Readability Metrics for Network Visualization

Cody Dunne and Ben ShneidermanHuman-Computer Interaction Lab &

Department of Computer ScienceUniversity of Maryland

Contact: cdunne@cs.umd.edu

26th Annual Human-Computer Interaction Lab SymposiumMay 28-29, 2009 College Park, MD

Citations between papers in the ACL Anthology Network

NetViz Nirvana

1. Every node is visible2. Every node’s degree is countable3. Every edge can be followed from source to

destination4. Clusters and outliers are identifiable

Readability Metrics

• How understandable is the network drawing?• Continuous scale [0,1]• Example: Journal may recommend– 0% node occlusion– <2% edge tunneling– <5% edge crossing

• Also called aesthetic metrics• Global metrics are not sufficient to guide users• Node and edge readability metrics

Specific RMs

• Node Occlusion– Proportional to number

of distinguishable items– 1: Each node is uniquely

distinguishable– 0: All nodes overlap in

connected mass

C B

D

A

Specific RMs (cont)

• Edge Crossing– Number of crossings

scaled by approximate upper bound

C B

D

A

Specific RMs (cont)

• Edge Tunnels• Number of tunnels scaled by

approximate upper bound• Local Edge Tunnels• Triggered Edge Tunnels

C B

D

A

SocialAction

• Social network analysis tool• Statistical measures• Attribute ranking• Multiple coordinated views• Papers:

– A. Perer and B. ShneidermanBalancing Systematic and Flexible Exploration of Social NetworksIEEE Transactions on Visualization and Computer Graphics, 2006, 12, 693-700

– A. Perer and B. ShneidermanIntegrating statistics and visualization: case studies of gaining clarity during exploratory data analysisCHI '08: Proceeding of the 26th annual SIGCHI Conference on Human Factors in Computing Systems, ACM, 2008, 265-274

– A. Perer and B. ShneidermanSystematic yet flexible discovery: guiding domain experts through exploratory data analysisIUI '08: Proc. 13th International Conference on Intelligent User Interfaces, ACM, 2008, 109-118

Contributions

• Global readability metrics• Node and edge readability metrics• Real-time RM feedback as nodes are moved• Integrated into attribute ranking system

Demo

Node occlusion:

14Edge tunnels:

70Edge crossings:

180Spring coeff:

510x9

Rank by:Node Occlusion

Node occl:

4(-10)Edge tunnel:

26(-44)Edge cross:

159(-21)Spring coeff:

610x9

Rank by:Node Occlusion

Node occl:

0(-4)Edge tunnel:

14(-12)Edge cross:

157(-2)Spring coeff:

710x9

Rank by:Node Occlusion

Node occl:

0(-0)Edge tunnel:

14(-0)Edge cross:

157(-0)Spring coeff:

710x9

Rank by:Local Edge Tunnel

Node occl:

0 (-0)Edge tunnel:

0(-14)Edge cross:

155(-2)Spring coeff:

710x9

Rank by:Local Edge Tunnel

Node occl:

0(-0)Edge tunnel:

0(-0)Edge cross:

155(-0) Spr. coeff:

710x9

Rank by:Edge Crossing

Node occl:

0(-0)Edge tunnel:

0(-0)Edge cross:

85(-70) Spr. coeff:

710x9

Rank by:Edge Crossing

Future Work

• Snap-to-Grid tool pulls node to local maxima• Feedback for layout algorithms• Evaluation

– NetViz Nirvana useful for teaching network analysis• E. M. Bonsignore, C. Dunne, D. Rotman, M. Smith, T. Capone, D. L. Hansen and B.

ShneidermanFirst Steps to NetViz Nirvana: Evaluating Social Network Analysis with NodeXLSubmitted, 2009

– Integration into NodeXL to test RM effectiveness• www.codeplex.com/nodexl• M. Smith, B. Shneiderman, N. Milic-Frayling, E. M. Rodrigues, V. Barash, C. Dunne, T.

Capone, A. Perer and E. GleaveAnalyzing (Social Media) Networks with NodeXLC&T '09: Proc. Fourth international conference on Communities and Technologies, Springer, 2009

Conclusion

• Global RMs to judge readability of network drawings

• Node and Edge RMs for interactive identification of problem areas

• Network analysts and designers of tools should take drawing readability into account

Paper

C. Dunne and B. ShneidermanImproving Graph Drawing Readability by Incorporating Readability Metrics: A Software Tool for Network AnalystsHCIL Tech Report HCIL-2009-13, Submitted, 2009

Contact

cdunne@cs.umd.edu

Additional RMs

• Angular Resolution• Edge Crossing Angle• Node Size• Node Label

Distinctiveness• Text Legibility• Node Color & Shape

Variance• Orthogonality

• Spatial Layout & Grouping

• Symmetry• Edge Bends• Path Continuity• Geometric-path

Tendency• Path Branches• Edge Length

Layout:Force-Directed Layout

Contrasts in meaning between thesaurus categories

Interactions between graph-summarized groups proteins within the human body

Collaboration between cancer research organizations