Tree Structures (Hierarchical Information) cs5764: Information Visualization Chris North

Where are we? Multi-D 1D 2D Trees Graphs 3D Document collections Design Principles Empirical Evaluation Visual Overviews

Trees (Hierarchies) What is a tree? DAG, one parent per node Items + structure (nodes + associations) In table model? Add parent pointer attribute 1:M

Examples File system menus org charts Family tree classification/taxonomy Table of contents data structures …

Tasks Multi-D tasks, plus structure-based tasks: Find descendants, ancestors, siblings, cousins Overall structure, height, breadth, dense/sparse areas …

Tree Properties Structure vs. attributes Attributes only (multi-dimensional viz) Structure only (1 attribute, e.g. name) Structure + attributes Branching factor Fixed level, categorical

Tree Visualization Example: TreeView Why is tree visualization hard? Structure AND items Structure harder, consumes more space Data size grows very quickly (exponential) »#nodes = b height

2 Approaches Connection (node & link) outliner Containment (node in node) Venn diagram A CB A BC

Connection (node & link)

TreeView Good for directed search tasks subtree filtering (+/-) Not good for learning structure No attributes Apx 50 items visible Lose path to root for deep nodes Scroll bar!

Mac Finder Branching factor: Small large

Hyperbolic Trees Rao, “Hyperbolic Tree” Xerox PARC Inxight Focus+context

Cone Trees Robertson, “ConeTrees” Xerox PARC 3D for focus+context

PDQ Trees Overview+Detail of 2D tree layout Dynamic Queries on each level for pruning

PDQ Trees

Disk Tree Ed Chi, Xerox PARC Overview: Reduced visual representation

WebTOC Website map: TreeView + size attributes

FSN SGI file system navigator Jurassic Park Zooming?

Ugh!

Containment (node in node)

2 Approaches Connection (node & link) Outliner Containment (node in node) Venn diagram Structure vs. attributes Attributes only (multi-dimensional viz) Structure only (1 attribute, e.g. name) Structure + attributes A CB A BC

Pyramids

3D Containment

Treemaps Shneiderman, “Treemaps” Maryland zooming

Treemap Algorithm Calculate node sizes: Recurse to children node size = sum children sizes Draw Treemap (node, space, direction) Draw node rectangle in space Alternate direction (slice or dice) For each child: –Calculate child space as % of node space using size and direction –Draw Treemap (child, child space, direction)

Squarified Treemaps Wattenberg Van Wijk

Cushion Treemaps Van Wijk

Dynamic Query Treemaps

Treemaps on the Web Map of the Market: People Map: Coffee Map:

DiskMapper

Sunburst Stasko, GaTech Radial layout Animated zooming

Sunburst (vs. Treemap) + Faster learning time: like pie chart + Details outward, instead of inward + Focus+context instead of zooming - Not space filling - More space used by non-leaves - Less scalability? All leaves on 1-D space, perimeter Treemap: 2-D space for leaves

Misc.

CHEOPS Beaudoin, “Cheops”

The Original Fisheye View George Furnas, 1981 (pg 311) Large information space User controlled focus point How to render items? Normal View: just pick items nearby Fisheye View: pick items based on degree of interest Degree of Interest = function of distance from f and a priori importance DOI(x) = -dist(x,f) + imp(x) x f

Example: Tree structure Distance = # links between f and x Importance = level of x in tree Distance: I A a i ii b i ii B a i ii b i ii Importance: I A a i ii b i ii B a i ii b i ii DOI: I A a i ii b i ii B a i ii b i ii f

Challenges Multiple foci George Robertson, Microsoft Research

Polyarchies multiple inter-twined trees Visual pivot George Robertson, Microsoft Research

Nifty App of the Day SAS JMP

Summary Hyperbolic <1000 TreeMap <3000, attributes, collective Cheops = scale up