The FlowVizMenu and
Parallel Scatterplot Matrix:
Hybrid Multidimensional Visualizations for Network
Exploration
Christophe Viau, École de technologie supérieure, Montreal
Michael J. McGuffin, École de technologie supérieure, Montreal
Yves Chiricota, Université du Québec à Chicoutimi, Chicoutimi
Igor 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 work
Using a Scatterplot Matrix (SPLOM)
and Node-Link Diagram to visualize a graph
GraphDice [Bezerianos et al., 2010]
Related work
Integration of scatterplots and parallel coordinates
Yuan et al., 2009
Steed et al., 2009
Holten and van Wijk, 2010
Our proposed interface
Our proposed interface
Parallel Scatterplot Matrix
Our proposed interface
FlowVizMenu
Parallel Scatterplot Matrix
Our proposed interface
Attribute-Driven
Layout
FlowVizMenu
Parallel Scatterplot Matrix
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)
Rotating around x- or y-axes causes a transition from
Scatterplot Matrix (SPLOM) to stacked Parallel Coordinates.
Scatterplot Matrix
(SPLOM)
Parallel Coordinates
Ordering of axes within P-SPLOM
Problem: traditional SPLOM
ordering doesn’t yield useful
parallel coordinates.
Axes are repeated in
each row and column
Repeated axes: useless for
parallel coordinates 
Ordering of axes within P-SPLOM
Solution: order the axes
according to a Latin square.
Each row and column
contains each axis once.
Useful parallel coordinates 
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 FlowMenu
with embedded visualization
• Smoothly animated
transitions
• Brushing and linking
• More than
two dimensions
possible with PCA
FlowVizMenu
In-out gesture to quickly
select axes of scatterplot
Attribute-Driven Layout (ADL)
ADL: Layout based on
a scatterplot selected
in the FlowVizMenu.
The network layout
can be a mixture of
• Attribute-Driven Layout (ADL)
• Manual layout
• Force-directed layout
Demo
Initial user feedback
Five 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 Objects
ARC 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 produce
interesting parallel
coordinates
Repeated axes: useless for
parallel coordinates 
P-SPLOM ordering
• We explored variants
of latin square