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From YouTube: Webinar | Using Data Visualization to Improve Messaging
Description
To draw attention to work that incorporates issues and convinces others to be proactive, a message must be clearly and accurately articulated. The webinar will provide a brief synopsis on how people see and understand information from data displays. It will provide fundamentals on how to present good data visualizations and discuss the importance of using the appropriate colors and charts to engage the audience.
A
Sorry
getting
used
to
the
advancement
here,
my
name
is
Karen
Emma,
Gordy
and
I'm
a
principal
program
evaluator
at
the
North
Carolina
program,
evaluation,
division
and
I
will
be
moderating
our
webinar
today,
I'd
like
to
thank
the
national
legend
of
program,
evaluation,
Society
and
the
National
Conference
of
State
Legislatures
for
sponsoring
this
webinar
NLP
es
is
the
NCSL
staff
association
for
legislative
staff
involved
in
programming
valuation
or
performance
auditing.
One
of
its
key
purposes
is
to
promoting
professional
development
opportunities
like
this
webinar
for
legislative
staff
I
serve
as
the
chair
of
the
NLP
program.
A
A
A
Our
presenter
today
is
Katherine
Tyson,
a
Senior
Program
evaluator
at
the
Minnesota
office
of
the
legislative
auditor,
Katherine
started
working
for
the
legislative
auditor's
office
in
2015.
She
holds
a
master's
of
Public
Health
degree
from
Emory
University
Katherine's
passion
for
data
visualization
began
after
she
intended
a
data
visualization
workshop
by
Stephanie
evergreen.
Since
then,
she
has
developed
and
presented
a
data
visualization
training
to
olá
staff
and
her
training
included
a
template
that
Ola
staff
can
use
to
create
certain
visualizations
welcome,
Katherine
Thank.
B
You
Kiernan
for
that
introduction,
I
think
we
can
all
agree
that
we
want
our
work
to
draw
attention
to
issues,
make
an
impact
and
convince
others
to
take
action.
Data
visualization
is
one
tool
you
can
use
to
achieve
these
goals
today.
I'll
cover
four
topics.
First,
I'll
explain
why
you
should
care
about
how
your
organization
presents
information
visually.
Second
I'll
provide
an
introduction
to
chart
or
types
of
data
visualizations
and
spend
some
time
talking
about
certain
types
of
charts.
B
So
first,
why
should
we
visualize
data
data?
Visualization
is
not
new.
In
fact
it's
been
around
for
centuries
and
you
might
recognize
usable
diagrams
the
graphic
on
the
top
hand.
Side
of
the
slide
is
florence
Nightingale's
1858
area
graph
that
shows
that
epidemic
disease
in
blue
was
responsible
for
more
british
guns,
but
over
the
course
of
the
Crimean
War
than
battlefield
saloons
in
red
and
the
bottom
graphic
is
Charles
Joseph,
my
nards
famous
1869
app
that
portrays
the
losses
suffered
by
Napoleon's
army
during
this
Asian
of
Russia
in
1812,
as
computer
technology
has
advanced.
B
B
B
B
Here's
an
example:
this
is
an
excerpt
from
a
report
my
office
published
in
March.
This
describes
how
an
office
was
at
the
Minnesota
Department
of
Health
has
not
met
deadlines
for
completing
maltreatment
investigations,
as
required
by
state
law.
Research,
suggests
that
our
readers
will
have
a
difficult
time,
remembering
the
specific
and
very
important
details
in
these
paragraphs,
because
the
information
is
presented
only
as
text.
B
However,
coupling
the
text
with
data
visualizations
takes
that
message
to
a
new
level.
Readers
now
have
a
greater
likelihood
to
remember
the
important
detail.
This
is
because
visuals
are
particularly
good
at
activating
humans
pathways
for
memory
formation.
We
can
use
this
to
our
advantage
by
applying
tried-and-true
graphic
design
concepts
to
our
visualizations.
B
This
stage
of
memory
formation
occurs
without
focused
energy
on
the
part
of
the
viewer
graphic
designers
operate
in
this
stage.
Emphasis
techniques
such
as
changes
in
color,
motion
alignment
orientation
and
size
grab
viewers
attention.
Here's
an
example
in
this
graph.
You
might
find
yourself
looking
for
something
that
stands
out,
such
as
Peaks
valleys,
intersections
dominant
colors
or
outliers.
You
have
might
have
noticed
that
green
line
that
crosses
through
the
others.
B
However,
when
trying
to
understand
the
graph,
you
might
have
felt
caught
up
at
certain
points,
this
graph,
which
displays
the
same
data
as
the
previous
one
use
of
color,
to
focus
your
attention
compared
with
the
previous
graph.
You
probably
didn't
have
to
even
read
the
data
labels
that
access
or
the
title
and
you're
about
90%
on
the
way
to
understanding
the
key
message.
Most
likely,
you
saw
X
decreasing
blue-lined
check
the
labels
in
the
title,
and
you
got
the
point
sight.
C
is
important.
B
B
However,
working
memory
is
limited.
Research
has
shown
that
we
can
only
hold
about
three
to
five
chunks
of
information
in
our
working
memory.
