Notes to Chapter Seven
English 308
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Data Displays
Data displays are
 Extra-level
 Include text (sometimes) but text is
secondary
 Greatly enhance readers’ ability to compare
numbers
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Data displays are useful
Because
 Some readers prefer to see visual
representative of numerical data
 Some sets of data are too complex for
readers to use them in text (tabular) form
 Some readers prefer a top-down perspective
of data, which can reveal trends and
relationships
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Two Ways of Viewing Data
Reason for Visit
Pct of Total
Computer
9%
English 100
17%
Tutoring
50%
Workshops
4%
WPE
20%
Designing Visual Language-Chapter 7
Reason for Visit
Computer
9%
WPE
20%
English 100
17%
Workshops
4%
Tutoring
50%
4
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The Design Process
We might begin the process by choosing a
chart type that might or might not be
effective.
For example, we might want to display
demographic information about who has
used a campus writing center.
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First Draft
African-American
Hispanic
Asian
Other
White
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Second Draft
White
6%
AfricanAmerican
8%
Other
10%
Hispanic
36%
African-American
Hispanic
Asian
Other
White
Asian
40%
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Third Draft
45
40
35
30
25
20
15
10
5
0
AfricanAmerican
Hispanic
Asian
Other
White
97-98
98-99
Designing Visual Language-Chapter 7
99-00
00-01
8
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Fourth Draft
00-01
White
Other
99-00
Asian
98-99
Hispanic
97-98
AfricanAmerican
0
20
Designing Visual Language-Chapter 7
40
60
9
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Fifth Draft
45
40
35
30
25
20
15
10
5
0
AfricanAmerican
Hispanic
Asian
Other
White
97-98
98-99
Designing Visual Language-Chapter 7
99-00
00-01
10
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Sixth Draft
45
40
35
30
African-American
25
Hispanic
Asian
20
Other
15
White
10
5
0
97-98
98-99
Designing Visual Language-Chapter 7
99-00
00-01
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Conventions of Data Displays—
Textual Elements
Textual elements provide
 Axes titles
 Axes labels
 Legends
 Titles
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Textual Elements
Chart Titles
Visits by School
Legend
CSULA Pct Fall 2000
Axes Titles
UWC Pct 1999-2002
25.0%
20.0%
15.0%
Pct of Total
10.0%
5.0%
Axes Labels
0.0%
ers
y
ics
on
s
es
ett
log
ati
L
om
c
o
n
nce
u
n
d
rvic
o
e
h
d
n
e
i
c
c
c
E
sa
nS
Te
lS
dE
Art
an
ma
nd
cia
u
a
s
o
H
S
es
ng
nd
nd
sin
eri
a
a
u
e
l
h
B
a
alt
gi n
tur
En
He
Na
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er
Oth
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Conventions of Data Displays—
Spatial Elements
Spatial elements include
 Display Type
 Size
 Shape
 Orientation
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Display Types: Pie Charts
Visits by Native Language
All Others
26%
English
30%
Chinese (all)
17%
Spanish
27%
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Display Types: Simple Bar
Charts
15006
14192
20
01
-
20
02
(P
ro
je
ct
ed
)
20
01
20
00
19
99
-
19
99
19
98
-
19
98
19
97
-
19
97
19
96
-
19
96
19
95
-
19
95
19
94
-
19
94
13907
10008
8702
19
93
-
11674
11457
10624
12564
20
00
-
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
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Display Types: Complex Bar
Charts
100%
90%
80%
70%
60%
D
50%
C
40%
B
30%
A
20%
10%
0%
1
2
3
4
5
Evaluation Question
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Display Types: Line Graphs
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
19
19
19
19
19
19
19
20
20
93
94
95
96
97
98
99
00
01
-19
-19
-19
-19
-19
-19
-20
-20
-20
94
95
96
97
98
99
00
01
02
(
Designing Visual Language-Chapter 7
Pro
jec
ted
)
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Display Types: Scatter Plots
60
50
40
East
West
North
30
20
10
0
0
1
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2
3
4
5
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Display Types: Data Maps
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Display Types: Gantt Chart
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Display Types: Graphical Matrix
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Conventions of Data Displays—
Graphic Elements
Graphic elements include
 Gridlines
 Plot Frames
 Tick Marks
 Background Shading
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Graphic Elements: None
18000
16000
14192
14000
13907
12564
12000
10000
15006
10624
11457
11674
10008
8702
8000
6000
4000
2000
0
1993-1994 1994-1995 1995-1996 1996-1997 1997-1998 1998-1999 1999-2000 2000-2001 2001-2002
(Projected)
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Graphic Elements: Gridlines
18000
16000
14192
14000
13907
12564
12000
10000
15006
10624
11457
11674
10008
8702
8000
6000
4000
2000
0
1993-1994 1994-1995 1995-1996 1996-1997 1997-1998 1998-1999 1999-2000 2000-2001 2001-2002
(Projected)
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Graphic Elements: Plot Frame
1 8000
1 5006
1 6000
1 41 92
1 3907
1 4000
1 2564
1 0624
1 2000
1 0000
1 1 457
1 1 674
1 996-1 997
1 997-1 998
1 0008
8702
8000
6000
4000
2000
0
1 993-1 994
1 994-1 995
1 995-1 996
1 998-1 999
1 999-2000
2000-2001
2001 -2002
(P r oj ected)
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Graphic Elements: Tick Marks
18000
16000
14192
15006
13907
14000
12564
11457
12000
10000
10624
11674
10008
8702
8000
6000
4000
2000
0
1993-1994
1994-1995
1995-1996
1996-1997
1997-1998
1998-1999
1999-2000
2000-2001
2001-2002
(Project ed)
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Graphic Elements: Shading
1 8000
1 5006
1 6000
1 41 92
1 3907
1 4000
1 2564
1 0624
1 2000
1 0000
1 1 457
1 1 674
1 996-1 997
1 997-1 998
1 0008
8702
8000
6000
4000
2000
0
1 993-1 994
1 994-1 995
1 995-1 996
1 998-1 999
1 999-2000
2000-2001
2001 -2002
(P r oj ected)
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Applying the Cognate Strategies
How do we apply this rich visual vocabulary
to data displays?
We can do so by considering the six cognate
strategies.
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Arrangement Questions
Which conventional genre (pie chart, bar
graph, etc.) should I use to structure the
data for my readers?
 Within this conventional genre, how can I
best organize the data to reveal patterns
and trends for this situation?

