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Making visualizations
C. Andrews
Visualization Pipeline
Raw
Data
data tables visual
structures visualization
data
transformations
visual
mappings
view
transformations
user interaction
Insight!
We are here
Relational data model
Item
row
tuple
record
case
Attributes
columns, variables, fields
Semantics
value - a single number or string
variable - the name of a single attribute of the thing being
measured (height, weight, etc…)
observation - set of values for all variables of the thing being
measured
Variable types
Measures (Dependent variables)
measurements of the data
can be analyzed and aggregated
Dimensions (Independent variables)
values that describe the data
dates, categories, names
Example: Tree growth
Tree
118
484
664
1004
1231
1372
1582
3
30
51
75
108
115
139
140
1
30
58
87
115
120
142
145
5
30
49
81
125
142
174
177
2
33
69
111
156
172
203
203
4
32
62
112
167
179
209
214
We have five trees. Every few months (118 days, 484 days,
etc…), someone measured the circumference of each tree and
recorded it in this table.
What are the variables? Which are the measures and which are the
dimensions?
Long vs wide data tables
Tree
age
circumference
1
118
30
1
484
58
1
664
87
1
1004
115
1
1231
120
1
1372
142
1
1582
145
2
118
33
2
484
69
2
664
111
2
1004
156
2
1231
172
2
1372
203
2
1582
203
3
118
30
3
484
51
3
664
75
3
1004
108
3
1231
115
3
1372
139
Tree
118
484
664
1004
1231
1372
1582
3
30
51
75
108
115
139
140
1
30
58
87
115
120
142
145
5
30
49
81
125
142
174
177
2
33
69
111
156
172
203
203
4
32
62
112
167
179
209
214
Tidy data
Tree
age
circumference
1
118
30
1
484
58
1
664
87
1
1004
115
1
1231
120
1
1372
142
1
1582
145
2
118
33
2
484
69
2
664
111
2
1004
156
2
1231
172
2
1372
203
2
1582
203
3
118
30
3
484
51
3
664
75
3
1004
108
3
1231
115
3
1372
139
•Every column is a variable
•Every row is an observation
•Every cell is a single value
Level of Measurement
Nominal
labels without ordering (e.g., genders, types of fruit)
Ordinal
a well ordered set of values (e.g., grades, military rank)
Quantitative
Interval
a distance can be computed between two values
Ratio
there is a fixed origin, or absolute smallest value on the scale
Quantitative measures
Binary (0 or 1, True or False)
Discrete (e.g., number of eyes, number of birds in a flock)
Continuous (e.g., temperature, length)
Visualization Pipeline
Raw
Data
data tables visual
structures visualization
data
transformations
visual
mappings
view
transformations
user interaction
Insight!
We are here
Visual mapping
visual mapping
Computable (math)
visual = f(data)
Comprehensible (invertible)
data = f-1(visual)
Creative
borrowed from C. North
Eight Visual Variables/Encodings/Aesthetics
Position
Glyph or Shape
Size (length, area, volume)
Brightness or Luminance
Color
Orientation
Texture
Motion
Encoding to chart
Encoding
Encoding
Encoding Mark
.
.
..
.
.
Mark
Chart
+
.
.
.
Mark
+
Variable
Variable
Variable
Scale
Axis
Scales and axes
0 1 2 3 4 5 6
0
1
2
3
4
5
6
(3,2)
400 px
Cartesian
𝛼
r
(r, 𝛼)
Polar
Circular
0
1
2
3
4
5
6
7
(3,2)
Encoding to chart: example
doctor
duration
Variables Encoding
position (x)
length
Mark
bar
Scales Chart
Graphical Interfaces
Declarative “Languages”/Libraries
Other Programming Libraries
Chart tools Data exploration tools
Excel, Google charts. plotly Tableau, Spotfire, DataVoyager
ggplot2, D3.js, Plot, Vega, Vega-lite, Altair, Bokeh, Plotly
Vis focused General graphics APIs
Matplotlib, VTK, Prefuse OpenGL, Processing, OpenFrameworks