At
a
time
when
a
viewers
working
memory
is
overloaded,
it
dropped
some
chunks
of
information
by
visually,
organizing
and
emphasizing
information.
Effective
data
displays
make
this
information
more
accessible
for
your
readers
and
increase
their
ability
to
understand
your
message.
B
For
example,
the
math
on
the
left
on
the
slide
is
the
current
map
of
the
Minneapolis
Skyway
system.
It's
notoriously
confusing,
possibly
because
readers
are
not
able
to
use
the
diagram
to
convert
the
layout
of
the
Skyway
from
their
working
memory
to
long-term
memory.
The
map
on
the
right
is
a
hypothetical
Skyway
system
map
created
by
a
local
reporter.
It's
modeled
after
the
New
York
City
subway
system
map.
B
When
information
is
received
into
the
long-term
memory,
it
can
be
recalled
later
on
retold
to
others
and
combined
with
other
ideas.
We
want
the
information
we
present
to
make
it
to
this
stage
when
forming
long
term
memories,
we
rely
on
conventions
and
metaphors.
In
other
words,
our
brain
sees
our
past
experiences
to
develop
expectations
to
create
cognitive
shortcuts.
For
example,
we
generally
think
of
high
performance
of
being
spatially
high
in
a
charge
or
low
performances
being
specially
low,
and
what
visuals
depicting
data
over
time
can
show
time
in
any
spatial
direction
and
remain
technically
accurate.
B
B
Here's
an
example
without
thinking
about
it,
we
access
for
conventions
in
our
mind
to
health,
explain,
explain
the
meaning
of
this
graph.
First,
we
think
that
light
colors
mean
like
things
second
color
saturation
indicates
higher
or
lower
values.
Third
categories
are
arranged
and
plotted
from
one
extreme
to
another
and
forth
that
the
segments
of
a
pie
chart
sum
to
100%.
As
you
can
see
in
this
graph,
none
of
those
for
conventions
hold
true
in
the
pie.
Chart
light
colors
do
might
do
not
mean
like
things
rather
dissimilar
responses
are
grouped
together.
B
Second,
the
color
saturation
does
not
indicate
higher
or
lower
values,
while
the
categories
are
plotted
from
the
largest
percentage,
the
smallest.
The
order
of
the
categories
does
not
make
sense
with
this,
like
art
type
scale.
Finally,
if
you've
already
some
the
percentages
in
the
graph,
you
know
that
the
pieces
of
the
pie
do
not
sum
to
100%
what,
at
first
glance,
looked
like
a
well-constructed
grass
repeatedly
disrupts
our
expectations.
It
forces
us
to
think
harder
about
what
we're
looking
at
and
it
limits
viewers
ability
to
accurately
understand
and
remember
the
information
being
presented
here.
B
This
is
a
better
version
of
that
chart.
This
chart
supports
the
four
conventions
I
spoke
about
in
the
previous
slide.
In
this
chart,
light
colors
mean
like
things,
because
the
positive
and
negative
response
categories
are
grouped
together
with
color.
Also
the
darker
colors
indicate
more
extreme
categories,
and
categories
are
arranged
and
plotted
from
one
extreme
to
another.
B
Finally,
the
segments
of
the
bar
sum
to
100%
I
have
spent
some
time
today
talking
about
how
we
see
and
understand
information.
I
did
so
because
understanding
this
is
critical
to
designing
effective
data
visualizations.
If
your
charts
don't
make
what's
important
stand
out,
if
complex
data
don't
coalesce
into
a
few
clear
ideas
or
as
unconventional
visual
techniques
confuse
your
readers,
the
credibility
of
your
message
is
at
stake.
I'll
come
back
to
those
concepts
later
on
in
this
presentation
and
we'll
revisit
these
design
concepts,
but
for
now
let's
change
our
focus
to
types
of
data
visualizations.
B
First,
let's
take
a
look
at
two
broad
types
of
visualizations.
If
the
information
you
want
to
present
focuses
on
ideas
instead
of
statistics,
you're,
probably
going
to
want
to
use
a
consent,
visualization
two
examples
of
conceptual
graphics
are
organizational
charts
and
flowcharts,
such
as
the
two
diagrams
on
the
top
half
of
the
slide.
I've
also
made
timelines
and
other
sorts
of
graphics
to
organize
and
convey
important
ideas
and
reports.
I've
written.
On
the
other
hand,
if
you
want
to
present
a
message,
that's
based
on
numbers,
you'll
use
a
data-driven
visualization.
B
The
visual
you
choose
will
depend
on
whether
the
data
are
qualitative
or
quantitative
in
nature.
For
example,
if
you
want
to
show
the
frequency
with
which
certain
words
are
mentioned,
in
an
interview
or
in
a
news
article,
you
could
use
a
word
cloud
which
is
shown
on
this
slide.
If
you
want
to
compare
revenues
and
expenditures
for
one
program
over
time,
you'd
probably
choose
to
use
something
like
a
bar
chart
to
display
that
data.
The
remainder
of
this
presentation
focuses
on
those
quantitative
data
driven
chart
types.
