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Ensemble simulations are one of the primary sources of uncertain data sets in scientific studies. While modeling and measuring a real-world phenomenon via simulations, the lack of knowledge regarding the ground-truth compels the scientists to use multiple initial conditions and/or different input parameters to get an estimate of the possible outcomes. The resulting ensemble data sets are used for decision making in real world and thus, are of prime importance to the weather and the geo-scientists. At GRAVITY lab, we have proposed various tools and techniques to analyze and visualize such ensemble datasets. Using information theoretic measures we quantify and visualize the uncertainty of ensemble features like isosurfaces and streamlines. We also develop effective visual analytic solutions to study the effect of input parameters and initial conditions on the ensemble results by performing various types of sensitivity analysis.
Publications:
Publications:
- Subhashis Hazarika, Ayan Biswas, Han-Wei Shen: Uncertainty Visualization Using Copula-Based Analysis in Mixed Distribution Models, IEEE Transactions on Visualization and Computer Graphics , 24(1): 934-943 (2018)
- Soumya Dutta, Chun-Ming Chen, Gregory Heinlein, Han-Wei Shen, Jen-Ping Chen: In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations.IEEE Trans. Vis. Comput. Graph. 23(1): 811-820 (2017). [Best Paper Honorable Mention award, IEEE SciVis 2016]
- Ayan Biswas, Guang Lin, Xiaotong Liu, Han-Wei Shen: Visualization of Time-Varying Weather Ensembles across Multiple Resolutions. IEEE Trans. Vis. Comput. Graph. 23(1): 841-850 (2017)
- Wenbin He, Xiaotong Liu, Han-Wei Shen, Scott M. Collis, Jonathan J. Helmus: Range likelihood tree: A compact and effective representation for visual exploration of uncertain data sets. PacificVis 2017: 151-160
- Soumya Dutta, Han-Wei Shen: Distribution Driven Extraction and Tracking of Features for Time-varying Data Analysis. IEEE Trans. Vis. Comput. Graph. 22(1): 837-846(2016)
- Hanqi Guo, Wenbin He, Tom Peterka, Han-Wei Shen, Scott M. Collis, Jonathan J. Helmus: Finite-Time Lyapunov Exponents and Lagrangian Coherent Structures in Uncertain Unsteady Flows. IEEE Trans. Vis. Comput. Graph.22(6): 1672-1682 (2016)
- Wenbin He, Chun-Ming Chen, Xiaotong Liu, Han-Wei Shen: A Bayesian approach for probabilistic streamline computation in uncertain flows. PacificVis (Notes) 2016: 214-218
- Chun-Ming Chen, Ayan Biswas, Han-Wei Shen: Uncertainty modeling and error reduction for pathline computation in time-varying flow fields. PacificVis 2015: 215-222
- Ayan Biswas, David S. Thompson, Wenbin He, Qi Deng, Chun-Ming Chen, Han-Wei Shen, Raghu Machiraju, Anand Rangarajan: An uncertainty-driven approach to vortex analysis using oracle consensus and spatial proximity. PacificVis 2015: 223-230
- Ayan Biswas, Han-Wei Shen: Evaluation of stream surfaces using error quantification metrics. Visualization and Data Analysis 2014: 90170Z
- Ayan Biswas, Soumya Dutta, Han-Wei Shen, Jonathan Woodring: An Information-Aware Framework for Exploring Multivariate Data Sets. IEEE Trans. Vis. Comput. Graph. 19(12): 2683-2692 (2013)
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