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Arrangement Strategies
Choose an appropriate display type for the
data—and be ready to change if the
selected display type does not work.
 Decide how you want to sequence or group
the data. Different sequences or groupings
create different emphases.

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Arrangement Strategies (cont.)
Which display type is best for this data?
100
90
90
4th Qtr
1st Qtr
13%
13%
80
70
2nd Qtr
17%
60
50
40
27.4
30
3rd Qtr
20
57%
10
20.4
20.4
0
1st Qtr
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3rd Qtr
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Arrangement Strategies (cont.)
Which display type is best for this data?
4 t h Qt r
1 st Qt r
13%
13%
2 n d Qt r
17%
3 r d Qt r
57%
4th Qtr
23%
3rd Qtr
26%
1st Qtr
23%
2nd Qtr
28%
Designing Visual Language-Chapter 7
90
80
70
60
50
40
30
20
10
0
2000
2001
1st Qtr 2nd 3rd Qtr 4th Qtr
Qtr
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Emphasis Questions
Which data, or trends in the data, need to
stand out?
 What do I want readers to notice most
when they use the display?

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Emphasis Strategies
Data displays give you enormous power to
control which data and which relationships
among the data to emphasize or deemphasize.
 With that power comes great ethical
responsibility.

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Emphasis Strategies
Here’s a simple line graph.
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Emphasis Strategies
Stretching the graph and adjusting its scale “changes”
how the data looks.
East
West
North
100
90
80
70
60
50
40
30
20
10
0
1st Qtr
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Emphasis Strategies
Squeezing the graph and adjusting its scale again
“changes” how the data looks.
East
West
North
50
45
40
35
30
25
20
1st Qtr
2nd Qtr
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Emphasis Strategies
Graphic coding can also be used for emphasis.
East
West
North
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25
20
15
10
5
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1st Qtr
2nd Qtr
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Clarity Questions
How can I ensure that my readers will
understand the display?
 What perceptual problems might readers
have deciphering this display, either its
individual pieces of data or the big picture
trends?

