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

Research output: Contribution to journalArticle

5 Scopus citations

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.

Original languageEnglish (US)
Article number8440838
Pages (from-to)256-266
Number of pages11
JournalIEEE Transactions on Visualization and Computer Graphics
Volume25
Issue number1
DOIs
StatePublished - Jan 2019

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Keywords

  • Direct Manipulation
  • Ensemble Visualization
  • Semantic Interaction
  • Shock Physics
  • Visual Parameter Space Analysis

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