-: So, birds of a feather flock together.
And my point here when we're talking about maps
is that there are different types of maps, right?
You have navigation maps,
you have maps for identifying
where to find petroleum deposits,
you have thematic maps to communicate data,
all different kinds of maps.
But they're all maps,
and even though they're different from each other
and certainly have different tasks, they have similarities.
Okay, you could put two of these maps side by side
and they might look nearly identical
even though one might be for navigation,
one might be for identifying petroleum deposits.
So, these are different maps,
but oftentimes they look kind of similar,
but, like I said, they enable different tasks.
But here's the thing, they look similar
and part of the reason is because the toolkit is the same
whether you're creating a map for communications
or you're creating a map to share some information
to help find petroleum deposits,
I don't know why I keep using that example,
or for navigation
you're trying to focus on something specific.
You're trying to enable that task.
And the task might be how to find the closest Popeyes
or the task might be essentially understanding the nature
of elections in your state.
But when you think about what you want to focus
your audience on, you're gonna use similar techniques.
So, I'm just gonna share some examples,
this isn't really as much of a lesson
as it is walking through some examples,
and I'll share some stuff that I can think of as we do that.
But really, whether you're creating a navigation map
or any of these other types of maps,
your actual tasks are similar.
So, for those of you who are GIS people,
you've been learning how to create maps
throughout this entire certificate program
or maybe you're an undergrad or grad student
focusing on GIS as part of your studies,
you've learned a lot of stuff
and a lot of those same things apply.
Now, because I come at it from the standpoint
of data visualization and communications,
a lot of the things that I'm gonna say
are gonna be slightly more strongly worded maybe
than what you might have learned
when you were learning how to create cardiographic maps
because my task of communication
is a little bit more focused,
a little bit different than a purely navigational focus.
But long story short, the tasks are the same,
so let's look at some examples
and see if we can make sense of them.
One of them is this great data story from Reuters.
And this is looking at how at the time,
this was back in 2020,
there was the humongous iceberg heading for a disaster,
as it says here.
And the basic gist of it
is that there was this iceberg that came off
of detached from Antarctica
and was drifting along the currents
and was gonna crash into this island, South Georgia island.
And so, this particular map,
you know, look at the design.
This is a beautifully designed map,
very simple overall map
color-wise, very faded back subtle grays and whites.
And we're looking at it from an interesting perspective,
you never see a map
looking from the the south pole up, right?
It's a globe, it's a severe,
but we can see South America off to the left
and all the other stuff off to the right
around the other way.
Long story short,
it's a perspective we're not used to seeing,
and the subtle color really draws the eye
to the only thing that is actually bright and in color,
which is all the blue,
which is showing all these different currents
flowing off and/or around Antarctica.
And then the blue is the shapes,
the pathways of various icebergs
as they've broken off the continent
and have started flowing,
essentially being forced in different directions
by those currents.
We can also see in yellow this iceberg,
the one that is the subject matter
of this particular data story.
So, very subtle clean map
that is really all about a very specific story,
ocean currents,
the history of icebergs and how they've traveled,
and this one and how it sort of fits in
with the vast majority of icebergs clearly flow
up and to the left in this particular view, right?
I don't wanna say north 'cause of course north in Antarctica
is every single direction, right?
So, that can be a little mind demanding
when you look at a map from this direction.
Now, later on in this data story,
they use maps in other ways.
Here we can see satellite photography,
but essentially it's a map-like experience
seeing the iceberg travel
over time and sort of rotate around,
that's kind of cool.
We also see this, which is not a map,
but this is a depiction of the relative size
of this iceberg as compared to other things.
And this is not a map,
but I want to acknowledge it for a second
because we're gonna see a map version of it in a moment.
We can see that this iceberg
is about the size of Cape Verde, right?
This is interesting.
I love the design of this
because these rotated squares
just feel visually more interesting
than if it was a bunch of rectangles,
literally just by rotating them 45 degrees
they look more interesting.
I can compare it to things like Luxembourg
and Reunion Island and Kiribati, et cetera.
And there's a lot of various objects
that I can compare it to.
So, that's interesting, it's visually striking.
I like the sort of the organic design,
but in this particular data story
it's also worthwhile showing it
next to other geographic things.
So, putting it back into a mapping context,
essentially doing both.
I like the idea that they showed it both ways.
Okay, I can see this size of this iceberg
as compared to Puerto Rico, something I'm familiar with,
I have a better sense now of what that really means.
I'll point out one little detail,
by the way, in this particular view.
It's interesting that there are two shades of gray, right?
Puerto Rico and Jamaica are two different shades of gray.