B
Frankly,
there
are
quite
a
lot
of
charts
of
this
type.
More
than
the
ever-popular
column
bar
line
and
pie
charts
each
type
of
chart
has
different
strengths
and
weaknesses
when
it
comes
to
presenting
data
and
column
bar
line
and
pie.
Charts
are
not
always
appropriate
or
the
best
way
to
present
data,
but
how
do
you
decide
on
the
chart
type?
Well,
that
depends
on
a
few
key
questions.
Who
will
see
this?
What
do
they
want
to
understand?
What
do
they
need
to
understand?
What
idea
do
I
want
to
convey?
What
could
I
show?
B
What
should
I
show
and
how
will
I
show
it?
You
probably
consider
these
questions
informally,
while
writing
reports
and
making
graphics.
However,
I
think
it's
important
to
always
keep
in
mind
why
you
intend
to
visualize
your
data
in
the
first
place
during
the
rest
of
this
presentation.
You'll
hear
me
say
often
that
certain
choices
depend
on
your
message.
The
answer
to
these
questions
can
help
you
define
the
message
you
intend
to
convey.
For
example,
are
you
trying
to
show
policymakers
that
a
tax
credit
has
has
little
effect
on
the
state's
economy?
B
If
so,
how
can
you
tailor
the
graphic
to
communicate
that
message
to
this
very
specific
audience?
Your
message
drives,
which
chart
type
you
should
use
and
which
formatting
choices
you
make
I
have
grouped
quantitated
quantitative
data
driven
chart
types
into
six
categories.
Based
on
the
questions
we
just
discussed
my
big
data,
visualization
research
and
common
types
of
research
questions.
B
Some
charts
are
particularly
good
at
displaying
results
from
comment,
survey,
questions
and
I,
grouped
these
charts
into
a
survey.
Category
charts
in
the
proportion
categories
showed
data
that
are
parts
of
a
whole
and
finally,
are
the
show.
Relationships
are
grouped
into
a
relationship
category
I'd
like
to
note
that
this
is
only
one
grouping
of
charts
and
many
more
exist
out
there.
Also
the
categories
on
this
slide
overlap
somewhat.
For
example,
you
could
use
charts
from
the
comparison
category
to
visualize
survey
data
today
I'm
going
to
talk
about
graphs
in
three
of
these
categories.
B
There
are
many
charts
that
compare
data
either
among
categories
or
across
time
I'm
going
to
breeze
through
the
12
on
the
screen
in
the
top
row.
Stacked
bar
charts
line,
graphs
and
side-by-side
charts
are
quite
popular
ways
to
compare
data
and
you're,
probably
familiar
with
them
in
the
second
row.
Small
multiples
are
charts.
They
combine
multiple,
buy
or
line
charts
to
compare
multiple
categories.
This
is
probably
my
favorite
type
of
chart,
because
I
found
that
small
multiples
are
so
versatile,
back-to-back
charts
and
deviation
bar
charts
share
some
similar
features.
B
These
graphs
compare
data
across
the
middle
axis.
You
might
have
seen
this
back-to-back
graph
before
as
a
population
pyramid.
The
next
graph
overlapping
column
is
used
to
compare
two
categories
when
one
is
inherently
part
of
the
other
slope
graph
are
similar
to
line
graphs,
but
they
plot
data
at
only
two
points
in
time.
As
an
example,
this
type
of
chart
would
be
useful
if
you
intend
to
display
a
metric
variant
of
programs
performance
during
its
first
and
last
year
of
operation
and
the
years
between,
don't
matter
as
much
to
communicate
your
message.
B
Dot
plots
and
dumbbell
dot
plots
are
yet
another
way
to
compare
data.
These
trust
could
be
used
in
similar
situations
as
that
side-by-side
chart
on
the
top
right
corner
of
this
slide.
Dumbbell
dot
plots
are
particularly
good.
That's
showing
the
difference
between
two
data
points,
as
the
line
that
connects
the
two
data
points
draws
the
eye
to
the
separation
between
the
points.
B
Lollipop
charts
are
an
alternative
to
the
standard
bars
graph.
These
charts
focus
the
eye
on
the
most
important
part
of
the
chart.
The
data
point.
They
are
particularly
useful
for
a
long
list
of
data
because
they
give
some
visual
relief
or
whitespace.
That
would
not
be
there
if
you
had
used
a
bar
chart
and
finally,
Sam
key
diagrams
are
used
to
show
the
flow
of
data
between
nodes
and
the
width
of
the
band
depicts
quantity.
B
B
Benchmark
charts
are
used
to
compare
data
against
a
standard
that
stays
the
same
across
categories
or
time
and
combo
charts
are
used
to
compare
data
against
a
standard
that
changes
across
categories
our
time
bullet
graph.
The
fourth
graph
on
this
screen
are
an
interesting
chart
that
probably
have
limited
applications.
This
chart
plus
data,
the
dark,
gray
bar
and
the
yellow
target
line
against
two
or
more
ranges
of
performance.
In
this
case,
we
can
say
that
these
three
levels
of
performance
depict
poor,
satisfactory
and
good
range
performance.
