Watson Innovations Cognitive Visualization Lab

1. Watson Innovations Cognitive Visualization Lab Readability metric feedback for aiding node-link visualization designers Cody Dunne cdunne@us.ibm.com ibm.biz/cogvislab August 10, 2015 Graph Summit 2015

2. Cody Dunne, PhD – Cognitive Visualization RSM Web: ibm.biz/codydunne Email: cdunne@us.ibm.com

3. Watson Graph Readability The team Mauro Martino Manager CVL Daniel Weidele Research Intern CVL Ben Shneiderman Professor UMD Steve Ross STSM CVL

4. Why Visualization? Anscombe’s quartet – Table

5. Why Visualization? Anscombe’s quartet – Statistics & Visualization

6. Why Visualization? Tukey No catalogue of techniques can convey a willingness to look for what can be seen, whether or not anticipated. Yet this is at the heart of exploratory data analysis. ... the picture-examining eye is the best finder we have of the wholly unanticipated. – Tukey, 1980

7. Node-Link Graph Visualization General Graph ≈ Network Node ≈ Vertex ≈ Entity Edge ≈ Link≈ Relationship≈ Tie

8. Watson Graph Readability Comparing two popular layout algorithms D3.js Force Layout GraphViz SFDP

9. Watson Graph Readability Immense variation in layout readability and speed Hachul & Jünger, 2006

10. Watson Graph Readability Evaluate, compare, and improve layouts Node Overlap How much of the underlyingnetwork structure can youunderstand from a given layout? Edge Crossings Edge Crossing Angle

11. Watson Graph Readability Measuring Readability Simple rules or heuristics Davidson & Harel, 1996 Global readability metrics Purchase, 2002 User performance Huang et al., 2007, etc. Source: Sugiyama, 2002, p. 14

12. Our metrics Existing metrics New Local • Node overlap • Edge tunnel • Drawing space used • Group overlap • Distance Coherence • Edge crossing • Angular resolution • Edge crossing angle • Stress

13. DEMO

14. Watson Graph Readability Node Overlap RM Global readability metric [0,1] where: 0 = Complete overlap 1 = No overlap Node readability metric Ratio of node area that overlaps other nodes

15. Watson Graph Readability Edge Crossing RM Global readability metric [0,1] where: 0 = All possible crossings 1 = No crossings Edge readability metric Just like gobal RM

16. Watson Graph Readability Edge Crossing RM (continued) Node readability metric [0,1] where: 0 = All possible crossings 1 = No crossings

17. Watson Graph Readability Goal Evaluate, compare, and improve layouts • Layout algorithm heuristics and parameters • User-generated or user-modified layouts • Manual layout suggestions a la snap-to-grid • Fully automatic layouts • Recommend layouts and parameterizations

18. Watson Graph Readability Layout algorithm & design comparison interface

19. Watson Graph Readability Machine learning to identify best layout • Train a model M(G,S(G),L,P(L))->(RM,UO) • Graph G with statistics S(G), layout algorithm L and parameters P(L) • Readability metrics for L on G with P(L) • argmax_{L,P(L)|(G?),S(G),RM'} M, with RM'⊆RM as the optimal layout

20. Watson Graph Readability Use in practice • Need interface on top of your graph store • Data cleaning, process sanity check • Exploration • Must be able to evaluate effectiveness • Works with aggregate views

21. Watson Graph Readability Discussion • Raise awareness of readability issues • Localized identification of where improvement is needed • Optimization recommendations for tasks • Interactive optimization • Future optimization plans Dunne C, Ross SI, Shneiderman B, and Martino M (2015), “Readability metric feedback for aiding node-link visualization designers”. IBM Journal of Research and Development. Dunne C and Shneiderman B (2009), "Improving graph drawing readability by incorporating readability metrics: A software tool for network analysts". University of Maryland. Human-Computer Interaction Lab Tech Report No. (HCIL-2009-13).