The document provides an overview of a presentation on designing with data. It outlines the agenda which includes introductions to general theories, quantitative and qualitative data, details of visualization design, and a critique section. The document then delves into each section, providing examples and explanations of concepts like storytelling with data, different graph types, using statistics, qualitative methods, details of design, and suggestions for further references.

1. Welcome to the presentation
on Designing with Data. I
hope you’re excited to learn.
Dominic Prestifilippo | andCulture | Design Methods Training | December 4, 2013

2. AGENDA
• Intro
• General Theories
• Quantitative
• Qualitative
• Details
• Critique

3. introduction
People are visual learners
Visualizations help everyone

4. introduction
“… 80% of the information
we take in is provided by
our eyesight.”
People are visual learners.
http://www.vision1to1.com/EN/HomePage.asp?BGColor=1&Category=6&Article=122

5. Introduction
Visualizations help everyone.
1. Making them provides further insight into the information
2. Visualizations invite comments and inspired discussion
3. Enable presentations that aren’t reliant on scripts or memorization
Dan Roam, Back of the Napkin, pg 11

6. General Theories
Storytelling
Levels of Information
Layer Information
Proportions
Sanity Check

7. General Theories | Storytelling
Tell a story.
Provide context.
Don’t let data lie.
have intent.

8. General Theories | Storytelling
Tell a story.
Have a point to make
when creating an
infographic and let that
guide your decisions.
http://visual.ly/most-popular-baby-names-girls

9. General Theories | Storytelling
Tell a story.
Have a point to make
when creating an
infographic and let that
guide your decisions.
My interpretation is,
anyone with these names
should hope they have
interesting middle names.
Is that the intent?
http://visual.ly/most-popular-baby-names-girls

10. General Theories | Storytelling
provide context.
380,000
Number Of Locations Worldwide
Information without
context is un-relatable.
People don’t know what
it means or what to do
with it.
Western
Union
http://issuu.com/dpresto/docs/remas_book

11. General Theories | Storytelling
provide context.
Sure it seemed like a
lot before, but you may
have also thought there
was a lot of these other
locations. This helps
highlight the differences
in perception of “a lot.”
380,000
Number Of Locations Worldwide
Information without
context is un-relatable.
People don’t know what
it means or what to do
with it.
31,000
16,700
8,500
Wal-Mart
Starbucks
McDonalds
Western
Union
http://issuu.com/dpresto/docs/remas_book

12. General Theories | Storytelling
Don’t let Data Lie.
Percentages hide
absolute values,
skewing real scale.
http://visual.ly/most-popular-content-management-systems-2013

13. General Theories | Storytelling
Don’t let Data Lie.
Percentages hide
absolute values,
skewing real scale.
Earlier in the graphic,
we’re told Wordpress has
50.07% of the CMS market
while Joomla only has
6.44%
http://visual.ly/most-popular-content-management-systems-2013

14. General Theories | Storytelling
have intent.
Treat each decision as if
it is crucial to the entire
piece, because it is.
http://visual.ly/knife-skills

15. General Theories | Storytelling
have intent.
Treat each decision as if
it is crucial to the entire
piece, because it is.
I assume the decision to
illustrate this as a sketch
is to make something
potentially scary and
dangerous seem more
approachable.
http://visual.ly/knife-skills

16. General Theories | levels of info
Broad Points.
Visible from 4’ or more
Very Specific Details.
visible from less than 1’

17. General Theories | levels of info
4 feet
12 inches
http://visual.ly/how-startup-funding-works

18. General Theories | Layer Information
Average wait times
Juxtaposing relevant data can produce even more interesting results,
highlighting potential relationships and making both data sets more
valuable.
http://visual.ly/waiting-time-week

19. General Theories | Layer Information
Average wait times per day is much more interesting
http://visual.ly/waiting-time-week

20. General Theories | Proportions
The Golden Ratio.
The Fibonacci Sequence.

21. General Theories | Proportions
The Golden Ratio.
a/b = (a+b)/a ≈ 1.618033988
a
b
Sample Pattern.

22. General Theories | Proportions
The fibonacci sequence.
1
0+1=1
1+1=2
1+2=3
2+3=5
3+5=8
5+8=13
8+13=21
13+21=34
•
•
•
Sample Pattern.
•
•
•

23. General Theories | Sanity Check
• Is this important?
• Does this provide value?
• Does this make sense?
• Can this be done better?
• Does this help convey my message?
•
•
•

24. Quantitative
Graph Types
Statistics

25. Graph Types | Basic Bar Charts
whiskers
bar chart
bar chart
Bar Chart.
“The biggest benefit
of bar charts is that
different tems of
data can easily be
compared visually.”
whiskers
whiskers
histogram
histogram
Stacked Bar Chart.
histogram
histogram.
“Stacked bar charts
describe totals while
allowing a degree of
internal breakdown
of the data.”
“…in a histogram
it is important to
retain and display
the empty space. It
contributes to the
picture of the data
as a whole.”
stacked bar chart
stacked bar chart
candlestick
candlestick
Brian Suda, A Practical Guide to Designing with Data, pg 114, 119, 120