B
Undoubtedly
many
charts
can
effectively
display
data
collected
from
surveys,
particularly
those
charts
in
the
comparison
category
I
talked
about
earlier.
However,
here
are
four
chart
types
that
can
help.
You
display
results
from
common
types
of
survey,
questions,
100%,
stacked
bar
and
diverging
bar
graph,
our
respective
ways
to
prevent
data
from
buy,
curtail
survey.
Questions
as
you
can
see
on
the
screen.
B
The
difference
between
these
two
types
of
charts
as
their
alignment,
the
align
for
the
diverging
bar
graph
allows
it
to
be
very
particularly
effective
at
showing
the
relative
sizes
of
positive
values
on
one
side
of
the
middle
line
and
negative
values.
On
the
other
side,
data
from
ranking
questions
can
sometimes
be
difficult
to
graph.
If
you're
applying
results
from
one
survey,
I
had
one
ranking
question
you
could
use
a
bar
graph
or
a
lollipop
chart
show
the
results.
B
But
if
you
ask
that
same
ranking
question
over
a
period
of
time
through
multiple
surveys,
you
could
use
this
ranking
data
chart
to
show
how
the
rank
of
the
categories
changed
over
time
and
finally,
nested
diagrams
can
help
show
another
tricky
and
common
type
of
survey,
data
branching
data,
for
example.
This
diagram
could
effectively
show
that
of
100
survey.
Respondents
70%
said
they
liked
chocolate
ice
cream
and
over
that
group
of
people
60%
liked
to
top
their
chocolate
ice
cream
with
chocolate
syrup
and
so
forth.
B
After
choosing
a
type
of
chart
that
could
best
present
the
story
you
want
to
tell
your
next
step
is
formatting
the
chart,
such
as
by
adding
labels
to
your
data,
coloring
certain
data
points
or
adjusting
the
range
of
your
axes
for
all
the
power
software
programs
to
generate
reasonably
good-looking
visualizations
they're,
not
capable
of
making
decisions
about
how
to
hold
visual
into
one
that
can
inform
readers
and
convince
them
to
take
action.
It's
other
us.the
intervene
with
decision
and
Tech's
bring
our
key
ideas
to
the
forefront.
B
Remember
that
good
design
serves
a
more
important
function
than
just
simply
looking
pretty.
It
helps
your
reader
access
and
understand
ideas
in
this
section,
I'm
going
to
discuss
set
of
design
concepts.
You
and
your
team
can
use
to
guide
how
you
format
your
charts
for
your
report
or
presentation
well,
design
data
visualizations
have
four
things
in
common,
they're,
structured,
clear,
simple
and
refined
in
the
next
slide.
I'll
further
describe
these
four
concepts
and
fix
a
cluttered
chart
to
show
you
how
to
use
these
concepts
to
improve
your
chart.
B
First
structure.
Does
your
visualization
looks,
neat
and
clean
or
being
muddled?
Impressions
of
the
relative
or
orderliness
of
a
chart
comes
from
its
structure.
This
means
that
all
charts
in
your
report
have
a
consistent
structure
that
they
align
visual
elements
and
they
limit
readers.
Eye
movements.
I'll
talk
about
these
three
concepts
in
the
coming
slides,
I
created
this
line
graph
in
excel
and
did
very
little
formatting.
That
was
not
generated
by
Excel
default
settings.
B
Well,
this
is
an
accurate
chart
and
it
might
help
me
and
my
team
understand
the
data
it's
formatted
in
a
way
that
makes
it
difficult
for
an
outside
reader
to
parse
out
and
understand
the
main
idea.
This
chart
needs
to
be
formed,
fit
a
intended
purpose,
commuting
communicating
a
specific
message
in
my
report:
let's
start
modifying
the
structure
of
this
chart,
so
it
fits
my
purpose.
B
First
make
sure
all
of
the
graphics
throughout
your
report
or
presentation
have
a
consistent
structure.
For
example,
in
my
office's
reports,
every
formal
exhibit
whether
it's
a
table.
A
chart
or
conceptual
diagram
includes
title.
The
visual
and
a
source
line
sticking
to
a
consistent
structure
is
useful
for
two
reasons.
First,
it
helped
prevent
ambiguity
about
the
structure
of
the
visualization
itself,
because
some
key
element
like
a
title,
is
missing.
Second
consistently
you've
been
Yuki
elements
makes
visuals
more
reusable
and
shareable.
B
B
The
second
way
to
improve
a
chart
structure
is
by
a
lean,
visual
element.
Professional
designers
divide
designs
into
evenly
spaced
grids
of
columns
and
rows
aim
to
use
few
as
few
points
of
alignment
as
possible,
because
more
points
make
the
chart
feel
busy
in
this
graph.
Center
justification
makes
multiple
alignment
points
for
elements
that
could
actually
share
one
unaligned
label
and
other
elements
in
this
visual
field
create
a
sense
of
haphazard,
nough.
B
The
third
element
of
having
good
structure
is
limiting
readers
eye
movements.
