[MUSIC PLAYING]
EDWARD TUFTE (VOICEOVER): In the
arrangement of visualization,
every single pixel should
testify directly to content.
As Johnny Ive, the great
Apple designer, said,
we spend most of our time
getting design out of the way.
It's got to get out of
the away, because it's
about the relationship
with the viewer
and how they reason
about the content.
Style and aesthetics cannot
rescue failed content.
If the words aren't
truthful, the finest
optically letter-spaced
typography
won't turn lies into truths.
There are enormously
beautiful visualizations,
but it's as a
byproduct of the truth
and the goodness
of the information.
The big steps in
showing information
began all with cartography,
about 6,000 years ago,
when the first map was
scratched into a piece of stone.
And that has wound up now
with the most widely seen
visualization in
the world, which
is Google Maps, where people
are using a visualization
to actually do something.
The next big step was
development of real science.
Galileo got his telescope going.
He saw things that have
never been seen before.
He made beautiful
drawings of sunspots,
and he'd watched the
sun for about 40 days,
and he did engravings
of the sunspots.
So he visualized what he saw.
And so the history
of visualizing data
is, very substantially,
a history of science.
JULIE STEELE (VOICEOVER):
Data visualization is not just
some airy fairy,
creative process,
but it's actually a
very linear process
of decision making
that you can do based
on some few basic principles.
Three things should
inform your design always.
One is you, as the designer.
What you have to say and
what you want to communicate.
Two is the reader.
That reader is not
you, and they're
going to come with their own
context, and their own biases,
and their own assumptions, and
you need to account for that.
And third is the data itself,
and what that has to say,
and how that informs the truth.
There's a lot of subconscious
brain activity happening.
We evolved for it
to happen that way.
We evolved to see things
and make snap decisions.
Are all those lines in the
graph just dried grass,
or is that a tiger
that's coming to eat you?
[GROWLING]
We have to be able to recognize
those patterns right away
and make snap decisions on
them in order to survive.
And that can be an
advantage as a designer.
You can communicate
a lot of information
very quickly, because we all
have brains that are designed
to recognize patterns this way.
But also, there's
the emotional impact.
We react to design, and to
art, and to the aesthetics
of a piece, just
as much as we react
to the information
contained in it.
And so if you want to
change someone's mind,
if you want to change
someone's behavior,
sometimes presenting the
information in a visual format
is the fastest way
to get them to engage
with that information.
JOSH SMITH (VOICEOVER): Truth
is one of those ambiguous things
that you can't really
define, and probably changes
and evolves, the more
understanding you have.
Data itself is a
result of research.
So I would say that data is
just a clue to the end truth.
I think a successful
infographic tells a story.
It communicates, hopefully,
accurate and sometimes
complicated data in a way that
many people can understand.
I think the first step,
usually, is always
dig really deeply into the
data ourselves, and find
each key point, and create a
hierarchy, and a narrative out
of that story.
When you start to
merge different pieces
of information,
and when you start
to learn really what it's all
saying, the narrative is clear.
The one key fact that
everything can revolve around,
it's the hero of the piece.
There's one single
piece of data or insight
that people respond to
and kind of encapsulates
the whole vision.
And then invite people in
to see the nuances and all
of the rest of the
story around it.
When you look at a
piece, it's successful
when it translates data from
something that's complicated
to something simple.
When it communications
a message that otherwise
would have taken somebody
hours to digest and find
in an instant.
JER THORP (VOICEOVER):
My deepest interest
lies in the boundary
between data and culture.
Data are measurements
of something.
In very many cases,
the somethings
that we're talking
about are human systems.
We're dealing with data systems
that are larger than anything
that humans have ever built
or experienced before.
And these really
large systems, things
happen within them
that are emerging.
For example, Gate Change
combined shot footage
from airports, for
pretty much every airport
in the world, and then
air travel data as well.
So the central idea
was to show people
that, every time that
you're in an airport,
you are standing on the surface
of a system that is almost too
complex to comprehend.
Any given time, there are
more than a million people
in the air.
And so there's another
purpose of data visualization.
There's revelation, which
is, show us something
that we've never seen before.
This is, for me,
much more exciting.
Anybody can visualize data in
Excel and see some bar charts.
For me, it's about
showing them something
in this kind of loose narrative
frame that they can interpret.
So we show them some
pieces of the picture,
and the idea is that they can
sort of stand back from that
and watch it pass for a
little bit, and come out of it
with some deeper understanding.
Part of it is leaving it open to
interpretation, but part of it
is also not really knowing.
I don't have some masterful
understanding of this system
that you don't.
I have some ideas about
how these systems might
be changing, and how
they might be growing,
and how they may be important
toward culture and society,
and I want to share some
of those ideas with you.
And maybe you can put
together something
that I wouldn't have been
able to put together.
EDWARD TUFTE (VOICEOVER):
I think in general,
audiences are a lot smarter
than a lot of people think.
So it's not know your audience,
it's respect your audience,
and really know your content.
That's what you should be
knowing and reasoning about.
Look after truth and
goodness, and beauty
will look after herself.
You want to see to
learn something,
not to confirm something.
We usually see to
confirm things.
It's very economizing
for the brain.
How can we see not to
confirm, but to see to learn?
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