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Stronger Research Reporting Using Visuals
Applying Visual Design for Better Research – VCU Workshop
5th October, 2011
2
We live in a time of unprecedented
Information Overload
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“ The highest-paid person in the first half of the next century
will be the ‘storyteller.’ ”
Rolf Jensen, 1996
As Story-tellers, we learn..
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To write for the reader, not for yourself
As Story-tellers, we learn..
5
To write for the reader, not for yourself
A story needs a logical flow
As Story-tellers, we learn..
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To write for the reader, not for yourself
A story needs a logical flow
To have a point of view
As Story-tellers, we learn..
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To write for the reader, not for yourself
A story needs a logical flow
To have a point of view
Only to report data that is vital to
telling the story
How can visuals help in storytelling?
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Attention
Comprehension
Complexity
Understanding
Retention
Aesthetics
Timing
Emotion
The eyes are drawn like a magnet to images.
Graphics reduce time required to explain.
What’s wrong with wanting it to look good?
Pictures do a far better job of communicating emotion, and emotion does a far better job of inspiring action.
Presence of illustrations significantly improves retention.
Best way to summarise / represent complexity.
Less cognitive processing required, especially if image is familiar.
Can reveal patterns and relationships that would otherwise be hard to interpret or spot
Types of Visuals
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Graphs
Illustrations
Data Viz
“Best 100 non-fiction books of the twentieth
century”
- amazon.com
Graphs
“When a graph is made, quantitative and categorical information is encoded by a display method. Then the
information is visually decoded. This visual perception is a vital link. No matter how clever the choice of the
information, and no matter how technologically impressive the encoding, a visualization fails if the decoding fails.”
(William S. Cleveland, The Elements of Graphing Data, Hobart Press, 1994, p. 1)
To 3D or not to 3D?
Series 1
Series 30
1
2
3
4
5
Series 1Series 2Series 3
To 3D or not to 3D?
Series 1
0
2
4
6
Series 1
To 3D or not to 3D?
Series 10
2
4
6
Series 1
To 3D or not to 3D?
Series 1
0
2
4
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Category1
Category2
Category3
Category4
Series 1
To 3D or not to 3D?
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2
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Series 1
To 3D or not to 3D?
0
2
4
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Series 1
To 3D or not to 3D?
0
2
4
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Series 1
0
1
2
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Category 1 Category 2 Category 3 Category 4
Series 1
Series 2
Series 3
To 3D or not to 3D?
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Losing Perspective
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Losing Perspective
Losing Perspective
0
0.1
0.2
0.3
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0.6
0.7
0.8
0.9
1
Category 1 Category 2 Category 3 Category 4
Areas, Volumes and Magnitudes
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0.1
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0.9
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Category 1 Category 2 Category 3 Category 4
Areas, Volumes and Magnitudes
Ratio of size from Cat 1 to 2 is 1:2 BUT ratio or shape area is 1:4
Areas, Volumes and Magnitudes
0
0.5
1
Category1 Category
2Category
3Category
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Areas, Volumes and Magnitudes
Lie factor = size of effect shown in graphic / size of effect in data
Areas, Volumes and Magnitudes
Areas, Volumes and Magnitudes
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2
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Category 1 Category 2 Category 3 Category 4
Series 3
Series 2
Series 1
Areas, Volumes and Magnitudes
Who ate all the Pies?
Sales 1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Who ate all the Pies?
Sales 1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Who ate all the Pies?
Sales 1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Who ate all the Pies?
We make angle judgments when we read a pie chart, but we don’t judge angles very well. These judgments
are biased; we underestimate acute angles (angles less than 90°) and overestimate obtuse angles
(angles greater than 90°). (Naomi Robbins, Creating More Effective Graphs, Wiley, 2005, p. 49)
Who ate all the Pies?
Who ate all the Pies?
17%
22%
58%
8% Sales 1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Who ate all the Pies?
13%
17%
62%
8%
Q2
17%
22%
58%
8%
Q1
8%
23%
60%
9%
Q3
6%
26%
58%
10%
Q4
Who ate all the Pies?