This
graph
forces
readers
to
move
their
eyes
back
and
forth
from
the
data
to
the
legend
back
to
the
data
understand
which
label
applies
to
each
line,
it's
best
to
put
elements
that
work
together
in
close
proximity,
try
to
connect
keys
and
legends
directly
to
the
visual
counterparts
in
this
graph,
I
embedded
the
legend
by
putting
labels
next
to
the
line
as
represent
I,
did
this
by
simply
adding
text
boxes.
B
This
is
a
relatively
simple
approach
to
limiting
readers
eye
movement
and
you
can
do
the
same
type
of
thing.
Embedding
legends
into
all
types
of
charts,
including
bar
charts,
now
onto
our
second
design
concept.
Clarity,
does
the
chart
make
sense
to
you,
or
are
you
stuck
wondering
what
you're
supposed
to
see
everything
that
makes
a
visual
self-explanatory
makes
it
more
effective?
B
This
means
that
the
chart
is
unambiguous
and
does
not
float
metaphors
or
conventions.
The
bottom
line
is
that
the
less
you
have
to
explain
the
chart,
the
more
you
can
talk
about
its
ideas,
ambiguous
visual
leaves
the
reader
without
a
key
takeaway
and
they're
left
on
their
own,
to
try
to
assign
meaning
to
the
visual
they're
forced
to
slow
down
and
think
about
the
visual
instead
of
the
message
in
this
chart,
for
example,
I
finally
felt
asking
what
does
this
mean?
What
is
this
chart
telling
me?
The
message
is
not
clear.
B
B
B
Here's
the
chart
with
a
modified
title,
basically
I
rephrase
the
subtitle
so
that
it
reflects
our
main
message
that
Americans
have
been
concerned
about
the
affordability
of
health
care
over
the
past
15
years.
In
addition
to
making
sure
your
visuals
are
unambiguous,
make
sure
that
your
visual
does
not
slope
metaphors
or
conventions
basically
use
color
and
other
chart
elements
in
a
way
that
supports
your
audience's
past
experiences
scene
and
understanding.
Visuals
and
I
talked
a
little
about
that
earlier
in
this
presentation.
In
our
example,
the
chart
is
OK.
B
B
If
this
chart
looks
simple,
elegant
and
pleasing,
or
does
that
look
clever,
it
is
being
complex.
Clarity
and
simplicity
go
hand-in-hand,
but
while
clarity
concerns
effective
communication
such
as
answering
the
question,
does
the
idea
come
through
simplicity,
addresses
effective
presentation
such
as?
Are
you
only
showing
what's
necessary
for
the
idea
to
come
through
when
we
think
of
simplicity?
B
We
often
think
of
the
absence
of
things
that,
if
we
just
keep
taking
away
more
and
more
information
will
achieve
simplicity's,
but
excessive
simplicity
leads
to
a
lack
of
clarity
instead
think
about
relative
simplicity,
how
little
you
can
show
and
still
convey
your
idea
clearly
start
by
assessing
each
element
in
the
graph.
You
can
use
the
flow
chart
on
the
screen
to
help
make
these
decisions.
It
first
asks
whether
the
element
is
necessary
and
you
need
if
it
is
then
consider
whether
whether
the
element
can
be
made
simpler.
B
Let's
evaluate
whether
each
element
in
this
chart
is
necessary
or
whether
we
can
modify
and
delete
elements
to
increase
simplicity,
I'll
start
at
the
top
of
the
chart
and
work
clockwise
around
the
visual
using
the
flow
chart.
We
just
talked
about
consider
whether
the
title
is
necessary.
It
usually
is,
but
is
this
one
unique?
No,
in
fact
the
subtitle
and
the
access
label,
y-axis
label,
repeat
parts
of
the
title
and
that
y-axis
label
only
describes
the
structure
of
the
visual.
Not
the
message
of
the
visual.
B
All
three
elements
can
either
be
deleted
or
simplified
I
rephrase
the
title
and
deleted
the
subtitle
and
why
access
label?
My
new
title
answers
the
question:
what
am
I
trying
to
say
or
show
this
type
of
title
is
called
an
active
title.
My
office
uses
active
titles
for
our
exhibits
because
it
takes
less
time
for
leaders
to
understand
information
if
you
just
simply
tell
them
the
point
directly.
Also,
it
removes
some
concerns
about
ambiguity
and
lessens
readers
risk
of
a
misunderstanding.
B
Now,
let's
look
at
the
legend.
Is
that
element
necessary?
Yes,
it
labels
the
data
in
the
visual.
Without
it,
you
wouldn't
know
what
the
data
are,
what
the
lines
represent,
so
we're
going
to
keep
the
legend
next,
the
axes
so
X
and
the
y
axes
are
also
necessary
elements
and
they
usually
are
for
data
plots,
so
we're
going
to
keep
them.
B
Finally,
is
the
information
in
the
visual
itself
necessary?
Yes,
otherwise,
you
wouldn't
have
a
visual.
However,
this
chart
contains
a
lot
of
extraneous
and
redundant
elements.
For
example,
there
are
tick
marks
along
the
x
axis,
a
label
for
each
year
and
a
marker
at
each
line
to
represent
each
point
in
time.
Are
these
elements
necessary?
