Interactive Visualization of Large Graphs and

NetworksTamara Munzner

Stanford UniversityComputer Science Department

Contributions

• analysis of three software systems– relating intended tasks to spatial

layout, visual encoding choices

• two novel layout/drawing algorithms– scalable– targeted

Three Visualization Systems

generalgraph drawing infovis

domain specific

H3 PM Const

H3• web hyperlinks • quasi-hierarchical

Planet Multicast• MBone tunnels• find poorly placed

Constellation• parsed dictionaries• refine algorithms

Talk Outline• graph drawing, information

visualization background• software systems

– goal– previous work– video– discussion– evaluation

• general discussion• conclusion

Graph Drawing• automatic layout and drawing of node-link

graphs

Hofstadter. Godel, Escher, Bach. Gansner and North. Improved force-directed layouts.

Goal: help humans understand

• aesthetic criteria– minimize crossings– expose structure: hierarchy,

symmetry, circular

Tom Sawyer Software. Hierarchical Toolkit Tom Sawyer Software. Symmetric Toolkit Tom Sawyer Software. Circular Toolkit

System Scalability, Data Set Size

node count, log scale

1000 10M1K 100M1M100K10K10 1B

Web(pages)

manualdictionary

GEB figure

most GD systems

exceptional GD systems(dot, Gem3D)

H3

Planet Multicast

Constellation

MBone (tunnels)

Net(hosts)

Net(routers)

mid-size web sites

my site

Stanford graphics site

data sets

my systems

previous systems

Fundamental Idea

• extend reach of graph drawing with information visualization approach

• techniques– interactivity– incorporate domain-specific

information

Information Visualization

• external visual representation of data, exploits perceptual system to reduce human cognitive load

• find appropriate visual metaphor for data that is not implicitly spatial

Interactivity

• mimic reality– 2D paper: pan, zoom– 3D object: rotate, translate, scale

• beyond– semantics impossible in real world– distortion, multi-scale

Domain/Task Focus

• user-centered design, ethnography• understand high level goals

– maintain web site

• break down into lower level tasks– minimize user navigation to important

pages– find and fix broken links

• design visual encoding• evaluate effectiveness

Evaluating Visualization Systems

• quantitative algorithmic improvements

• conceptual framework analysis• impact/adoption• user studies• anecdotal evidence

System 1: H3

• time: 1996-8

• data: web hyperlinks– quasi-hierarchical

graphs: can find reasonable spanning tree using domain-specific information

• goal: scalability

• method: 3D hyperbolic

Background: Hyperbolic Space

• Focus+Context distortion– project from infinite hyperbolic to

finite euclidean– pick best model for useful distortion

conformal:geodesics warped

projective:angles warped

4x4 matrix

Background: Hyperbolic Space

• exponential room in space• exponential number of tree nodes

hyperbolic hemisphere area

exponential:2 sinh r

2

euclidean hemisphere areageometric:

2r2

Thurston and Weeks, The Mathematics of Three Dimensional Manifolds, Scientific American

2D hyperbolic plane

Previous Work: Hierarchies

Cone Trees[Robertson, Mackinlay, Card

91]

Tree Maps[Johnson, Shneiderman

91]

• hierarchies

• distortion: [Furnas, Brown, Carpendale, Keahey]

Robertson, Mackinlay and Card. "Cone Trees: Animated 3D visualizations of hierarchical information. Johnson and Shneiderman. Treemaps: A Space-filling Approach to the Visualization of Hierarchical Information

Previous Work: Distortion & Hierarchy

• 2D Hyperbolic Tree– [Lamping, Rao, Pirolli 94,95]– scalability analysis later

• Fractal [Koike, Yoshihara 93]

• SHriMP [Storey, Muller 95]– don’t scale

• taxonomy [Noik 94]

Lamping, Rao, and Pirolli. A Focus+Content Technique Based on Hyperbolic Geometry for Viewing Large Hierarchies.

Concurrent Work: Nicheworks

• Nicheworks [Wills 97]– layout scales to 1M nodes– linked views– multiple layout approaches

• very different visual metaphor

Wills et al. Nicheworks.

Concurrent Work: Skeletonization

• Skeletonization [Herman 98]– abstractions for tree structure

Herman et al. Skeletonization

H3 Layout• novel layout algorithm detailed in thesis

• hemisphere surface instead of linear circumference

• bottom-up pass: compute hemisphere sizes

• top-down pass: place child on parent surface

Information Density: Scale

center peripheral fringeH3 dozens hundreds thousands

2DPARC

dozens - hundreds

Lamping, Rao, and Pirolli. A Focus+Content Technique Based on Hyperbolic Geometry for Viewing Large Hierarchies.

Information Density: Codimension

dimspace

dim- structure = codim

webviz 3 1circle

2

H3 3 2hemisphere

1

(Carpendale) 3 3cubic grid

0

• want balance between clutter and void• topological approach to describing density• difference between structure and surrounding space

dense

sparse

Carpendale, Cowperthwaite, and Fracchia. Extending Distortion Viewing from 3D to 2D.

