explates: spatializing interactive analysis to scaffold visual exploration
DESCRIPTION
EuroVis 2013 conference presentation of the ExPlates data-flow system for multidimensional visualization.TRANSCRIPT
›› ExPlates ›› PivotLab ›› PurdueUniversity
›› ExPlatesSpatializing Interactive Analysis to
Scaffold Visual ExplorationWaqas Javed
Niklas ElmqvistPurdue UniversityWest Lafayette, IN, USA
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›› ExPlates ›› PivotLab ›› PurdueUniversity
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Life is a journey, not a destination.
›› ExPlates ›› PivotLab ›› PurdueUniversity
››“Life is a journey, not a destination.”
― Ralph Waldo Emerson (1803-1882)
Visual
Exploratio
n
›› ExPlates ›› PivotLab ›› PurdueUniversity
››visual exploration [ˈvɪʒʊəl -zjʊ- ˌɛkspləˈreɪʃən],
n.using visualization to analyze data, often without
prior knowledge or questions about the data
›› ExPlates ›› PivotLab ›› PurdueUniversity
›› GOAL
» Support visual exploration by spatializing the interaction
» Time → Space
» Externalizes not just the data,but also the exploration process
›› ExPlates ›› PivotLab ›› PurdueUniversity
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PREVIEW
›› ExPlates ›› PivotLab ›› PurdueUniversity
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Why is this important?Why is this difficult?
›› ExPlates ›› PivotLab ›› PurdueUniversity
››» Perception: many views
yield high visual clutter
» Memory: rememberingpast choices and results
» Reasoning: synthesizing multipledisparate findings is difficult
›› ExPlates ›› PivotLab ›› PurdueUniversity
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DUPLICATE ― NOT UPDATE!
›› ExPlates ›› PivotLab ›› PurdueUniversity
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Exploration Plates (ExPlates)
» Data-flow method for visualization that automatically spatializes interaction
Spatialize…
›› ExPlates ›› PivotLab ›› PurdueUniversity
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Plate Anatomy» Building block: exploration plate– Visualization state: data, mapping, view– Input and output ports (anchors)– Connected by wires
» Mutating ops create new plate(s)– Filtering, change visualization,
transforms
» Invariant ops update current plate– Color scale, viewport, formatting
›› ExPlates ›› PivotLab ›› PurdueUniversity
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Plate Types» Visualization plates: visual
representations of input data» Data plates: data transformations
from input to output» Annotation plates: add annotation
to specific locations on the canvas
›› ExPlates ›› PivotLab ›› PurdueUniversity
››Output anchors
Input anchors
Control area
Visualization area
Datawires
›› ExPlates ›› PivotLab ›› PurdueUniversity
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Canvas and Layout» Infinitely zoomable visual canvas–Mouse control + automatic operations
» Grid-based semi-automatic layout– Padding for data wires
» Two ways to create new plates–Manual (menu) or automatic
(spatializing)
›› ExPlates ›› PivotLab ›› PurdueUniversity
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DEMO
›› ExPlates ›› PivotLab ›› PurdueUniversity
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IMPLEMENTATION
›› ExPlates ›› PivotLab ›› PurdueUniversity
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Implementation» Web-based system (JavaScript +
SVG)» Google Data Source API– Google Docs (spreadsheets)– RSS/Atom feeds– XML files– CSV files
» Rendering: RaphaëlJS (raphaeljs.com)– Extensible with other SVG toolkits (D3,
etc)
›› ExPlates ›› PivotLab ›› PurdueUniversity
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›› ExPlates ›› PivotLab ›› PurdueUniversity
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DISCUSSION
›› ExPlates ›› PivotLab ›› PurdueUniversity
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Discussion and Limitations
» Scalability: complex exploration + size– Zooming and panning navigation–Web-based setting gives upper bound
» Expertise: web-based but not intended for novice-level users
» Comparison: relation to MDV tools– Data-flow (DataMeadow, GraphTrail)– Dashboard/workbench (Tableau,
Spotfire)
›› ExPlates ›› PivotLab ›› PurdueUniversity
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CONCLUSION
›› ExPlates ›› PivotLab ›› PurdueUniversity
››» Spatializing
exploration– Branching visual history– Duplicate, do not update
» Data flow system– Automatic layout
» Multidimensional data– Visualization + analysis
» Web-based prototype– Live, dynamic updates
›› ExPlates ›› PivotLab ›› PurdueUniversity
››Questions?
Niklas ElmqvistPurdue University
West Lafayette, IN, [email protected]
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All images are Creative Commons from Flickr.com