Bento Box: An Interactive and Zoomable Small Multiples Technique for Visualizing 4D Simulation Ensembles in Virtual Reality

Seth Johnson, Daniel Orban, Hakizumwami Birali Runesha, Lingyu Meng, Bethany Juhnke, Arthur Erdman, Francesca Samsel, Daniel F. Keefe

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

We present Bento Box, a virtual reality data visualization technique and bimanual 3D user interface for exploratory analysis of 4D data ensembles. Bento Box helps scientists and engineers make detailed comparative judgments about multiple time-varying data instances that make up a data ensemble (e.g., a group of 10 parameterized simulation runs). The approach is to present an organized set of complementary volume visualizations juxtaposed in a grid arrangement, where each column visualizes a single data instance and each row provides a new view of the volume from a different perspective and/or scale. A novel bimanual interface enables users to select a sub-volume of interest to create a new row on-the-fly, scrub through time, and quickly navigate through the resulting virtual “bento box.” The technique is evaluated through a real-world case study, supporting a team of medical device engineers and computational scientists using in-silico testing (supercomputer simulations) to redesign cardiac leads. The engineers confirmed hypotheses and developed new insights using a Bento Box visualization. An evaluation of the technical performance demonstrates that the proposed combination of data sampling strategies and clipped volume rendering is successful in displaying a juxtaposed visualization of fluid-structure-interaction simulation data (39 GB of raw data) at interactive VR frame rates.

Original languageEnglish (US)
Article number61
JournalFrontiers in Robotics and AI
Volume6
DOIs
StatePublished - Jul 23 2019

Bibliographical note

Funding Information:
This work was supported in part by grants from the National Science Foundation (IIS-1251069, IIS-1218058) and the National Institutes of Health (1R01EB018205–01).

Funding Information:
The authors thank Bogdan Tanasolu, Georgi Subashki, and Shan Sandy Wang for assistance with developing simulations and data wrangling. Thanks to Dr. Paul Iaizzo and the University of Minnesota Visible Heart Lab for access to heart geometry data and feedback during iterative development. This work was supported in part with computing resources from the Minnesota Supercomputing Institute and hardware donations from NVidia. The software utilizes the VRPN library maintained by UNC-Chapel Hill's CISMM project with support from NIH/NCRR and NIH/NIBIB award 2P41EB002025. Funding. This work was supported in part by grants from the National Science Foundation (IIS-1251069, IIS-1218058) and the National Institutes of Health (1R01EB018205?01).

Publisher Copyright:
© Copyright © 2019 Johnson, Orban, Runesha, Meng, Juhnke, Erdman, Samsel and Keefe.

Keywords

  • 3D user interfaces
  • comparative visualization
  • ensemble visualization
  • small multiples
  • virtual reality

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