This chapter is a very brief introduction
to some of the most important
fundamentals of communicating
ideas using visual signs.
There's some very basic principles
that if you keep in mind,
as you design your visualizations,
they really become essential and valuable.
As you make your own design your own
visualizations to present your own data.
And you'll find that there's some
very simple things you can do
that I think will help tremendously.
So the first, and
probably one of the most often overlooked
ideas, is the concept of The Grid System.
So this is a page I've taken from
Josef Mueller-Brockman's extensive
book on grid systems, and
what you can see here is he's laid out
the idea of how a grid organizes
data when it's presented on a page.
And what you can see here is that
the information's organized into columns.
Each column is left-justified to each
of the each of the different grids.
[COUGH] Excuse me.
The margins between the grids
are all the same size,
and the line height is the same size.
Now, this gives incredible meaning and
organization to the,
to what's being presented.
So first of all you'll see that the eye
very naturally flows across and
down each one of the columns.
Separately, following that gestalt
principle that we talked about before,
of proximity,
things that are in the same column,
are our mind reads them as having
perceived similarity of meaning.
They can see how the grid system,
is utilized by a newspaper
like the New York Times to present what
is truly a very dense amount of data.
And one of the reasons that it
makes sense is because they have so
strictly enforced the grid.
There's another major principle that
the New York Times is abiding by here.
And it's something that we can
find when we go back even to
ancient Egyptian papyrus, and it's this
idea that's called hierarchy of size.
And in this beautiful scene taken
from the Egyptian Book of the Dead,
the most important figures are look,
the biggest.
And so what you see here is in the center
on the bottom row is the god Anubis,
and Anubis is twice the size of
the human being on his left.
Now, we interpret this in modern times
not to mean that Anubis was twice as
tall as a man, but that he was twice
as important as the other figures.
And you'll find that the royal,
the people on the left who are the same
size as the gods are the rulers.
So this hierarchy of size is imposed,
also in The New York Times,
where you'll see that the main what is
the biggest visual item on the page?
Well, it's the headline, right?
It's The New York Times logo.
What's the second biggest
thing on the page?
It's the central image,
and the central column.
So your eye is drawn to the most
visually dominant aspect of the page.
So the reason why making things
large gives them more meaning.
So the idea of hierarchy of size and
grid are really being strictly being
enforced by the New York Times.
What are some other basic
elements of visual communication?
Another one of the most common
is this idea of grouping.
And you can see how this appears
in the periodic table here,
and very often one of the most
important parts about
the periodic table is the way that
the columns themselves are organized.
And what you have on the left
are all of the metals and
what you have on the right are all of the
non-metals, and in the middle are all of
the transition metals, and on the very
bottom is the lanthanum series.
And these groups are given meaning
by being next to one another.
In other words,
it's very clear that hydrogen and
lithium share a common quality
by being in the same column.
There's one additional
principle that I think is very,
very often overlooked in
scientific visualization.
Tufte brings this about, and he calls
this idea one plus one equals three.
So let me explain it.
Let's take a moment.
Look at the screen and
tell me what you see.
I mean most people would
say they see two lines.
Let's go again.
Now tell me what you see.
I think most people consistently say,
I see two lines.
Let's do it one more time,
now what do you see?
Most people will say,
I see two lines and a space.
It's very much like the two lines now
create a road through this, graphic.
Essentially, the content is the same,
but the spacing is different.
And there's a perceptive
psychology effect here, and
Tufte calls this,
one plus one equals three.
And what he means is that even though you
have two graphical elements on the page,
what you really have to pay attention
to is the third graphical element,
which is the negative space that's created
between two strong graphical elements.
So when you create lines,
what's very important is that you realize
that you're not just drawing a line,
but by dividing space you're creating
all the negative space around it.
So it's very easy in drawings for
us to create many lines that all,
call for our attention.
So what is one of the ways that we can
offer understanding the principles of
psychology, to, and perception, for
how to minimize something like this?
Well, let's look at what
Tufte would call reduction of
noise in this classic box and
whisker plot.
So very briefly, the plot shows a number
of categories along the X axis.
What you see is the max and
min values along the lines, and
then the box and those are the whiskers,
and the box shows the standard deviation,
the you know, the majority of the, 95% and
the line in the middle shows the median.
So, this is a,
traditional scientific graph that
really came out of two key in the 50s.
So, what is it about
this graph that really
confronts this concept of
one plus one equals three?
Well, Tufte has another idea that
he calls the graphical integrity.
The main idea is that every line in
a visualization should convey meaning, and
you should convey meaning in
the most compact form possible.
