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Drag and Track: A Direct Manipulation Interface for Contextualizing Data Instances within a Continuous Parameter Space

Journal Article

Drag and Track: A Direct Manipulation Interface for Contextualizing Data Instances within a Continuous Parameter Space. Daniel Orban, Daniel F. Keefe, Ayan Biswas, James Ahrens, David Rogers. IEEE Transactions on Visualization and Computer Graphics (2018)

Abstract

We present a direct manipulation technique that allows material scientists to interactively highlight relevant parameterized simulation instances located in dimensionally reduced spaces, enabling a user-defined understanding of a continuous parameter space. Our goals are two-fold: first, to build a user-directed intuition of dimensionally reduced data, and second, to provide a mechanism for creatively exploring parameter relationships in parameterized simulation sets, called ensembles. We start by visualizing ensemble data instances in dimensionally reduced scatter plots. To understand these abstract views, we employ user-defined virtual data instances that, through direct manipulation, search an ensemble for similar instances. Users can create multiple of these direct manipulation queries to visually annotate the spaces with sets of highlighted ensemble data instances. User-defined goals are therefore translated into custom illustrations that are projected onto the dimensionally reduced spaces. Combined forward and inverse searches of the parameter space follow naturally allowing for continuous parameter space prediction and visual query comparison in the context of an ensemble. The potential for this visualization technique is confirmed via expert user feedback for a shock physics application and synthetic model analysis.

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