Abstract
Scientific visualization tools are rapidly embracing the necessary challenge of simultaneously visualizing multiple parameterized simulation data sets [8]. In the new paradigm, scientists hope to understand parameter relationships and stochastic trends that exist in a parameter space [6], [7]. At the same time, virtual reality (VR) environments have enabled exciting possible opportunities for exploring and comparing time varying spatial data sets [3]. Although VR offers a unique perspective to view 3D and 4D data, it requires high framerates for interactivity and optimized use of precious GPU memory. Accurate simulations, on the other hand, are often very large due to dynamic unstructured mesh resolutions and small timesteps, making it difficult to simply render even one data set. To solve this, large data visualization frameworks often use data sampling and efficient rendering techniques to engage the GPU [1], [8]. Even then, VR is mostly used to add a stereoscopic view, and is rarely an integral part of interactive data instance comparison [3].
Original language | English (US) |
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Title of host publication | 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 110-111 |
Number of pages | 2 |
ISBN (Electronic) | 9781538668733 |
DOIs | |
State | Published - Oct 2018 |
Event | 8th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2018 - Berlin, Germany Duration: Oct 21 2018 → … |
Publication series
Name | 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018 |
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Conference
Conference | 8th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2018 |
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Country/Territory | Germany |
City | Berlin |
Period | 10/21/18 → … |
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). Thanks to Bogdan Tanasolu, Georgi Subashki, and Shan “Sandy” Wang for simulation assistance and data wrangling. Thanks to Dr. Paul Iaizzo and the University of Minnesota Visible Heart Lab for access to heart geometry data.
Funding Information:
This work was supported in part by grants from the National Science Foundation (IIS-1251069,IIS-1218058)