Evaluation: Scalability• drawing: constant

– incremental• exception: precision

• layout: linear in |E| – 110,000 edges in 12 seconds given DFS input

• limits:– computational: global layout in main memory– cognitive: disorientation past ~100K nodes

• large neighborhood not global overview• future: landmarks, LOD, abstraction

Evaluation: Impact• product from SGI

– Site Manager aimed at web content creators– bundled starting with Irix 6.3

• research use of library– interface for Skitter Internet tomography

data– analysis of Autonomous System data

• viewer use– 6 researchers converted data to use viewer

• image use– 6 reprint requests

Evaluation: User Study

• [Risden, Czerwinski, Munzner, Cook 00]

• compared 3 browsers for adding content to collection of web pages

snap portal(Yahoo style)

collapsible tree XML3D: H3 + lists

User Study Results• reliably faster for existing category task• no decline in quality for new category task

differencesstatistically significant

differencesstatistically insignificant

System 2: Planet Multicast

• time: 1996• joint work:

– Hoffman, Claffy, Fenner

• data: MBone tunnels • task: find badly

placed tunnels• goal: simple baseline• method: 3D

geographic

Previous Work: Geographic Network

• SeeNet3D– [Cox, Eick 95]– arcs on globe layout

• SeeNet– [Becker, Eick, Wilks 95]

• NSFNet– [Cox, Patterson 92]

Becker, Eick, and Wilks. Visualizing Network Data

Cox and Eick. 3D Displays of Network Traffic.

Cox and Patterson. Visualization Study of the NSFNet.

Geographic Layout

• distance as stand-in for resource usage– partially correlated

• geographical determination arduous– major scalability problem

• immediate comprehension– evocative, many image reprints

• Wired, National Geographic

– still picture captures much of function

Evaluation: Anecdotal Insights

…> pen-mbone-1.sprintlink.net(204.213.238.11) dc-mbone-1.sprintlink.net(206.229.87.99)

[1/64/tunnel]> elm.can.net(199.246.170.7) dc-mbone-1.sprintlink.net(206.229.87.99) [1/64/tunnel]> boston.terra.net(199.103.128.254) dc-mbone-1.sprintlink.net(206.229.87.99) [1/0/tunnel/querier]> NS.FLSIG.ORG(192.153.117.162) dc-mbone-1.sprintlink.net(206.229.87.99) [1/64/tunnel]> ace.mid.net(198.247.225.251) dc-mbone-1.sprintlink.net(206.229.87.99) [1/64/tunnel]> fw-mbone-1.sprintlink.net(206.61.106.99) dc-mbone-1.sprintlink.net(206.229.87.99)

[1/16/tunnel]> gateway10.crawford.com(198.69.210.2) dc-mbone-1.sprintlink.net(206.229.87.99) [1/32/tunnel]> csce-2--rngm-nb-f-1.net.tamu.edu(128.194.1.11) dc-mbone-1.sprintlink.net(206.229.87.99)

[1/64/tunnel]...

System 3: Constellation

• time: 1998-9• joint work:

– Guimbretière

• data: MindNet query results

• task: plausibility checking for linguists

• method: 2D custom• goal: targeted

Definition Graph• dictionary entry sentence• nodes: word senses• links: relation types

Semantic Network

• definition graphs as building blocks• unify shared words• large network

– millions of nodes– grammar checking now, translation

future– global structure known: dense

• probes return local info

Path Query• best N paths between two words• words on path itself

• definition graphs used in computation

Task: Plausibility Checking

• paths ordered by computed plausibility

• researcher hand-checks results– high-ranking paths believable?– believable paths high-ranked?– stop words

Top 10 Paths: kangaroo - tail

Goal

• create unified view of relationships between paths and definition graphs– shared words are key– thousands of words (not millions)

• special-purpose algorithm debugging tool – not understand the structure of English

Previous Work: Semantic Networks

• Visual Thesaurus– [Thinkmap applet]– casual browsing,

constant motion– < 20 nodes

• SemNet– [Fairchild, Poltrock,

Furnas 88]– multiple 3D layouts

Fairchild, Poltrock, and Furnas. SemNet: Three-Dimensional Graphic Representations of Large Knowledge Bases.

Thinkmap applet. www.thinkmap.com cited 3/09/00.

Traditional Layout

• avoid crossings– reason: avoid false attachments

A

C

B

ambiguity

A B

C D

artifact salience

Information Visualization Approach

• spatial position is strongest perceptual cue– encode domain specific attribute– plausibility gradient

Constellation Semantic Layout

• novel layout algorithm detailed in thesis– paths as backbone, definition graphs attached – curvilinear grid– iterative design for maximum semantics with reasonable information density

• allow crossings for long-distance proxy links

Selective Emphasis• highlight sets of boxes and edges

– interaction– additional perceptual channels

• avoid perception of false attachments

Evaluation: Layout Effectivness

Evaluation: Layout Comparison

dot H3

Talk Outline• graph drawing background• software systems

– goal– previous work– video– discussion– evaluation

• general discussion• conclusion

Visual Salience

• Planet Multicast– long-distance tunnels

• H3– distant points of possible interest

• fringe: aggregate information

• Constellation– selective emphasis– word size tied to importance

Canonical Word Size

Hidden State• Constellation avoids hidden state

– change salience instead of toggle drawing

• closed world assumption– if not visible, doesn’t exist– easy to forget previous actions– false negative conclusions

• H3, PM do have hidden state– non-tree links sometimes drawn – intra-city tunnels never drawn

Graph Functions

• structure discovery– pure spatial layout– implicit in traditional graph drawing

• contextual backdrop• linked view

Graph Functions

• structure discovery• contextual backdrop

– additional visual encoding• color, linewidth, shape, enclosure• combination more than sum of parts

• linked view

Contextual Backdrop

Graph Functions

• structure discovery• contextual backdrop• linked view

– brushing [Becker and Cleveland 88]– invoke other software components

Linked View

Contributions• detailed analysis of three software

systems– interactive, range of domain specificity– relate intended tasks to spatial layout,

visual encoding

• two novel layout/drawing algorithms– Constellation

• targeted design

– H3: • scales 100x beyond previous work • product, user study