Well,
the
answer
is
a
little
more
complicated
than
the
other
elements
we
just
described
in
this
case.
The
necessity
of
these
elements
depends
on
the
context
of
the
presentation.
B
So
let's
say
this
chart
is
going
to
be
used
in
a
formal,
PowerPoint
presentation.
That
means
audience
only
has
a
few
seconds
to
look
at
the
graph
and
understand
the
message.
The
current
graph,
one
you
see
on
the
screen
does
not
support
this
purpose,
while
the
detail
in
the
graph
might
blend
well
to
discussing
research
findings
as
a
small
group
or
in
a
detailed
appendix
of
a
report
where
readers
could
take
time
to
contemplate
the
other
data
points,
we
don't
want
money.
B
Only
the
first
time
last
year
were
necessary
to
understand
the
message
of
the
graph,
so
I
removed
the
x-axis
label
for
all
years
between
2004
and
2008
teen,
as
well
as
the
tick
marks
on
the
x-axis
line.
I
also
remove
the
y-axis
line,
recolor
the
grid
lines
to
gray,
remove
the
markers
from
each
line
and
I'll
show
you
that
change
again
in
this
graph.
That
y-axis
line
is
simply
unnecessary
for
readers
to
understand
this
graph.
So
I
deleted
it.
B
B
Additionally,
the
markers
along
the
lines
are
no
longer
necessary
once
I
remove
the
years
from
the
x-axis,
which
was
the
information
the
markers
were
displaying
the
other
thing.
I
changed
was
the
color
the
lines
to
simplify
the
graph
and
to
emphasize
the
one
key
message
of
this
graph:
I
colored
all
lines,
except
for
the
one
for
affordability
of
health
care,
gray.
I
did
this
because
simplicity
suffers
when
you
make
charts
too
colorful,
because
you
want
them
to
be
eye-catching
or
you
want.
You
have
a
lot
of
categories
to
plot.
B
In
an
effort
to
understand
the
chart,
viewers
will
know
color
differences
and
wonder
what
they
mean:
the
more
differences
they
see,
the
more
they
have
to
work,
to
figure
out
what
the
distinctions
represent,
find
the
lowest
number
of
distinctions
you
can
use
that
preserve
those
that
are
needed
to
convey.
The
message
remember
great,
is
your
friend.
We
typically
think
of
great
information
as
background
or
secondary
by
comparison
with
the
information.
Color
use
great
is
provide
context
without
disrupting
the
main
idea.
B
Another
thing
to
think
about,
when
applying
color
to
your
graphics
is
whether
your
color
choices.
Follow
inventions,
for
example,
use
oranges
and
reds
to
represent
negative
values
and
blues
and
greens
to
represent
positive
values,
use
contrasting
colors
for
contrasting
data
and
complementary
colors
for
complementary
data.
If
you
have
groups
of
data
use
a
similar
palette
of
colors
and
if
you
have
a
range
of
data,
use,
low
saturation,
colors
or
pale
colors
for
lower
values
and
high
saturation
or
bright
colors
for
higher
values.
B
Last
year,
I
developed
a
color
guide
for
my
office
to
use
when
applying
color
to
our
graphic.
The
gut
guide
contains
color
codes
for
several
different
types
of
color
schemes
that
fit
the
conventions.
I
just
mentioned
feel
free
to
email
me
after
this
webinar.
If
you'd
like
more
information
about
our
color
guide.
B
Now
we
have
address
structure,
clarity
and
simplicity
and
frankly,
our
chart
looks
for
good
and
I
could
use
it
as
is
well
I
want
today,
I
could
take
steps
to
further
refine
the
chart.
An
important
way
to
refine
your
chart
is
by
focusing
on
the
main
idea
the
preceding
steps
likely
will
have
helped.
You
clarify
the
main
idea
you
intend
to
convey.
Sometimes,
so
you
might
struggle
to
pull
out
a
key
message.
B
The
charts
on
this
slide
provide
an
example
of
adjusting
reference
points
using
some
completely
made-up
data.
The
message
in
this
chart
on
the
left
is
slightly
muddled
by
the
abundance
of
data
in
the
chart
on
the
right
I've
removed
reference
points,
which
makes
the
message
pop
specifically
I,
move
the
middle
removed,
the
middle
age
groups,
because
they
didn't
help
illustrate
the
idea
of
an
age
divide.
B
B
Here's
a
comparison
of
that
healthcare
affordability
chart
before
and
after
we
use
graphic
design
concepts
to
guide
how
we
formatted
this
chart.
You
can
apply
these
concepts
to
your
visuals
to
improve
their
communication
power.
It
will
take
some
time
to
become
confident
in
your
application
of
these
concepts.
B
Personally
I've
completed
two
reports
in
the
two
years
after
learning
how
to
use
these
design
concepts
and
comparing
my
sets
of
visuals
from
the
two
projects,
I
think
is
eye,
opening
and
I.
Think
you
too
will
prove
with
time
and
practice.
If
you
have
questions
about
the
graphics
you
make
I'd
encourage
you
to
show
somebody
in
your
office.
Who's
unfamiliar
with
the
topic.