0%
10%
20%
30%
40%
50%
60%
70%
Q1 Q2 Q3 Q4
Apples
Oranges
Bananas
Grapefruit
Hollands and Spence found that trends are best analyzed with line graphs than with a series of pie charts. When estimating trends with line graphs, people can use a slope estimation procedure; with pie charts, they must perform multiple size discriminations between pie slices.
Hollands JG, Spence I. Judgments of change and proportion in graphical perception. Hum Factors 1992;34:313-34.
Chart Junk & Data Ink
4.3
2.5
3.5
4.5
2.4
4.4
1.8
2.8
2
2
3
5
$0.00 $1.00 $2.00 $3.00 $4.00 $5.00 $6.00
Category 1
Category 2
Category 3
Category 4
Chart Junk & Data Ink
Gillan and Richman found that participants had faster response times and were more accurate when the data-ink ratio was high than when it was low. In addition, integrated tasks (e.g., global comparisons or synthesis judgments) appear to be more affected by the data-ink ratio than are focused tasks (e.g., selecting the value of a data point).
Gillan DJ, Richman EH. Minimalism and the syntax of graphs. Hum Factors 1994;36:619-44
Lipkus I M , Hollands J G J Natl Cancer Inst Monogr 1999;1999:149-163, Oxford University Press
Chart Junk & Data Ink
Recap…
Data Integrity – avoid:
Data Clarity – avoid:
1. 3 dimensional treatments
2. Tricks of perspective
4. Too many pies
3. Lie-factors of area or volume
5. Unnecessary clutter
6. A low data-to-ink ratio
Tufte’s 5 principles of GOOD information design
5. Completely integrate words, numbers and images
3. Show multivariate data (more than 2 dimensions)
1. Enforce visual comparisons between groups
4. Content driven—all about explaining the data
2. Show or suggest causality
1. Enforce comparison
In other words, we must always ask the question, “compared to what?”.
Fortunately, visual comparison is faster and easier than mathematical or conceptual comparison:
“visualization made it possible to see the effects
of design changes on the pressure distribution
of an airplane wing, for example. The same thing
could be done with number crunching in theory,
but it was a lot more immediate and obvious where
things went wrong when the model was actually
shown as an image”
- Robert Kosara, http://stat-computing.org/newsletter/issues/scgn-22-1.pdf
simplified version
139 thousand tonnes of carbon dioxide would fill a sphere 521 metres across. To most Londoners, '139 thousand tonnes of carbon dioxide' is not a very meaningful quantity. Illustrating it in the context of London landmarks allows viewers to make it meaningful for themselves.
London’s Daily Greenhouse Gas Contribution 1. Enforce comparison
simplified version
1980’s weather is compared against ‘normal’ weather averages allowing you to immediately spot points of difference.
New York Weather for 1980 1. Enforce comparison
2. Suggest Causality
Without an indication of cause, you can be left wondering what the point is. i.e. if you show a trend, it begs the question, why is this happening?
http://youtu.be/pLqjQ55tz-U
2. Suggest Causality
simplified version
The world we seek to understand is multivariate.
The more variables, the more opportunities we have to see relationships and patterns
3. Show Multivariate Data
simplified version
3 Dimensions:- - Temperature - Precipitation - Humidity
New York Weather for 1980
3. Show Multivariate Data
oil consumption (Y axis) by year (X axis) and region (stacked area)
Increase in oil consumption
3. Show Multivariate Data
“Small Multiples” Also called Trellis / Lattice / Grid / Panel Chart
oil consumption (Y axis) by year (X axis) and region (stacked area)
Increase in oil consumption
3. Show Multivariate Data
Platforms, by type of usage, by volume
How BI Customers Use their Platforms
3. Show Multivariate Data
3. Show Multivariate Data
Platforms, by type of usage, by volume
How BI Customers Use their Platforms
Size of the circle is the amount of approval of
the premier/PM
Colour of Circle indicates vote difference
• Dark green = 15+ vote lead,
• Light green is 5-14 lead,
• White = +/- 5% lead/trail,
• Red= 5-14 trail & dark red (no example here) is
trail by 15 or more
Canadians think it time for a change of government, if they don’t see the
Government as being on the right track. And their vote intentions tend to
reflect that.
