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The FlowVizMenu and Parallel Scatterplot Matrix:
Hybrid Multidimensional Visualizations for Network Exploration
Christophe Viau, École de technologie supérieure, MontrealMichael J. McGuffin, École de technologie supérieure, MontrealYves Chiricota, Université du Québec à Chicoutimi, ChicoutimiIgor Jurisica, Ontario Cancer Institute, Toronto
Network exploration by graph metrics
?
Network exploration by graph metrics
Computed metrics:• Degree
Network exploration by graph metrics
Computed metrics:• Degree• Closeness centrality• Clustering coefficient• K-core decomposition• ...
Network exploration by graph metrics
Computed metrics:• Degree• Closeness centrality• Clustering coefficient• K-core decomposition• ...
Multi-dimensional visualizations
Scatterplot Matrix(SPLOM)
Parallel Coordinates
Related workUsing a Scatterplot Matrix (SPLOM)and Node-Link Diagram to visualize a graph
GraphDice [Bezerianos et al., 2010]
Related workIntegration of scatterplots and parallel coordinates
Steed et al., 2009 Holten and van Wijk, 2010
Yuan et al., 2009
Our proposed interface
Parallel Scatterplot Matrix
Our proposed interface
Parallel Scatterplot Matrix
FlowVizMenu
Our proposed interface
Parallel Scatterplot Matrix
FlowVizMenu
Attribute-Driven Layout
Our proposed interface
A sequence of scatterplots
A sequence of scatterplots
Rotating scatterplots around the y-axis
Rotating scatterplots around the y-axis
Rotating scatterplots around the y-axis
Parallel Scatterplot Matrix (P-SPLOM)
Scatterplot Matrix(SPLOM)
Rotating around x- or y-axes causes a transition from Scatterplot Matrix (SPLOM) to stacked Parallel Coordinates.
Parallel Coordinates
Ordering of axes within P-SPLOM
Problem: traditional SPLOM ordering doesn’t yield useful parallel coordinates.
Repeated axes: useless for parallel coordinates
Axes are repeated in each row and column
Ordering of axes within P-SPLOM
Solution: order the axes according to a Latin square.
Useful parallel coordinates Each row and column contains each axis once.
Scatterplot Staircase (SPLOS)Inspired partly by quilts [Watson et al. 2008]
Sequence of scatterplots:treats one dimension differently.
Scatterplot Staircase (SPLOS): all dimensions treated uniformly; every adjacent pair of plots share an axis.
Parallel coordinates:more difficult to judge correlations than in scatterplots[Li et al., 2010]
FlowVizMenu
• Variant of a FlowMenuwith embedded visualization
• Smoothly animated transitions
• Brushing and linking• More than
two dimensionspossible with PCA
FlowVizMenu
In-out gesture to quicklyselect axes of scatterplot
Attribute-Driven Layout (ADL)
ADL: Layout based ona scatterplot selected in the FlowVizMenu.
The network layoutcan be a mixture of• Attribute-Driven Layout (ADL)• Manual layout• Force-directed layout
Demo
Initial user feedbackFive bioinformaticians used our prototype and gave feedback.
All had experience working with network data.
Results:
Pros:• Exploring along multiple metrics, smooth transitions,
and integration of views were judged useful• All participants stated they would use the interface
if it were made available to them
Cons:• Some pairings of metrics within the scatterplots
may not be useful• Too many hotkeys + button combinations
in the current prototype
Contributions:Three hybrid multidimensional visualization techniques for visualizing networks
Contributions:Three hybrid multidimensional visualization techniques for visualizing networks
• A Parallel Scatterplot Matrix (P-SPLOM) that transitions between a scatterplot matrix and parallel coordinates
Contributions:Three hybrid multidimensional visualization techniques for visualizing networks
• A Parallel Scatterplot Matrix (P-SPLOM) that transitions between a scatterplot matrix and parallel coordinates
Contributions:Three hybrid multidimensional visualization techniques for visualizing networks
• A Parallel Scatterplot Matrix (P-SPLOM) that transitions between a scatterplot matrix and parallel coordinates
• A FlowVizMenu to quickly select the dimensions for an embedded scatterplot
Contributions:Three hybrid multidimensional visualization techniques for visualizing networks
• A Parallel Scatterplot Matrix (P-SPLOM) that transitions between a scatterplot matrix and parallel coordinates
• A FlowVizMenu to quickly select the dimensions for an embedded scatterplot
Contributions:Three hybrid multidimensional visualization techniques for visualizing networks
• A Parallel Scatterplot Matrix (P-SPLOM) that transitions between a scatterplot matrix and parallel coordinates
• A FlowVizMenu to quickly select the dimensions for an embedded scatterplot
• An Attribute-Driven Layout to configure the graph according to a scatterplot of graph metrics
Future directions
• Application to other domains• Evaluation of performance and usability• Exploration of the design space of each visualization
(e.g., on a small screen)
Acknowledgments
We thank our collaborators for their feedback: • SAP Business Objects • Members of Jurisica Lab at OCI• Members of the Multimedia Lab at ETS
This research was funded by an SAP Business ObjectsARC Fellowship, NSERC, and the FQRNT.
Thank you
P-SPLOM: variants
P-SPLOM: Pearson correlation coefficient
P-SPLOM: Latin square
P-SPLOM: another latin square
Scatterplot Staircase
Parallel Scatterplot Matrix (P-SPLOM)
• Rotating around x- or y-axes causes a transition from Scatterplot Matrix (SPLOM) to stacked Parallel Coordinates
Ordering of axes within P-SPLOM
The traditional SPLOM ordering doesn’t produceinteresting parallel coordinates
Repeated axes: useless for parallel coordinates
P-SPLOM ordering
• We explored variants of latin square