designing with data: creating visualizations to tell your story

Welcome to the presentation on Designing with Data. I hope you’re excited to learn.

Dominic Prestifilippo | andCulture | Design Methods Training | December 4, 2013

AGENDA

• Intro

• General Theories

• Quantitative

• Qualitative

• Details

• Critique

introductionPeople are visual learners

Visualizations help everyone

INTroDuCTIoN

People are visual learners.

http://www.vision1to1.com/EN/HomePage.asp?BGColor=1&Category=6&Article=122

“… 80% of the information we take in is provided by

our eyesight.”

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

General TheoriesStorytelling

Levels of Information

Layer Information

Proportions

Sanity Check

GENErAl ThEorIEs | SToRyTELLING

Tell a story.

Provide context.

Don’t let data lie.

have intent.

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

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

GENErAl ThEorIEs | SToRyTELLING

provide context.

Information without context is un-relatable. People don’t know what it means or what to do with it.

http://issuu.com/dpresto/docs/remas_book

WesternUnion

380,000

Num

ber O

f Loc

atio

ns W

orld

wid

e

GENErAl ThEorIEs | SToRyTELLING

provide context.

Information without context is un-relatable. People don’t know what it means or what to do with it.

http://issuu.com/dpresto/docs/remas_book

WesternUnion

380,000

Num

ber O

f Loc

atio

ns W

orld

wid

e

Wal-Mart Starbucks McDonalds

31,00016,7008,500

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.”

GENErAl ThEorIEs | SToRyTELLING

http://visual.ly/most-popular-content-management-systems-2013

Don’t let Data lie.

Percentages hide absolute values, skewing real scale.

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

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

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

I assume the decision to illustrate this as a sketch is to make something potentially scary and dangerous seem more approachable.

GENErAl ThEorIEs | LEVELS of INfo

VEry sPECIfIC DETAIls. visible from less than 1’

Broad Points. Visible from 4’ or more

GENErAl ThEorIEs | LEVELS of INfo

4 feet 12 inches

http://visual.ly/how-startup-funding-works

GENErAl ThEorIEs | LAyER INfoRMATIoN

Juxtaposing relevant data can produce even more interesting results, highlighting potential relationships and making both data sets more valuable.

Average wait times

http://visual.ly/waiting-time-week

GENErAl ThEorIEs | LAyER INfoRMATIoN

Average wait times per day is much more interesting

http://visual.ly/waiting-time-week

GENErAl ThEorIEs | PRoPoRTIoNS

The Golden ratio.

The fibonacci sequence.

The Golden ratio.

a/b = (a+b)/a ≈ 1.618033988

sample Pattern.

GENErAl ThEorIEs | PRoPoRTIoNS

a

b

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

GENErAl ThEorIEs | PRoPoRTIoNS

•••

•••

sample Pattern.

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?•••

QuantitativeGraph Types

Statistics

GrAPh TyPEs | BASIC BAR CHARTS

bar chart

histogram

stacked bar chart

whiskers candlestick

bar chart

histogram

stacked bar chart

whiskers candlestick

bar chart

histogram

stacked bar chart

whiskers candlestick

Bar Chart.

“The biggest benefit of bar charts is that different tems of data can easily be compared visually.”

stacked Bar Chart.

“Stacked bar charts describe totals while allowing a degree of internal breakdown of the data.”

histogram.

“…in a histogram it is important to retain and display the empty space. It contributes to the picture of the data as a whole.”

Brian Suda, A Practical Guide to Designing with Data, pg 114, 119, 120

bar chart

histogram

stacked bar chart

whiskers candlestick

bar chart

histogram

stacked bar chart

whiskers candlestick

GrAPh TyPEs | ADVANCED BAR CHARTS

Whiskers.

“…whisker is a small vertical line representing plus or minus two per cent from the value, with some horizontal lines to make the ends easier to see and measure.”

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

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…”

Brian Suda, A Practical Guide to Designing with Data, pg 132

Unknown

Male

female

GrAPh TyPEs | oTHERS

line graph.

“Line graphs work best when the data is continuous.”

“one of most common variables used in line graphs is time…”

scatter plot.

“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.”

Brian Suda, A Practical Guide to Designing with Data, pg 111, 161

sTATIsTICs | AVERAGE

Σ( )= M= M = M#of elements in the series

Σ( )= M= M = M#of elements in the series

Σ( )= M= M = M#of elements in the series

MEan.

“We add together all of our test results and then divide it by the sum of the total number of marks there are.”

MEdian.

“The Median is the ‘middle value’ in your list.”

Mode.

“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

qualitativeStatements

Relationships

sTATEMENTs | BoLD STATEMENTS

Make Bold statements

sTATEMENTs | HIGHLIGHTING

http://www.plantbasedpeople.com/misc.php?do=bbcode

“Use this to highlight a piece of a quote you would like cited.”

sTATEMENTs | ICoNoGRAPHy

http://pictos.cc/

Include relevant iconography to help with wayfinding and make the written

content more memorable

rElATIoNshIPs | MIND MAP

Mind Map

Idea 1Idea 3

Idea 2

Sub-idea 1

Sub-idea 2Sub-idea 1

Sub-idea 2

Sub-idea 1

Sub-idea 2

Sub-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.

rElATIoNshIPs | AffINITy MAP

Using proximity and position to indicate relationships between statements.

These clusters develop organically depending on the content under review.

rElATIoNshIPs | fLoW CHARTS

Decision Decision

action

Start

Stop

action

flow charts are a very detailed, standardized way of mapping processes.

DetailsData to Pixel Ratio

Chart Junk

Resolution

Color

Legends

DETAIls | DATA To PIxEL RATIo

Brian Suda, A Practical Guide to Designing with Data, pg 25, 27

“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

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4

6

8

10

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

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.

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.

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.

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Further ReferencesA 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

AGENDA

• Intro

• General Theories

• Quantitative

• Qualitative

• Details

• Critique

Thank you for learning more about Designing with Data. Do

you have any questions?

Dominic Prestifilippo | andCulture | Design Methods Training | December 4, 2013

Critiquehttp://visual.ly/