So let's take an example.
What are lines that don't
need to be on this screen?
Well, let's take the most obvious ones.
The first is the background lines.
They don't really need to
communicate what can be shown in
the very small little ticks that are now
placed on the left, and it reduces
the graphical noise significantly and
it doesn't change the meaning at all.
Well, let's continue to reduce.
What are other lines on this
page that we don't need?
Well very often,
you'll see that scientists will
create figures in boxes, right?
But the box very clearly violates this
principle of one plus one equals three,
because what does it do?
It draws attention to the box,
what you really want to pay
attention to is the data.
So how do we get rid of the box?
We can very simply remove the top and
the right,
which don't add any meaning to the figure.
So if you're learning anything from this,
it's, think about the graphs that
you're drawing, and how much
additional line they are including for
the data that they communicate.
Tufte goes even further,
and he says you know what?
The box is a two-dimensional box, but
what it's really communicating
is the top and the bottom point.
And the line is a point,
it doesn't need to be a line.
So if we want to reduce this even further,
we can actually remove the box entirely
and replace the midpoint with a dot.
Now you have a graph that has no
less meaning, and far less ink.
In the way that Tufte
describes data graphics,
this is a high value for us to strive for.
Another thing that we can
do that really allows us to
focus on this idea of one
plus one equals three.
Look at each one of
the graphical lines here.
They're really significant, and,
when you look at the image,
you don't just see the data.
You see the line.
But the line is really pointing you,
just to the endpoints, right?
What it's really showing you,
is, the top line is
showing you the maximum data point,
and, the top of the standard deviation.
So, what if you also diminish
the intensity, or the width, of each line?
And now what you do is you've
taken very thick lines,
which draw attention to themselves,
and made it so
that what you're paying attention
to are the end points of the lines.
So you can even further
reduce the noise or
the ink necessary to communicate
the number of data points
in a graph by turning down
the intensity of the lines.
Tufte talked about this as expressiveness.
What's important is that data
graphics are expressive and
here I've chosen McKinley's description
which is the idea that, visual,
graphics need to express all the facts in
the data and only the facts in the data.
This is something that's very easy to do,
to accidentally, violate, and
I'll give you a quick example.
So here you see a data set that shows
you the relationship between a different
number of car manufacturers and
the country in which they're manufactured.
So look at this graph,
what is wrong with it?
So you see that, you can easily look at
this, and tell that the various cars,
come from different nations, but
what's misleading about this graphic?
Well, what's misleading about this
graphic, is the bar communicates
an idea of a continuous value,
and that the bar for
Honda is bigger than the bar for
the ACM, for the AMC.
And actually, there's no quantity
communicated in each of these values.
And a better way for us to represent
this fact would be by showing points.
What we actually have is
that we're mapping ordinal,
excuse me, nominal values, right?
Category labels,
which is the country with the origin of
the manufacturer of each car and
nominal values don't have magnitude.
So when you show them using
a bar chart like that,
you give a, the false impression
that there's meaning in the data.
That implies a magnitude that's not there.
So, this graph is not expressive in
the way that McKinley describes it,
because it's communicating information
that's not actually there.
Another thing that Tufte talks about,
with this idea of data ink.
If we're going to make the graph
as have as few pixels as possible,
to communicate the most meaning, what is
the furthest possible way that we can go.
Is what Tufte calls a chart junk,
and chart junk is
a wonderful example of how
data graphics appear very often in
popular culture in magazines and
they're designed to give this huge
emotional impact, like you can see
in this graphic,
what's trying to be shown by the newspaper
is this idea that the costs of
elections are becoming monstrous.
And so they have this
Tasmanian devil serpent, and
the teeth of the devil serpent represent
the spending levels, and they're going up.
But if you look at the graph to the right,
what's represented is the same value,
empirically.
So in the way that Tufte
represents graphics,
the graphic on the right is
the more meaningful graphic,
because it communicates the same
data with far less editorial,
right, far less unnecessary graphic,
graphical marks.
Now it's also important to note is,
while I think Tufte,
is a purist, in the way representation
should include meaning and
only meaning,
experiments have shown that readers
remember infographics with this
kind of emotional content better.
So, as a designer of graphics you'll have
the option of deciding the faithfulness
of the representation.
So what I hope comes clear to you
from this particular chapter is that
there are a number of ways that you can
choose to represent the data, and that,
they, are small changes can give
you significant multiplier in
the organization and the legibility of
your graphics as well as their integrity.
And I hope that you feel more well
equipped to make decisions about how
to decide how to encode
particular kinds of data.