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Niklas Elmqvist | Purdue University Pierre Dragicevic | INRIA Jean-Daniel Fekete | INRIA

“. ”. Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation. Niklas Elmqvist | Purdue University Pierre Dragicevic | INRIA Jean-Daniel Fekete | INRIA. Visualizing Complex Data. Complex visualization. ?. Complex dataset.

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Niklas Elmqvist | Purdue University Pierre Dragicevic | INRIA Jean-Daniel Fekete | INRIA

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  1. ” Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation Niklas Elmqvist | Purdue University Pierre Dragicevic | INRIA Jean-Daniel Fekete | INRIA Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  2. Visualizing Complex Data Complex visualization ? Complex dataset Many simple visualizations Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  3. 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 Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  4. 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 … Limitednumber of displayed dimensions! Scatterplots dimension B dimension A Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  5. Problem • Many (most?) interesting real-world datasets have manydimensions • Certainly more than a scatterplot can show! • Two possible solutions: • More complex visual representation • Parallel coordinates, DataMeadow, etc… • Lose simplicity of scatterplots • Create many scatterplots (one per combination of dimensions) • But how to visualize them? Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  6. 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 Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  7. Example: Scatterplot Matrix Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  8. 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? Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  9. 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 diceto see another side Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  10. 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” Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  11. Example: 3D Perspective Transition Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  12. 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 Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  13. Interaction Techniques Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  14. Demonstration DEMO Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  15. 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? Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation

  16. Questions? • Niklas ElmqvistElectrical & Computer EngineeringPurdue UniversityWest Lafayette, IN 47907-2035E-mail: elm@purdue.eduWeb: http://engineering.purdue.edu/~elm/

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