Have
them
give
you
an
immediate
reaction
like
within
30
seconds
and
ask
them
what
they
understand
from
the
graphic
before
we
move
on
to
the
final
portion
of
my
presentation.
B
Let's
talk
about
some
important
things
to
keep
in
mind
when
designing
data.
Visualization,
remember
that
readers
may
print
or
copy
your
course
in
black
and
white.
While
you've
got
control.
Whether
this
happens,
you
can
take
steps
to
make
sure
your
graphics
are
legible
in
both
color
and
in
black
and
white.
First,
you
can
embed
your
legend
within
the
graph.
As
we
spoke
for
earlier,
you
can
test
every
graphics
ability
by
photocopying.
B
It
in
black
and
white
and
third,
the
intentional
about
how
and
where
you
color,
you
should
only
use
colors
to
enhance
or
support
the
key
message
of
the
grass
and
don't
place
dark
shades
or
light
shades
right
up
next
to
each
other.
Those
three
strategies
can
help
all
readers
interpret.
Data
visualization,
however,
make
sure
to
test
the
colors
you
used
for
legibility,
with
for
individuals
with
colorblindness,
there
are
many
computer
programs
and
websites
I
can
help
you
determine
whether
a
graphic
is
colorblind
friendly.
B
There
are
other
times
when
it
may
be
better
to
present
data
in
a
table
rather
than
in
a
chart,
for
example,
if
you
suspect
that
the
audience
will
not
understand
how
to
read
the
graph,
you
may
not
want
to
visualize
the
data
and
if
the
audience
makes
a
judgment,
call
about
the
visualizations
based
solely
on
the
data
label
and
not
on
the
visualization
itself.
The
table
could
suffice.
There
are
other
times
when
it's
important
to
present
data
that
are
not
in
the
same
scale.
B
B
Finally,
let's
talk
about
some
software
programs.
You
can
use
to
create
a
visualization
I'll.
Give
you
a
brief
overview
of
the
pros
and
cons
of
three
programs
as
well
as
some
other
additional
resources
that
can
help
guide
your
future
chart.
Making
endeavors
tableau
is
a
popular
software
program
that
was
built
for
data
visualization,
because
it's
popular
there
are
a
lot
of
online
resources
to
help
make
certain
types
chart.
However,
your
agency
mine,
on
already
on
this
program
available
for
you
to
use
Microsoft
Excel
on
the
other
hand,
is
probably
readily
available
to
you.
B
Well,
this
program
was
not
built,
especially
for
data
visualization.
The
program
has
several
default:
chart
types
that
you
can
use
to
easily
plot
your
data.
If
you're
skilled
at
chart
making
in
Excel.
There
are
many
ways
you
can
hack
the
program
to
produce
uncomment
charts.
For
example,
you
think
this
will
scatter
plot
and
some
Engineer
would
create
any
type
of
dot
plot.
You
want
last
year,
I
created
what
I
call
the
chart
starts
late
for
my
colleagues
to
use
to
make
these
more
complicated,
charts
again.
Email
me
after
this
webinar.
B
If
you
would
like
to
learn
more
about
this
template.
Finally,
you
can
use
Microsoft
Visio
to
create
conceptual
diagrams.
In
the
past.
You
may
have
created
these
types
of
graphics
using
PowerPoint.
However,
in
my
opinion
and
Visio
has
some
features
that
allow
for
more
easily
and
neatly
constructed
diagram.
So
if
you're
making
those
diagrams
I'd
recommend
looking
checking
out
Visio,
regardless
of
the
software
programs,
you
use
to
create
visuals,
it's
helpful
to
have
guides
and
examples
of
well
made
charts.
B
Additionally,
there
are
a
lot
of
websites
and
blogs
that,
with
sent
mix
of
bad
graph
instructions
how
to
make
new
types
of
chart.
Other
interesting
ideas
about
reporting
data,
I,
recommend
signing
up
email
alerts
from
website
and
blogs
you
like,
so
that
you
can
see
new
information.
That's
posted
I
listed
my
three
favorite
blocks
on
this
site.
B
A
Thank
You
Catherine
for
your
excellent
presentation.
We
have
a
few
minutes
for
questions
so
if
you
could
type
them
in
the
chat
box
at
the
lower
left
of
your
screen,
I
will
ask
Catherine
to
address
as
many
as
we
can
get
to
I'll
start
Catherine
with
the
first
one
we
have
about
citing
the
source.
Should
you
include
the
gear
I'm
thinking
that
if
you've
also
put
the
year
somewhere
in
the
title
such
that
it
would
be
repetitive.
B
And
I
think
there's
several
ways.
You
could
cite
a
source
site,
I'm
thinking
about
some
of
the
reports
we
do.
If
something
has
a
year
that's
easily
recorded,
then
that
would
be
good,
sometimes
I've,
seen
reports
where
people
have
like
a
sources
cited
at
the
end.
That
would
have
more
information
about
sources.
B
You
might
have
noticed
on
our
on
the
chart
that
I
modified
throughout
this
presentation.
I
had
a
really
simple
source
listed
there.
That's
because
I
took
data
from
15
different
surveys
to
make
that
that
chart
and
I
thought
it
would
overwhelm
the
visual
if
I
had
included
all
of
those
sources
in
there.
