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
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
• The VPL Research ‘Data Glove’
• Parkinson’s tremor, Lou Gehrig’s
Disease (ALS), Huntington’s
Disease
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
• 2 years graduate work in Neurophysiology
– Biophysical basis of Parkinson’s 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
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
• Compressed Dimensional Arrays
• EEG, ECG Spatiotemporal Isosurfaces
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
• Master’s Degree Student
– SDSU Learning Design & Technology Program
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]
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
3.1415926535897932384626433832795028841
97169399375105820974944592307816406286
20899862803482534211706798214808651328
23066470938446095505822317253594081284
81117450284102701938521105559644622948
95493038196442881097566593344612847564
82337867831652712019091456485669234603
48610454326648213393607260249141273724
58700660631558817488152092096282925409
17153643
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
3.1415926535897932384626433832795028841
97169399375105820974944592307816406286
20899862803482534211706798214808651328
23066470938446095505822317253594081284
81117450284102701938521105559644622948
95493038196442881097566593344612847564
82337867831652712019091456485669234603
48610454326648213393607260249141273724
58700660631558817488152092096282925409
17153643
Total 35
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
7
3
4
3
1
6
3
5
3
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
What did you observe?
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
PACE Boot Camp 2
SDSC,
SanCourtesy
Diego, CA,
October
15-16,
Slide:
of Sean
Ahern,
NICS2014
•
•
•
•
Scalars
Vectors
Tensors
Multi-dimensional
PACE Boot Camp 2
SDSC, San
Diego,
CA, October
15-16,NICS
2014
Slide:
Courtesy
of Sean Ahern,
Motivation For VISUALIZATION
Create visual representations based on underlying data that are
•
•
•
•
•
Concise
Unambiguous
Intuitive
Interactive
Scalable
(Yes)
(Preferably)
(Trainable)
(Desirable)
(We wish)
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
Plots and Charts
Image: d3js gallery by Michael Bostock
I
x1
II
y1
10 8.04
8 6.95
13 7.58
9 8.81
11 8.33
14 9.96
6 7.24
4 4.26
12 10.84
7 4.82
5 5.68
x2
10
8
13
9
11
14
6
4
12
7
5
III
y2
9.14
8.14
8.74
8.77
9.26
8.1
6.13
3.1
9.13
7.26
4.74
x3
IV
y3
x4
10 7.46
8 6.77
13 12.74
9 7.11
11 7.81
14 8.84
6 6.08
4 5.39
12 8.15
7 6.42
5 5.73
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
PACE Boot Camp
2
SDSC, San Diego, CA, October 15-16, 2014
8
8
8
8
8
8
8
19
8
8
8
y4
6.58
5.76
7.71
8.84
8.47
7.04
5.25
12.5
5.56
7.91
6.89
12
12
10
10
8
8
Y2
Y1
Anscombe’s Quartet
6
6
4
4
2
2
0
0
0
2
4
6
8
10
12
14
16
0
2
4
X1
6
8
10
12
14
16
X2
12
12
10
10
8
8
Y4
14
Y3
14
6
6
4
4
2
2
0
0
0
2
4
6
8
X3
10
12
14
16
0
5
10
X4
Anscombe 1973,TheAmerican Statistician
15
20
Process: Map scalar data to a color table
Visual Validation
Utility: To investigate range of data
Swift error diagnostic and visual validation
PACE Boot Camp 2
SDSC,(Heatmap
San Diego,
CA, October 15-16, 2014
Images: Mathworks.com
example)
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
Process: Connect data in a pair wise manner on
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
Y-Y axes
• Filter example
• Hover example
• All hit stats example
Utility: Summarize high dimensional data
Find trends and relationships
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
Parallel Sets
Image: Titanic Survivors by Michael Bostock
Process: Recursive mapping of hierarchical data
into rectangles
Treemap designed by
Ben Shneiderman,
UMD (1990) History and
examples
Utility: Compare
tree structures
and attributes of
varying depth
PACE Boot Camp 2
SDSC,UMD
San Diego, CA, October 15-16, 2014
Image: Treemap Demo,
Circular Treemap
Image: Kai Wetzel
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
Voronoi Treemap
Circa (2005): Michael Blazer and Deussen
WSJ’s SmartMoney
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC,Image:
San Diego,
CA, example
October by
15-16,
2014
Treemap
Michael
Bostock
Process: transform a hierarchical data into a
linearly proportionate rectangles
Interactive
Link
Utility: examine proportionate
PACE
Boot Camp 2
distribution
of hierarchical data
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
Image: Google Analytics
Sankey Diagrams
Image: Sankey Diagram by Michael Bostock
Process: topologically represent hierarchical
data
Utility:
Show and investigate relationships
PACE Boot Camp 2
SDSC,
San Diego,
CA, October
15-16,
2014 Bostock
Image:
Force Directed
Layout
by Michael
PACE Boot Camp 2
Image: Visualization by Angi Chau
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
Image: Uber taxi rides in San Francisco by Michael
SDSC,
San Diego, CA, October 15-16, 2014
Bostock
Image: Reingold-Tilford Tree by Michael Bostock
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
Marian Boguna, Fragkiskos Papadopoulos, and Dmitri Krioukov
“Geographic
Location of
Prague”
Cosmographia
Petrus Apianus, 1546
Edward
PACE Boot Camp
2 Tufte, “The Visual Display of Quantitative
Information”,
1983,
Graphics
SDSC, San Diego,
CA, October
15-16,
2014 Press
•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
Edward Tufte, “The Visual Display of Quantitative
Information”, 1983, Graphics Press
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
From “Atlas of Cancer Mortality for U.S.
Counties”, Mason et al, NIH 1975
“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”,
PACE Boot Camp 2
1983, Graphics Press
SDSC, San Diego, CA, October 15-16, 2014
•Hannibal’s campaign
in Spain, Gaul, and
northern Italy
•Napoleon’s 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”,
PACE Boot Camp 2
1983, 2014
Graphics Press
SDSC, San Diego, CA, October 15-16,
• 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
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
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
Edward Tufte, “The Visual
Display of Quantitative
Information”, 1983, Graphics
Press
Utilization of Primary Colors in Displaying More than One
Variable”, reviewed in American Statistician, 34 (1980)
Edward Tufte, “The Visual Display of Quantitative Information”,
PACE Boot Camp 2
1983, 2014
Graphics Press
SDSC, San Diego, CA, October 15-16,
“Mathematical Model for Urban Air
Pollution”, McRae et al, Atmospheric
Environment, 16 (1982)
Edward Tufte, “The Visual Display of Quantitative
Information”, 1983, Graphics Press
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
Electroencephalogram (EEG), time series
on left, 2D topographic brain maps on right
• Visualization of a 2-dimensional dataset
changing with time
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
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
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014
• In vivo
• In vitro
• In silico
• In situ
PACE Boot Camp 2
SDSC, San Diego, CA, October 15-16, 2014