I don't even know why that is,
I don't know if it serves a purpose,
visually I like it though.
So, this is an example
where there's a somewhat extraneous use of color here,
but it doesn't take away from the design.
So, we haven't talked about design
and visualization best practices yet,
we'll talk about that later.
But remember this one when we do talk about that.
Long story short, color,
they use color very simply, very beautifully in this
and yet, they also inject a little bit of extra color
to sort of make it visually more rich.
Later on in this data story,
we get this other map where we can see zoomed in here
a little bit closer view of South Georgia Island,
the island that they're worried this iceberg might run into.
And we also see the path,
and what we see is the path all the way through the ocean
from when it left Antarctica back in 2017.
And then moment by moment we can see the dots,
and I don't know if the dots are every day or every week,
I can't remember what the dots represent,
but long story short, one dot for every place
the iceberg was during 2018, 2019, 2020.
So, clearly it traveled a lot further,
it's going faster once it hits 2020
as compared to previous times.
You can see sort of rotated
and it hung around here for a little while.
But think about this map experience,
once again very subtle, not as subtle as the other one.
We see depth of the ocean here, which is important,
it's part of this, the so what here
because they sort of make a point
to point out the underwater shelf
surrounding South Georgia Island,
the fact that this is shallow water
and therefore that could have an effect
on how the iceberg behaves,
maybe crashes into the shelf
not directly into the island itself, et cetera, et cetera.
So, various maps, even in this one data story
to depict very specific ideas, very specific pieces.
And they're designed differently
because they enable different tasks.
Another example, this data story
comes from the Washington Post, as it says here,
mapping America's wicked weather and deadly disasters.
And so, the Washington Post is great data storytelling,
they have a really good graphics team.
And this is just a series of maps
looking at these various disasters, right?
So, floods, we're looking at zero to 150 floods,
you know, warnings for floods
and where the concentrations are.
So, no surprise, the Mississippi River Delta
and really the heart of the Mississippi River here
is where the vast majority of flooding
occurs in the United States.
There's a good amount in Texas,
there's pretty much just about zero flooding
in like Wyoming, right?
And so, we can see the patterns.
Why does this matter?
This is called thematic mapping.
I can see the data overlaid on top of the geography.
Well, if I was a farmer in the Mississippi Valley,
you know I might be concerned
or thinking about what crops I might plant there.
And obviously, this is gonna help me make decisions
about other things.
If I'm disaster manager in a certain state,
I might know what types of issues to look out for.
Another map shows tornadoes and hurricanes.
No surprise, we know hurricanes are not an issue in Kansas.
Tornadoes though, sure are, right?
And so, it's interesting
that they chose to map these two together.
Tornadoes and hurricanes are very different things
caused by different types of events,
but they're both wind events,
so it also kind of makes sense
that we would look at them together.
We can see a lot of information on this map, right?
Tornadoes are very localized.
Essentially a tornado touches down
and it's a string of disaster.
So, you can see these cone markings,
these these lines essentially for the tornadoes.
Hurricanes are more sort of regional events
and we can see that the areas of impact.
The gold is one level of impact,
the orange is another level of impact,
the strength of the hurricanes.
And they're more sort of overlaid over different regions
not so much very localized and targeted, right?
Two different types of maps, very localized, targeted,
this happened here type of information
versus regionally things tend to happen in this area-ish.
Different technique because of very different thing
that's being enabled,
different type of data being displayed.
Extreme heat and cold.
Really beautiful map here
to show really subtle use of color.
You know, the 3D relief
to show the mountains in the west here
really makes that bright color pop
in such an interesting way.
It looks like lava flowing through these canyons,
but it just really shows you how the intense heat
in the southwest from Phoenix west there
and down to the border,
you know, how intense in Death Valley,
how different that is,
even from just a little bit to the west
or the north or the east.
But there are these pockets of extreme heat
as you go down some of those canyons, really striking.
This one using yet another technique,
just sort of blended color.
Very, very subtle use of color,
very different from this approach.
So, beautifully designed, very thoughtfully done,
really effectively tells a story.
This one is another one
where it's more about very localized,
you know places where wildfires happened,
the perimeters of these larger wildfires
and how many more of them happened in 2018
as compared to the entire decade from 2008 to 2017.
Reveals obviously patterns of fires,
they're mostly in the west.
And yet, some interesting ones like Northern Wisconsin
or maybe that's Michigan at that point.
Oh no, that's, sorry, Minnesota
had it looks like a very big fire at one point.
Northern Florida and Southern Georgia
had really big fire at one point.
I don't really remember those happening,
but this map reveals that information.
So, different techniques
beautifully designed, really bring the story forward.