NF
SK
AB
MN
BC
Feds
ON
PQ
PEI NS
NB
Time for Change
Rig
ht T
rack
3. Show Multivariate Data
3. Show Multivariate Data
If there are elements that don’t serve the purpose of explaining the data, they are probably chart junk.
4. Content-Driven
There is nothing on here that is irrelevant New York Weather for 1980 4. Content-Driven
Aim for the viewer to be able to take in the whole picture in one glance, so avoid separate, complex legends which need to be continually referenced to make sense of the data
4. Fully integrate words, numbers and images
simplified version
Key annotations are present right within the chart New York Weather for 1980 4. Fully integrate words, numbers and images
Key annotations are present right within the chart
Distinct Segments driven by exposure interactions and psychographic engagement 4. Fully integrate words, numbers and images
Napoleon’s March on Moscow illustrates the principles
Enforce visual
comparisons —
the width of the
tan and black
lines gives you an
immediate
comparison of the
size of
Napoleon’s army
at different times
during the march
Show causality — the map shows how the
temperature and river crossings defeated Napoleon.
Show
multivariate
data —
Napoleon’s
March shows
six: army size,
location (in 2
dimensions),
direction, time,
and
temperature
Completely
integrate
words,
numbers and images—in this
map, number
sit comfortably
with words and
the only legend
is a scale to
give a sense of
distance
The design
should be
content-driven —
Napoleon’s March
was designed as
an anti-war
poster…the
designer was
passionate about
the information
being presented.
The point of the
poster wasn’t the
design, it was the
information. simplified version
Quiz: Does this meet all of the criteria?
simplified version
Data Visualization
“Statistics journals rarely cover graphical methods… Outside of statistics, though, infographics and data visualization are more
important. Graphics give a sense of the size of big numbers, dramatize relations between variables, and convey the complexity of data and
functional relationships… sometimes to more efficiently portray masses of information that their audiences want to see in detail (as with sports scores, stock prices, and poll reports), sometimes to help tell a story (as
with annotated maps), and sometimes just for fun:.”
- Visualization, Graphics, and Statistics, Andrew Gelman and Antony Unwin, Statistical Computing & Graphics, July, 2010
Info-graphics
Data Visualization
Dashboards
Dynamic Data
Visualization
Info-graphics Summarize complex information using both decorative as
well as data-driven visual elements
Info-graphics
Info-graphics
Dynamic Data Vizualisation
Uses motion or other interactive elements to allow the user
themselves to explore a dataset for insight
Dynamic Data Vizualisation
- Some tools becoming available
Many Eyes, (www.many-eyes.com)
Dashboards
Summarize key statistics into one page or panel of charts
Dashboards
Dashboards
Using Excel ‘Slicers’ for a Dynamic Dash
MY AWESOME DASHBOARD
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
Gross Profit
Sum of Total GP
Sum of Total sales
0 50000 100000 150000 200000
Salesperson 1
Salesperson 2
Salesperson 3
Salesperson 4
Salesperson 5
Total Sales
Sum of Total GP
Sum of Total sales
Month
Jan-09
Feb-09
Mar-09
Apr-09
May-09
Jun-09
Jul-09
Product
Product A
Product B
Product C
Product D
Salesperson
Salesperson 1
Salesperson 2
Salesperson 3
Salesperson 4
Salesperson 5
Illustrations
“Ask yourself this: What information are you representing with the written word on a slide that you could replace with a photograph (or other appropriate image or graphic)?.. Images are powerful, efficient
and direct. Images can also be used very effectively as mnemonic devices to make messages more memorable. If people cannot listen and read at the same time, why do most PowerPoint slides contain far more
words that images? … It takes the realization that modern presentations with slides and other multimedia have more in common with cinema
(Images and narration) …than they do with written documents.”
- Presentation Zen, Garr Reynolds, 2008
Illustrations
Use of decorative, non-data driven images to add meaning
to your reporting.
Think like a designer: Simple, bold, colour-matched to your palette, Rule of 3rds
Use images along with bold words to make your headline points
For memorability or to emphasise a point pick an image that has an emotional appeal cute, comical, evocative
Source images from good quality, legal sources
Don’t be afraid to try!
But you don’t need to be one: a tonne of image manipulation tools right in PowerPoint.
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88
That’s all folks! Questions? Contact me: Laura Davies, SVP [email protected]