26. Graph Types | Advanced Bar Charts
bar chart
whiskers
Whiskers.
bar chart
whiskers
“…whisker is a
small vertical line
representing plus or
minus two per cent
from the value, with
some horizontal
histogram
histogram
lines to make the
ends easier to see
and measure.”
stacked bar chart
candlestick
stacked bar chart
candlestick
Candlestick chart.
“The whiskers, or
wicks, that extend
up and down do not
measure margin
of error, but the
maximum and
minimum…” where the
bar represents the
starting and finishing
points.
Brian Suda, A Practical Guide to Designing with Data, pg 121, 122

27. Graph Types | Pie Chart
“…a pie chart can only
represent relative
amounts.”
“The most effective pie
charts comprise only
two items, such as the
percentage of male or
female customers.”
“The total value of the
information must add up to
one hundred per cent…”
Unknown
Female
Male
Brian Suda, A Practical Guide to Designing with Data, pg 132

28. Graph Types | Others
line graph.
scatter plot.
“Line graphs work
best when the data
is continuous.”
“Scatter plots are
a useful tool to
reveal relationships
between any amount
of independent
values. …The data
points are placed in
a grid in an attempt
to build a larger
picture.”
“One of most
common variables
used in line graphs
is time…”
Brian Suda, A Practical Guide to Designing with Data, pg 111, 161

29. Statistics | Average
Σ(
Σ(
)= M
#of elementsof elements in the series
# in the series
)= M
=M
=M
=M
=M
MEan.
MEdian.
Mode.
“We add together all
of our test results and
then divide it by the sum
of the total number of
marks there are.”
“The Median is the
‘middle value’ in
your list.”
“The mode in a list
of numbers refers to
the list of numbers
that occur most
frequently.”
http://math.about.com/od/statistics/a/MeanMedian.htm

30. qualitative
Statements
Relationships

31. Statements | Bold Statements
Make Bold
Statements

32. Statements | Highlighting
“Use this to highlight a piece of a quote you would like cited.”
http://www.plantbasedpeople.com/misc.php?do=bbcode

33. Statements | Iconography
Include relevant iconography to help
with wayfinding and make the written
content more memorable
http://pictos.cc/

34. Relationships | Mind Map
Sub-idea 1
a2
b-ide
Su
a
de
I
Idea
3
It is an unstructured
visual outline that allows
people to move through
the related content in any
order they choose.
Connected information
logically as its produced
so that train-of-thoughts
and conversations can
be easily documented by
topic.
a1
ide
ub
S
Sub
-id
ea
2
1
Mind Map
Id
ea
2
a1
de
-i
ub
S
Sub-idea
2
Su
bid
ea
3

35. Relationships | Affinity Map
Using proximity and
position to indicate
relationships between
statements.
These clusters develop
organically depending on
the content under review.

36. Relationships | Flow Charts
Flow charts are a very
detailed, standardized way
of mapping processes.
Start
action
Decision
Decision
action
Stop

37. Details
Data to Pixel Ratio
Chart Junk
Resolution
Color
Legends

38. Details | Data to Pixel Ratio
“the amount of ink
representing the data
divided by the total ink on
the graph”
Don’t be confused; the
data–ink ratio is not
advocating the use of as
little ink as possible, but
only as much ink as needed
to convey the data
10
8
6
4
2
2
4
6
8
10
Brian Suda, A Practical Guide to Designing with Data, pg 25, 27

39. Details | Chart Junk
“…if you remove something
from the chart and it
doesn’t change the
meaning, it’s chart junk “
Brian Suda, A Practical Guide to Designing with Data, pg 25, 27

40. Details | Resolution
DPI Dots per Inch
For Print Media.
It is preferable that
documents are at least
300dpi.
For Digital Media.
It is preferable that
documents are at least
72dpi.

41. Details | Color
Color can do a lot to help
clarify information on a
chart. However, mis-use
and it will only add to the
confusion.
Be mindful of how you
use color. It can easily be
overdone.
Try starting with black and
white, then adding color
later.

42. Details | Legends
As nice as it can be to have
a very “clean” visualization
or chart, if it doesn’t convey
the necessary information
it is useless.
Make sure, if you do use
distinctions such as
color, shape, size, etc. to
differentiate data, make
sure it is labeled and clear.
10
8
6
4
2
2
4
6
8
10

43. Further References
A Practical Guide to Designing with Data by Brian Suda
The Back of the Napkin by Dan Roam
The Visual Display of Quantitative Information by Edward Tufte
Envisioning Information by Edward Tufte
Visual Explanations by Edward Tufte
Visual and Statistical Thinking: Displays of Evidence for Making Decisions by Eward Tufte

44. AGENDA
• Intro
• General Theories
• Quantitative
• Qualitative
• Details
• Critique

45. Thank you for learning more
about Designing with Data. Do
you have any questions?
Dominic Prestifilippo | andCulture | Design Methods Training | December 4, 2013

46. Critique
http://visual.ly/