There's a great article
all about the comparing Google and Apple Maps
and the subtle and not so subtle differences
between the two.
I'm not gonna go through this entire article,
but this is like a masterclass
in essentially different ways
of revealing very similar information
in two different platforms.
And the dramatic difference this can have
in your user experience,
and then also really in what you're able to accomplish
using one or other of these platforms.
This is from a few years ago,
so some of this may not even be relevant,
you know, these map systems get updated all the time.
I'm a big fan of Google Maps.
I used to despise Apple Maps,
but Apple Maps has improved immensely over the years,
and I should remind myself to give it a shot
because there are some things Apple Map does better
from navigation standpoint, from a wayfinding,
from a finding restaurants, et cetera type of standpoint.
They each have pros and cons, right?
And this is a great article
to sort of review some of that information.
And then I'm gonna show you four maps in a row
that are also are just sort of like a masterclass
in just thinking about designing maps
all based on the presidential election.
So, this one, I can't remember if this is from 2016 or 2020,
doesn't matter.
Long story short, as you can see here,
this is your typical election map
county by county across the United States
who won, blue or red, right?
And so, this is a valid map.
This is true.
You know this county in Nebraska voted for Trump, right?
Biden lost or Hillary Clinton lost,
I don't remember which one this is.
Doesn't matter, this is true, right?
But of course, what makes this map potentially misleading
is that, you know, if you look
especially like at Montana, it's huge,
it's a giant swath of mostly red,
which makes it feel like, "Wow, it's all about Trump there."
But in fact, the impact of Montana
is actually less than the impact of Rhode Island,
which is this little teeny thing over here
you can barely see.
So, this in other words, depicts land size
and the importance of land size and who it voted for.
But of course, people vote, not land, right?
So, this map is fair, true, and accurate,
but is it telling the story that is as relevant
for the election as some other maps?
Maybe not.
Here's a different approach.
This map is showing, once again using color,
red or blue, who won county by county, same idea.
The intensity of the color tells us how much they won by.
So, like some of these counties up in Montana
were a lot closer than you realize.
Some of them very stark difference
in some of these other counties throughout the country.
But the height of the county,
the 3D projection also shows us how many people are there.
So, this county went dramatically for Trump,
but almost nobody lives there
compared to this county, which is probably LA County,
where a gazillion people live
and it went for Biden, okay?
Maybe not even as strongly for Biden
as this one did for Trump,
but this county over here,
probably Chicago, Illinois, Cook County
this one has a ton of people in,
it went very strongly for Biden, I believe in this case.
Long story short, both of these maps are true,
one tells a different story than the other.
Okay, this one, same idea,
same data, election data state by state who won,
but now instead of the size of the state,
the actual land mass,
the proportional size is just is by population.
So, it's a donkey, but the donkey is sized by population,
so Biden won and there are a lot of people in California
Trump won Montana,
but there are very few people there, et cetera.
And then last but not least here,
we have another approach.
This is essentially a blended map, blended color.
In all the other ones,
it's who won and by how much.
Okay, not even by how much in all of them.
Here, what is the percentage breakdown,
Biden versus Trump.
So, as we can see here,
first of all, there are a lot of counties
where it was a lot closer than you might realize.
There's also a lot of counties where it's shades of purple.
In fact, the vast majority of the counties
across the United States are some shade of purple,
very few are red or blue.
Sort of a good reminder that we're a lot more mixed
than we might be led to believe.
So, four different maps,
four dramatically different stories based on what?
Whether we're using geography or some proportional symbol,
whether we're using just a binary color system
or a blended color system,
whether the color shows the intensity of who won
or the blending of the percentage share
of votes one way or the other,
et cetera, et cetera, et cetera.
These are not the only ways to map this election data.
In fact, this book, all four of these examples
or three out of the four, come from this one book
this one guy, Kenneth Field, wrote,
which is a hundred maps he created
all from the presidential election.
All wildly different, all valid, true maps,
they just tell very different stories.
So, you might have noticed
that we're looking at different types of maps,
I'm gonna say it again,
whether it's a navigation map, a communication map,
whatever it might be,
the techniques, like I said, don't change.
I'm still deciding am I putting a symbol here, yes or no?
Am I using a blend of color over here, yes or no?
Am I emphasizing this or am I emphasizing that?
Am I trying to emphasize one thing or three things?
The techniques are the same,
it's all about what do I wanna focus my audience on?
That's gonna drive every single decision.
We're back to the whys, right?
What am I trying to do?
What does my audience need?
And yes, what is the data saying?
Figure out your focal points,
figure out what must be emphasized
and design, orient your design towards that.