http://andculture.com/lab/designing-with-data
A presentation explaining the importance of visualizations. I begin by reviewing some general theories about translating data into visuals, and then dive deeper into some specifics for using qualitative and quantitative information to tell your story. Finally I close by discussing some more technical details that everyone making visualizations should be aware of.
It was geared towards an internal audience that has varying levels of technical understanding regarding the artistic, psychological, and narrative principles that inform well made visualizations and infographics.
Data visualization & Story Telling with DataDr Nisha Arora
Storytelling with data using the appropriate visualization is a skill that is well sought-after for data-driven decision making and it spans many industries and roles (technical/non-technical).
In this presentation, we will briefly discuss the importance of understanding the context, selecting the right visuals, key points for effectively using those for storytelling, design dos, and don’ts, etc.
Data Visualization dataviz superpower! Guidelines on using best practice data visualization principles for Power BI, Excel, SSRS, Tableau and other great tools!
Best Practices for Killer Data VisualizationQualtrics
There’s something special about simple, powerful visualizations that tell a story. In fact, 65% of people are visual learners.
Join Qualtrics and Sasha Pasulka from Tableau as we illuminate the world of data visualization and give you clear takeaways to help you tell a better story with data. Getting executive buy-in or that seat at the table may come down to who can visualize data in a way that excites and enlightens the audience.
Data Visualization Design Best Practices WorkshopJSI
This introduction was presented as part of a workshop at the Measurement and Accountability for Results in Health Summit at the World Bank (June 2015). The workshop focused on simple ways anyone working with data can improve their presentations, and included visualization redesign activity to put these principles in practice.
A quick reference on designing data visualizations that delight and leverage best practices from the design world to ensure your data is presented in meaningful, usable, fun ways.
Data visualization & Story Telling with DataDr Nisha Arora
Storytelling with data using the appropriate visualization is a skill that is well sought-after for data-driven decision making and it spans many industries and roles (technical/non-technical).
In this presentation, we will briefly discuss the importance of understanding the context, selecting the right visuals, key points for effectively using those for storytelling, design dos, and don’ts, etc.
Data Visualization dataviz superpower! Guidelines on using best practice data visualization principles for Power BI, Excel, SSRS, Tableau and other great tools!
Best Practices for Killer Data VisualizationQualtrics
There’s something special about simple, powerful visualizations that tell a story. In fact, 65% of people are visual learners.
Join Qualtrics and Sasha Pasulka from Tableau as we illuminate the world of data visualization and give you clear takeaways to help you tell a better story with data. Getting executive buy-in or that seat at the table may come down to who can visualize data in a way that excites and enlightens the audience.
Data Visualization Design Best Practices WorkshopJSI
This introduction was presented as part of a workshop at the Measurement and Accountability for Results in Health Summit at the World Bank (June 2015). The workshop focused on simple ways anyone working with data can improve their presentations, and included visualization redesign activity to put these principles in practice.
A quick reference on designing data visualizations that delight and leverage best practices from the design world to ensure your data is presented in meaningful, usable, fun ways.
Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.
This slide deck gives a general overview of Data Visualization, with inspiring examples, the strength and weaknesses of the human visual system, a few technical frameworks that may be used for creating your own visualizations and some design concepts from the data visualization field.
A short workshop from MERL Tech 2016 on how we can think more purposefully about telling stories with our data and designing visualizations to bring those stories to life in global health and development.
Use Cases of Enterprise Social Software in Consulting: A Practice PerspectiveDr. David Wagner
Presentation prepared for the 2020 GeNeMe Conference, held from Oct 7-9, 2020, in Dresden, Germany. The presentation was part of the Knowledge Communities Track. Please contact the lead author for a copy of the full paper or see conference proceedings (https://tu-dresden.de/mz/ergebnisse-transfer/veranstaltungen/geneme/tagungsbaende-der-geneme).
Borrowing from the communications and media experts, storyboarding is one of my favorite approaches to work through a data visualization design with a team. First identify your audience & what your data story is, then map it out visually to come to a common understanding of what your team is designing.
This slideshow provides an overview for best practices for visual analysis within Tableau. This is intended for anyone who wants to tell more compelling stories with their data.
How to Become a Data Science Company instead of a company with Data Scientist...Ruth Kearney
The journey of becoming a data science company is more about the culture and thinking, rather than hiring and up-skilling individuals. In Novartis, while we are hiring data scientists and spending a lot of time in training and learning related to data science, the destination for us is one of cultural change, which is required to make us a data science company.
Head of the AI Hub Dublin, Ashwini Mathur will share practical insights into the Novartis journey and how each employee plays a part. He will talk about the value of using the language of data science throughout the organisation and how this takes them one step closer to becoming a data science company.
A8: Mind Mapping for Effective Content ManagementGareth Saunders
Workshop at IWMW2008 on Mind Mapping for Effective Content Management by Dr Stephen Evans and The Revd Gareth J M Saunders from the University of St Andrews.
Why is it suboptimal to visualize data as plain figures? What is the purpose of data visualization? Why should you care? What is the interplay between statistics, data analysis, and a good marketing story? In this talk, I'll give some answers and try to convince you to adopt best practices in dataviz.
Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.
This slide deck gives a general overview of Data Visualization, with inspiring examples, the strength and weaknesses of the human visual system, a few technical frameworks that may be used for creating your own visualizations and some design concepts from the data visualization field.
A short workshop from MERL Tech 2016 on how we can think more purposefully about telling stories with our data and designing visualizations to bring those stories to life in global health and development.
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Presentation prepared for the 2020 GeNeMe Conference, held from Oct 7-9, 2020, in Dresden, Germany. The presentation was part of the Knowledge Communities Track. Please contact the lead author for a copy of the full paper or see conference proceedings (https://tu-dresden.de/mz/ergebnisse-transfer/veranstaltungen/geneme/tagungsbaende-der-geneme).
Borrowing from the communications and media experts, storyboarding is one of my favorite approaches to work through a data visualization design with a team. First identify your audience & what your data story is, then map it out visually to come to a common understanding of what your team is designing.
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A8: Mind Mapping for Effective Content ManagementGareth Saunders
Workshop at IWMW2008 on Mind Mapping for Effective Content Management by Dr Stephen Evans and The Revd Gareth J M Saunders from the University of St Andrews.
Why is it suboptimal to visualize data as plain figures? What is the purpose of data visualization? Why should you care? What is the interplay between statistics, data analysis, and a good marketing story? In this talk, I'll give some answers and try to convince you to adopt best practices in dataviz.
Slides from SXSW 2015 session on the intersection of data and design:
http://schedule.sxsw.com/2015/events/event_IAP41090
By Trina Chiasson from https://infoactive.co
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Designing with data: Creating Visualizations to Tell Your Story
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
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
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.
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?
•
•
•
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
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
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
45. Thank you for learning more
about Designing with Data. Do
you have any questions?
Dominic Prestifilippo | andCulture | Design Methods Training | December 4, 2013