Research Directions Alternative partitioning methods Top-down Visual cues for numeric and non- numeric content information Dynamic views (animation over time) Stock portfolio Node operations Zooming, marking, selecting, searching

Favorite Sentence Beard: “Users are never lost because they can see the complete information space.” Expression of primary goal of treemap Use of 2D graphics and implicit internal nodes Display of entire hierarchy at once (structure) Significant visual cues for most nodes (content) Solution to previous navigation and content problems

Contributions Demonstration of application and effectiveness of treemap Provision of worthwhile direction for future research Alternative partitioning methods Applications: stock (Smartmoney) Propagation of treemap concept Widely cited paper from 1991 IEEE Visualization conference

Critique Good Definition of problem domain Comparison to existing methods Concrete and relevant example Algorithms Bad Lack of emphasis on the difficulty of comparing rectangles with different aspect ratios Future research

Treemap Developments Academia 1992: stock portfolio visualization 1994: decision making 1994: satellite management 1999: cushion treemap; squarified treemap 2000: parameterized rectangles 2000: TreeMap : pivot by size; pivot by position Industry DiskMapper SeeDiff software code viewer Storyspace hypertext authoring system Tcl/Tk widget Smartmoney PeopleMap Peets Coffee

Link Recommendations UMD HCIL history of treemap TreeMap Demo comparison of five treemap partitioning algorithms layout.html layout.html