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Clarity Strategies
Clarity in data displays hinges largely on
how well they adhere to these perceptual
principles:
 Benchmarks
 Area
 Gray Scales
 Perspective
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Clarity Strategies: Benchmarks

When comparing data, we need a consistent
benchmark. Note how difficult it is in the chart below
to compare quarterly data for any group other than East.
180
160
140
120
North
100
West
80
East
60
40
20
0
1st Qtr
2nd Qtr
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4th Qtr
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Clarity Strategies: Areas


Using areas to represent data reduces clarity.
Comparing areas that represent data can be very
difficult. Is it clear from the chart below that B
represents 27.4, A and D represent 20.4, and C
represents 90?
D
A
B
C
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Clarity Strategies: Gray Scales


Using gray scales to represent data reduces clarity.
Comparing gray scales that represent data can be very
difficult. Is it clear what the different levels of gray
scale mean in the chart below?
D
East
West
North
C
B
A
0%
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20%
40%
60%
80%
100%
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Clarity Strategies: Perspective


Using perspective reduces clarity.
Comparing data in 3-D perspective can be very
difficult. Is it clear what the data proportions are in the
chart below?
100
80
East
60
West
40
North
North
20
East
0
1st Qtr
2nd Qtr
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Conciseness Questions
How can I get the most impact for the least
use of design elements?
 How can I avoid over-designing the
display?
 If I decide to embellish the display, does
the embellishment do some rhetorical
work?

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Conciseness Strategies
Data displays can be simple and direct or
highly embellished
 We can measure spatial conciseness in
terms of “data density” and graphic
conciseness in terms of “data-ink”

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Conciseness Strategies:
Spatial Conciseness
Data density measures how much data the display
contains relative to its area. For example in the chart on
the left, we have 4 pieces of data in about 8 square
inches. In the chart on the right, we have 12 pieces of
data in about 8 square inches.

100
100
90
90
80
80
70
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
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Conciseness Strategies:
Graphic Conciseness
Data-ink ratio measures how much graphic coding a data
display uses to show the data—bars, gridlines, tick
marks, and so on. For example, imagine how much toner
is needed to print the chart on the right compared to the
chart on the left.

100
90
4th Qtr
80
70
60
3rd Qtr
50
40
2nd Qtr
30
20
1st Qtr
10
0
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
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10
20
30
40
50
60
70
80
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Conciseness Strategies:
Textual Conciseness

The conciseness of the data display can also be
measured in terms of its textual cues—labels,
legends, titles, and the like. Compare the data
displays below.
Sales by Region
100
90
Sales by Unit
80
70
60
50
40
30
20
100
90
80
70
60
50
40
30
20
10
0
1st Qtr
10
2nd Qtr
0
3rd Qtr
4th Qtr
Quarter
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
East
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West
North
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Conciseness Strategies
While considering data density and dataink ratios might help you identify problem
areas, keep in mind that clarity and
conciseness always exist in a balance.
 As a rule, you should privilege clarity over
conciseness.

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Tone Questions
What tone do I want the display to project:
serious, friendly, tentative, authoritarian,
non-threatening, formal, informal,
technical?
 Which of these voices is appropriate for
readers in this situation?

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Tone Strategies

Compare the tone of these two displays.
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Tone Strategies

What is the tone of this chart?
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Tone Strategies

What is the tone of this chart?
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Tone Strategies

Or this chart?
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Ethos Questions
How can I design the data display so it
creates credibility for me, the other
authors, or the organization?
 What ethical problems can design choices
create?

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Ethos Strategies
Because data displays are so flexible and because
they can both reveal and hide trends and
relationships, writers/designers need to be, above
all, honest.
With data displays, ethos begins with the simple
question: Does the display tell readers an accurate
story about the data, or does it skew, twist, or
distort the data?
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Ethos Strategies


We’ve already
looked at stretched
and narrowed graphs
and “adjusted” scales
Here’s a data display
with regular scales.
1000
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800
700
600
500
400
300
200
100
0
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Ethos Strategies

Here’s the same data
in a display with
“adjusted” scales.
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600
500
400
300
200
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Ethos Strategies

Here’s the same data
on a logarithmic
scale
10000
100
1
1st Qtr
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Ethos Strategies
Deception problems can take many forms:
 Readers might be deceived and not realize
it, and even the writer might not realize it.
 Readers might detect the distortion,
leading to a loss of ethos for the writer.
 Readers might suspect deception, eroding
the credibility of the writer.
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Ethos Strategies

A heavy-handed design like this one might
lead readers to suspect that the writer is trying
to hide something.
East
100
North
West
50
West
North
East
0
1st Qtr
2nd Qtr
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Conclusion
Remember that the six cognate strategies do
not exist in separate, isolated packages but
constantly work together (and at times
against one another) to respond to the
rhetorical situation.
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