rolling the dice: multidimensional visual exploration using scatterplot matrix navigation 1 niklas...
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Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation 1Niklas Elmqvist | Purdue UniversityPierre Dragicevic | INRIAJean-Daniel Fekete | INRIA
“ ”Rolling the Dice: Multidimensional Visual Exploration
using Scatterplot Matrix Navigation
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Visualizing Complex Data
Complex dataset
Complex visualization
Many simple visualizations
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Motivation Information visualization is now more than 15
years old Lots of visual representations
New ones every year at IEEE InfoVis Varying complexity Varying purpose
Scatterplots: one of the simplest and most widely used visual representations Multidimensional data Examples: SpotFire, ADVIZOR, etc
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Scatterplots
Assign dimensions to graphical axes Two (typical) or three
Data cases as points in the space defined by axes
Additional dimensions Point color Point size Point shape …
Limited number of displayed dimensions!
dimension A
dimension B
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Problem Many (most?) interesting real-world datasets
have many dimensions Certainly more than a scatterplot can show!
Two possible solutions:1. More complex visual representation
Parallel coordinates, DataMeadow, etc… Lose simplicity of scatterplots
2. Create many scatterplots (one per combination of dimensions)
But how to visualize them?
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Scatterplot Matrices Idea: Create matrix of all data dimensions
Each column/row is a data dimension Each cell in the matrix is a scatter plot Reordering of columns/rows (automatic or manual)
Explored by others, but we add a twist: Use matrix as a space for navigation Visual exploration becomes a navigation problem
Result: Visualize complex data through sequence of simple visualizations
Example: Scatterplot Matrix
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Navigating Scatterplots Idea: Navigating from scatterplot A to scatterplot
B using an animated transition Problem with linear interpolation animation
No semantic meaning to the user Can be complex to follow
Compounded by large datasets Can we add meaning to the transition?
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Adding Meaning to Transitions Make the transition between scatterplots in the
scatterplot matrix easier to follow: Restrict to rectilinear movement (no diagonal
movement) Change only one visualized data dimension at a time
Utilize unused third graphical dimension for the new dimension to show during the transition
Metaphor: rotating a 3D scatterplot to show new 2D projection Like rolling dice to see another side
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Using the Third Dimension Lazy allocation 3rd graphical dimension
Invisible when viewing a 2D scatterplot, so can be assigned any data dimension
Allocation performed only during the transition Not “true” 3D – we use third dimension as a
presentation tool only Mechanics of performing 3D rotation:
Perspective view: 3-stage animation (extrusion, rotation, projection) Looks more natural, but requires three steps
Orthographic view: 1-stage animation (rotation) Only one step, but may look “weird”
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Example: 3D Perspective Transition
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Putting It Together ScatterDice application
Built in Java and uses OpenGL through JOGL Loads multidimensional datasets using the InfoVis
Toolkit [Fekete 2004]
Exploration by navigating a scatterplot matrix 3D transitions between adjacent scatter plots
Support reordering of dimensions Automatic: by correlation between dimensions Manual: drag and drop of rows columns
Interaction for the navigation is important
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Interaction Techniques
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Demonstration
Conclusions and Future Work Idea: Combine multiple simple visualizations
using interactive animation Visualize complex datasets Provide meaningful transitions
Interaction is a key element Avoid automated tours Allow refinement of queries
Future work Empirical evaluation of this method Other applications of the same approach?
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Questions? Niklas Elmqvist
Electrical & Computer EngineeringPurdue UniversityWest Lafayette, IN 47907-2035E-mail: [email protected]: http://engineering.purdue.edu/~elm/