But
if
that
was
included
in
a
report,
I'd
probably
have
a
sources
cited
page.
A
B
Like
I
said
before,
the
small
muscles
are
really
versatile
type
of
chart.
You
can
use
them
with
bar
charts
or
line
charts
to
compare
multiple
things
so,
for
example,
in
a
report
that
my
office
published
in
March
that
same
one,
that
I
showed
you
the
excerpt
from
earlier
in
the
presentation
we
used
small
multiples
line,
charts
in
that
in
that
report
to
present
data
over
time
about
whether
this
office
had
met
deadlines
for
completing
and
starting
their
investigate,
and
we
used
those
charts
side-by-side.
B
So,
for
example,
this
office
has
to
meet
many
different
deadlines,
so
there's
a
two-day
deadline,
a
10-day
deadline
and
a
60-day
deadline,
and
we
wanted
to
compare
all
on
the
same
graph,
those
deadlines,
but
you
know
they
had
different
underlying
data
and
they
each
were
unique
graph.
So
they
are
literally
three
separate
graph
stacked
up
next
to
each
other,
with
the
same
@y
ax
and
the
same
x
axis,
but
repeated.
A
B
Like
I
said,
there
are
several
computer
programs
and
websites
out
there
that
you
can
use
to
help
see
what
that
exhibit
or
what
chart
would
look
like
to
people
with
colorblindness.
So,
for
example,
I
don't
have
the
URL
off
the
top
of
my
head,
but
I
think
it's
like
colorblind.
You
were
or
something
I
would
suggest:
Google
inna,
Google,
googling
colorblindness
program
and
basically
it
has
closed
a
copy
of
the
exhibit
as
a
JPEG
or
a
picture
form.
And
then
you
can
toggle
through
different
types
of
chocolate
blindness
and
it
will
overlay
a
filter.
A
B
B
That
Gide
was
some
discussion
with
leadership
in
the
office
about
what
the
main
color
of
our
reports
was
going
to
be,
and
we
decided
on
like
a
dark
navy,
blue
and
at
that
point
then
I
used
a
Adobe
product
called
Adobe
color
to
plug
in
the
code
for
that
dark
navy,
blue
color
and
I
was
able
to
find
colors
that
work
that
were
complementary
to
that
color
and
then
continued
building
palettes
off
of
the
colors.
That
I
was
fine
using
this
program,
so
we
have
many
different
palettes,
I,
think
six
or
seven.
B
Well,
that's
a
complementary
color
palette,
the
blues
and
purples
and
greens
I
can
use
you
can
use
when
you're
use,
presenting
categories
of
data
and
then
there's
a
diverging
color
palette
that
has
blues
and
oranges
and
those
you
use.
For
example,
if
you're
presenting
Likert
scale
questions
with
or
survey
questions
that
have
you
know
positive
values
and
some
negative
values.
So
you
design
blue
and
the
shades
of
blue
to
positive
and
shades
of
orange
to
the
negative.
B
B
Well,
that
that's
a
great
question
as
well:
there's
a
lot
of
research
out
there
about
typology,
which
is
the
cell
phones
and
again
I,
would
point
you
to
those
resources
that
I
had
at
the
end
of
presentation
but
generally,
and
what
my
office
has
decided
on
in
charts.
You
kind
of
have
a
smaller
area
to
put
a
lot
of
information,
and
so
a
good
font,
for
that
would
be
something
like
Arial
narrow,
which
is
the
condensed
font
in
the
rest
of
our
report.
In
the
text
we
use
Times,
New
Roman
and
our
letters
are
Arial.
A
B
I
think
there
are
a
lot
of
opinions
about
that.
What
I
have
read
is
that
using
a
different
font
for
headings
and
a
different
font
for
the
text
of
the
report
is
a
good
practice,
because
it
helps
queue,
your
readers
and
to
noticing
changes
between
headings
and
text
and
then
adding
that
third
type
of
font
on
to
our
exhibits
was
kind
of
a
decision
to
again
separate
that
exhibit
from
the
rest
of
the
text
as
well
as
have
some
a
little
bit
more
room
to
include
information.
A
B
There
might
be
a
plug-in
somewhere
online
to
create
that
in
Excel,
but
when
I've
made
them
again,
I've
used
like
a
free
online
software
program,
but
things
like
the
lollipop
grass,
so
there's
dot
plots
and
the
dumbbell
dot
plots.
Those
are
all
hackable
using
Excel
and
those
graphs
that
I
just
mentioned,
and
those
are
actually
scatter
plots
that
I,
you
know
manipulated
into
to
show
those
unique
graph
types.
A
A
All
right
well
seeing
that
we've
gotten
through
all
our
questions
and
we're
one
minute
shy
of
ending
here.
I
just
wanted
to
thank
Kathryn
again
for
that
fabulous
presentation,
and
thanks
to
all
of
you
out
there
for
joining
us
today,
this
webinar
has
been
recorded
and
was
made
available
on
the
NCSL
website
in
the
next
few
weeks.
The
webinar
is
now
concluded.