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# Limn: Using Image and Video Technology for Visualizing a Million Cases of Multivariate data - PowerPoint PPT Presentation

Limn: Using Image and Video Technology for Visualizing a Million Cases of Multivariate data. Di Cook, Les Miller, Manuel Suarez, Peter Sutherland, Jing Zhang. History. John McDonald’s 3D rotation and linked brushing in early 90s. Why Scale Visual Methods?.

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### Limn: Using Image and Video Technology for Visualizing a Million Cases of Multivariate data

Di Cook, Les Miller,

Manuel Suarez,

Peter Sutherland, Jing Zhang

History a Million Cases of Multivariate data

John McDonald’s 3D rotation and linked brushing in early 90s

Why Scale Visual Methods? a Million Cases of Multivariate data

All three data sets have correlation

approximately 0.7

Type of Data a Million Cases of Multivariate data

Real-valued multivariate,

spatio-temporal context, class information

Goals a Million Cases of Multivariate data

• Provide multiple scatterplot displays, either as several static plots, or a sequence of tour projections.

• Link brush between them in real-time.

For 100Gb of multivariate data:

Real-time Graphics a Million Cases of Multivariate data

GGobi can handle 1 million points, but…

• There is a lot of overplotting even when using pixel sized glyph.

• Brush slow to color with continuous updating.

• Tour is too slow to tolerate: use scramble

Problems with Large Data Sets a Million Cases of Multivariate data

• Data Reduction: MV binning produces visual artifacts, screen size induces a binning, though.

• Scaling of Methods: computation, storage, memory.

Screen Resolution a Million Cases of Multivariate data

• Limited screen space induces binning

• Alpha-blending removes focus from low density pixels

• Using grey scale

Indexing Projections a Million Cases of Multivariate data

nxp data matrix

Pixel resolution plot window

Limn Software a Million Cases of Multivariate data

Two Steps:

• Create indexing on projected data, or an animation sequence and save as QuickTime movie.

• View density plots or animation, and interact with it by brushing, and overlaying subsets of data.

* Code is written in Java

Data Description a Million Cases of Multivariate data

Seasonal metrics data computed on AVHRR images across the USA in 1989: SoST, SoSN, EoST,EoSN, MaxT, MaxN, TotalNDVI.

And land cover classes: agriculture, grassland, deciduous, evergreen, barren.

Demo a Million Cases of Multivariate data

• Scatterplot matrix

• Tour movie

Currently we’re also exploring… a Million Cases of Multivariate data

• Sampling distributions of the pixel population.

• Overlaying movies for working with larger data.

• Broader array of data parsers.

Contact Information a Million Cases of Multivariate data

Software is archived at: www.sourceforge.net

Email: [email protected]