Distribution-based Representation, Analysis, and Visualization for Large-Scale Datasets

As it becomes more difficult to analyze large-scale simulation output at full resolution, users will have to review and identify regions of interest by transforming data into compact information descriptors that characterize simulation results and allow detailed analysis on demand. Among many different feature descriptors, the statistical information derived from data samples is a promising approach to tame the big data avalanche, because data distributions computed from a population can compactly describe the presence and characteristics of salient features with minimal data movement. The ability to computationally summarize and process data using distributions provides an efficient and representative capture of the information content of a large-scale data set. In GRAVITY lab, we aim for developing novel and compact distribution-based data representations which can on one hand reduce the size of the overall data significantly via statistical summarization techniques, and on the other hand allows for compact and efficient stochastic data analysis and visualization for feature discovery.

Publications:

  • Ko-Chih Wang, Naeem Shareef, and Han-Wei Shen: Image and Distribution Based Volume Rendering for Large Data Sets, IEEE PacificVis 2018
  • Tzu-Hsuan Wei, Soumya Dutta, and Han-Wei Shen: Information Guided Data Sampling and Recovery using Bitmap Indexing, IEEE PacificVis 2018
  • 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)
  • Cheng Li, Han-Wei Shen: Winding Angle Assisted Particle Tracing in Distribution-Based Vector Field, SIGGRAPH Asia Symposium on Visualization 2017. [Honorable Mention award]
  • Soumya Dutta, Jonathan Woodring, Han-Wei Shen, Jen-Ping Chen, James P. Ahrens: Homogeneity guided probabilistic data summaries for analysis and visualization of large-scale data sets. PacificVis 2017: 111-120
  • 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, SciVis 2016]
  • Tzu-Hsuan Wei, Chun-Ming Chen, Jonathan Woodring, Huijie Zhang, Han-Wei Shen: Efficient distribution-based feature search in multi-field datasets. PacificVis 2017: 121-130
  • 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
  • Ko-Chih Wang, Kewei Lu, Tzu-Hsuan Wei, Naeem Shareef, Han-Wei Shen: Statistical visualization and analysis of large data using a value-based spatial distribution. PacificVis 2017: 161-170
  • 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)
  • Chun-Ming Chen, Soumya Dutta, Xiaotong Liu, Gregory Heinlein, Han-Wei Shen, Jen-Ping Chen: Visualization and Analysis of Rotating Stall for Transonic Jet Engine Simulation. IEEE Trans. Vis. Comput. Graph. 22(1): 847-856 (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)
  • Kewei Lu, Han-Wei Shen: A compact multivariate histogram representation for query-driven visualization. LDAV 2015: 49-56
  • Tzu-Hsuan Wei, Chun-Ming Chen and Ayan Biswas: Efficient Local Histogram Searching via Bitmap Indexing, Computer Graphics Forum. Vol. 34, No. 3, 2015.
  • Abon Chaudhuri, Tzu-Hsuan Wei, Teng-Yok Lee, Han-Wei Shen, Tom Peterka: Efficient Range Distribution Query for Visualizing Scientific Data. PacificVis 2014: 201-208
  • Teng-Yok Lee, Han-Wei Shen: Efficient Local Statistical Analysis via Integral Histograms with Discrete Wavelet Transform. IEEE Trans. Vis. Comput. Graph. 19(12): 2693-2702 (2013)
  • Kewei Lu, Abon Chaudhuri, Teng-Yok Lee, Han-Wei Shen, Pak Chung Wong: Exploring vector fields with distribution-based streamline analysis. PacificVis 2013: 257-264
  • Steven Martin, Han-Wei Shen: Transformations for volumetric range distribution queries. PacificVis 2013: 89-96
  • Abon Chaudhuri, Teng-Yok Lee, Bo Zhou, Cong Wang, Tiantian Xu, Han-Wei Shen, Tom Peterka, Yi-Jen Chiang: Scalable computation of distributions from large scale data sets. LDAV 2012: 113-120
  • Steven Martin, Han-Wei Shen: Histogram spectra for multivariate time-varying volume LOD selection. LDAV 2011: 39-46
  • Udeepta Bordoloi, David L. Kao, Han-Wei Shen: Visualization techniques for spatial probability density function data. Data Science Journal 3: 153-162 (2004)
  • Udeepta Bordoloi, David L. Kao, Han-Wei Shen: Visualization and exploration of spatial probability density functions: a clustering-based approach. Visualization and Data Analysis 2004: 57-64