Slide 1

Slide 2 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 3 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 B.S., Applied Physics, Condensed Matter San Diego State University Advanced Physical Measurement 357 Advanced Physical Pain Good at triple integrals of magnetic fields Slide 4 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 The VPL Research Data Glove Parkinsons tremor, Lou Gehrigs Disease (ALS), Huntingtons Disease Slide 5 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 2 years graduate work in Neurophysiology Biophysical basis of Parkinsons Disease Research wing of the Loma Linda VA under Dr. Ross Adey Growing neurons, testing them with amphetamines, HPLC Photoacoustic spectroscopy of neuromelanin for optical absorption properties Nonlinear Dynamical Analysis of EEG and Dopaminergic Neurodynamics Slide 6 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 7 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Compressed Dimensional Arrays EEG, ECG Spatiotemporal Isosurfaces Slide 8 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Adjuct Professor at Cuyamaca College Web Programming, PHP/MySQL, JavaScript, HTML5, CSS3, Flash Masters Degree Student SDSU Learning Design & Technology Program Slide 9 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Why do we care about visualization? [Next sequence of slides courtesy of Amit Chourasia, SDSC, Director of Vis Services] Slide 10 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 3.1415926535897932384626433832795028841 97169399375105820974944592307816406286 20899862803482534211706798214808651328 23066470938446095505822317253594081284 81117450284102701938521105559644622948 95493038196442881097566593344612847564 82337867831652712019091456485669234603 48610454326648213393607260249141273724 58700660631558817488152092096282925409 17153643 Slide 11 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 3.1415926535897932384626433832795028841 97169399375105820974944592307816406286 20899862803482534211706798214808651328 23066470938446095505822317253594081284 81117450284102701938521105559644622948 95493038196442881097566593344612847564 82337867831652712019091456485669234603 48610454326648213393607260249141273724 58700660631558817488152092096282925409 17153643 734316353734316353 Total 35 Slide 12 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 13 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 14 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 15 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 16 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 17 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 18 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 19 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 20 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 21 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 What did you observe? Slide 22 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Text (ASCII or Binary) Images (confocal microscopy, satellite imagery) High Dimensional (structured and Unstructured) Mesh discretizes space into points and cells -1D, 2D, 3D Slide: Courtesy of Sean Ahern, NICS Slide 23 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Scalars Vectors Tensors Multi-dimensional Slide: Courtesy of Sean Ahern, NICS Slide 24 Motivation For VISUALIZATION Create visual representations based on underlying data that are (Yes) (Preferably) (Trainable) (Desirable) (We wish) Concise Unambiguous Intuitive Interactive Scalable Slide 25 Visualization Techniques Scientific Viz Color Map Contours, Isosurface And Explicit Geometry Volumetric Streamlines Line Integral Convolution Topological Glyphs Information Viz Plots (scatter, bar, pie ) Heatmaps Parallel Coordinates Treemaps Partition Maps Flow Maps Networks Slide 26 Plots and Charts Image: d3js gallery by Michael Bostockd3js gallery Slide 27 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 IIIIIIIV x1y1x2y2x3y3x4y4 108.04109.14107.4686.58 86.9588.1486.7785.76 137.58138.741312.7487.71 98.8198.7797.1188.84 118.33119.26117.8188.47 149.96148.1148.8487.04 67.2466.1366.0885.25 44.2643.145.391912.5 1210.84129.13128.1585.56 74.8277.2676.4287.91 55.6854.7455.7386.89 mean(X) = 9, variance(X) = 11 mean(Y) = 7.5, variance(Y) = 4.12 linear regression lineY = 3 + 0.5*X correlation(X,Y) = 0.816 Slide 28 Anscombes Quartet Anscombe 1973,TheAmerican Statistician Slide 29 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Process: Map scalar data to a color table Visual Validation Images: Mathworks.com (Heatmap example)Mathworks.com Utility:To investigate range of data Swift error diagnostic and visual validation Slide 30 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Slide 31 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Process: Connect data in a pair wise manner on Y-Y axes Slide 32 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Filter example Hover example All hit stats example Utility: Summarize high dimensional data Find trends and relationships Slide 33 Parallel Sets Image: Titanic Survivors by Michael BostockTitanic Survivors Slide 34 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Process: Recursive mapping of hierarchical data into rectangles Image: Treemap Demo, UMDTreemap Demo Treemap designed by Ben Shneiderman, UMD (1990) History and examplesHistory and examples Utility: Compare tree structures and attributes of varying depth Slide 35 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Image: Kai WetzelKai Wetzel Circular TreemapVoronoi Treemap Circa (2005): Michael Blazer and DeussenMichael Blazer and Deussen Slide 36 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 WSJs SmartMoney Slide 37 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Image: Treemap example by Michael BostockTreemap example Slide 38 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Process: transform a hierarchical data into a linearly proportionate rectangles Utility: examine proportionate distribution of hierarchical data Interactive Link Slide 39 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Image: Google Analytics Slide 40 Sankey Diagrams Image: Sankey Diagram by Michael BostockSankey Diagram Slide 41 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Process: topologically represent hierarchical data Utility: Show and investigate relationships Image: Force Directed Layout by Michael BostockForce Directed Layout Slide 42 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Image: Visualization by Angi ChauVisualization Angi Chau Slide 43 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Image: Uber taxi rides in San Francisco by Michael BostockUber taxi rides in San Francisco Slide 44 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Marian Boguna, Fragkiskos Papadopoulos, and Dmitri Krioukov Image: Reingold-Tilford Tree by Michael BostockReingold-Tilford Slide 45 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Geographic Location of Prague Cosmographia Petrus Apianus, 1546 Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 46 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Show the data Substance rather than method Avoid distortion Many numbers in small space Make large datasets coherent Encourage comparison Multiple levels of detail Serve a clear purpose Integrate with statistical and verbal descriptions From Atlas of Cancer Mortality for U.S. Counties, Mason et al, NIH 1975 Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 47 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Location of cholera deaths relative to community water pumps, Dr. John Snow E. W. Gilbert, Pioneer Maps of Health and Disease in England, Geographical Journal, 1958 Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 48 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Hannibals campaign in Spain, Gaul, and northern Italy Napoleons March on Moscow, 1812-13 Charles Joseph Minard, Tableaux Graphiques et Cartes Figuratives de M. Minard, 1845-69. Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 49 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Complex ideas communicated with clarity, precision, and efficiency Gives the greatest number of ideas in the shortest time with the least ink in the smallest space Nearly always multivariate Requires telling the truth about the data Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 50 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Self-promoting Taken over by decorative forms or computer debris Purveys style rather than substance Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 51 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 52 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Utilization of Primary Colors in Displaying More than One Variable, reviewed in American Statistician, 34 (1980) Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 53 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Mathematical Model for Urban Air Pollution, McRae et al, Atmospheric Environment, 16 (1982) Electroencephalogram (EEG), time series on left, 2D topographic brain maps on right Edward Tufte, The Visual Display of Quantitative Information, 1983, Graphics Press Slide 54 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Visualization of a 2-dimensional dataset changing with time Slide 55 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 Create a stack of 2D Dataset Slices Use a visualization tool to create EEG Isopotential Contour Surfaces Slide 56 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 3D analog to 2D topographic contour lines on USGS quadrangle maps 2D contour lines represent points of constant value on a surface 3D contour surfaces represent points of constant value in a volume Slide 57 PACE Boot Camp 2 SDSC, San Diego, CA, October 15-16, 2014 In vivo In vitro In silico In situ