This project proposes to study sensitivity analysis for guiding the evaluation of uncertainty of data in the visual analytics process We aim to achieve Semiautomatic Extraction of Sensitivity Information ID: 1006494
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1. Modeling the Uncertainty Due to Data/Visual Transformations using Sensitivity Analysis This project proposes to study sensitivity analysis for guiding the evaluation of uncertainty of data in the visual analytics process. We aim to achieve:Semi-automatic Extraction of Sensitivity InformationDifferential and Sampling-based Sensitivities of Graph-based Metrics and TransformationsSensitivity-guided Visual Representations and InteractionPI: Kwan-Liu MaCo-PI: Carlos Correa (now at Google)Postdoc: Yingcai Wu (now at MSRA)PhD Students: Yu-Hsuan Chan and Tarik CrnovrsaninPeriod: 9/2010-8/2012 (NCE to 8/2013)Amount: $316,918.00
2. A Framework for Uncertainty-Aware Visual AnalysisFormalize the representation of uncertainty & basic operationsQuantify, propagate, aggregate, and convey uncertainty introduced over a series of data transformationsEnhance and evaluate visual reasoning in an uncertainty aware manner with this framework
3. Centrality UncertaintyCentrality SensitivityRegression CubesGeneralized Sensitivity Scatterplot Flow-based Scatterplot Overview of Accomplishments
4. Flow-based Scatterplots Rank ProjectionsCluster by flow linesSensitivity Derivatives are estimated by local linear regression in (X,Y).Select by a flow lineFlow-based Scatterplots for Sensitivity Analysis, VAST 2010Streamlines are integrated similarly.
5. Generalized Sensitivity Scatterplots Sensitivity Derivatives are estimated by linear regression in a local neighborhoood of (X, Y, Z) in R3 Flow-based scatterplotGSS in R3Sensitivity Star GlyphsSensitivity FansXYZThe Generalized Sensitivity Scatterplot , submitted to TVCG
6. Rectangular SelectionsRegression CubesSensitivity SelectionsRegression Cube: A Technique for Multidimensional Visual Exploration and Interactive Pattern Finding, submitted to TiiS-VA
7. Rectangular SelectionsSensitivity SelectionsRegression CubesRegression Cube: A Technique for Multidimensional Visual Exploration and Interactive Pattern Finding, submitted to TiiS-VA
8. Results & ImpactVisualizing Flow of Uncertainty through Analytical Processes, InfoVis 2012Design Considerations for Optimizing Storyline Visualization, InfoVis 2012Visual Cluster Exploration of Web Clickstream Data, VAST 2012Visual Analysis of Massive Web Session Data, LDAV 2012Clustering, Visualizing, and Navigating for Large Dynamic Graphs, Graph Drawing 2012Ambiguity-Free Edge-Bundling for Interactive Graph Visualization, 18(5), IEEE TVCG 2012Visual Reasoning about Social Networks using Centrality Sensitivities, 18(1), IEEE TVCG 2012Visual Recommendations for Network Navigation, EuroVis 2011Visualizing Social Networks, Chapter 11, Social Network Data Analytics, Springer 2011
9. Extensions and OutreachSDAV: Scalable Data Management, Analysis and Visualization, UC Davis PI, $425,000.00 per year (2012-2017), DOE SciDACCo-Founder of IEEE Symposium on Large Data Analysis and Visualization (LDAV), 2011IEEE LDAV 2011, PI, $9,637.00, NSFSymposium Co-Chair, LDAV 2011LDAV Steering CommitteeCo-Chair, the 7th Ultra-Scale Visualization Workshop, SC12 Guest Editor, Big Data Visualization, IEEE Computer Graphics & Visualization, July/August 2013Kwan-Liu Ma
10. More Extensions & OutreachThree new projects on visual analytics for cyber intelligence with Northrop GrummanA new visual analytics project with HP LabUC Davis Center for VisualizationUC Davis Big Data Implementation CommitteeSelected invited talks on Big Data VisualizationSIGGRAPH Asia Workshop on Visualization, 2012UC Irvine CS Distinguished Lecture, 2012Seoul National University, 2012HP Lab, 2012IBM Almaden Research Center, 2012AMP Lab, UC Berkeley, 2011Keynote, PacificVis 2011XLDB 2011CEA/EDF/INRIA Summer School, France, 2011Kwan-Liu Ma
11. ThanksPapers athttp://vidi.cs.ucdavis.edu/research/uncertaintyvisQuestions?