WEBVTT FILE

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Hi my name is Eleanor Lutz and I like to
use art and data visualization ah to try

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and take scientific topics and share
them with the general public, so my most

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recent project was a series of about ten
different maps of astronomy data taken

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from open sources like NASA and the USGS
so I'd like to talk a little about some

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of the things I learned from making
these maps and then some of the design

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decisions behind each one, so to give you
a bit of background when I share these

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maps all of the code is open sourced on
github

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with tutorials so that anybody who wants
can make the maps themselves. I also have

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the maps available as posters and the
people who tend to generally use them

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are people who have young kids or our
teachers and classrooms so that's really

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the kind of audience that I'm designing
for, this first map shows the orbit paths

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of about 18,000 asteroids in the solar
system, so this map was probably the

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most difficult one for me because I
needed to pull together data from about

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five different open data sources and put
them together and the the question I

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really tried to answer while making this
map was what was the the general message

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I wanted to get across to these children
or the general public and for me what

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was the most awesome thing about this
data was just that there are so many

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asteroids all over the solar system and
I'm not actually a space scientist so

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this is something that was really
surprising to me so I decided to use

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design decisions that would really
emphasize that point so for example I'm

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showing you all of the orbits here on a
logarithmic scale with most of the map

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focus on the first billion kilometers
from the Sun and this was a design

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choice that let me include everything to
the boundaries of the solar system but

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still leave enough space to see just how
many asteroids are in the inner

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areas

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okay so for other projects I had to do
much less data wrangling so this is a

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geologic map of Mars some of you might
recognize the data from the USGS map

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which basically had all the data I'm
showing here already laid out and

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organized the main design choices I did
here was really to work with the

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language in the map the original map was
I think intended for scientific

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audiences so the labeling and the colors
were very difficult to understand

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especially for young audiences so in the
bottom here I've really shortened all

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the descriptions and tried to use
vocabulary that everybody could

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understand. I also changed the colors of
the map, so here's a zoomed in version

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I've decided to really emphasize the
volcanic geologic region so I'm making

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them a really bright red and then also
to emphasize the difference between the

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northern and southern hemispheres by
putting slightly different color schemes

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so I want to point out that sometimes
these design decisions don't necessarily

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make the map more legible I think some
of the volcanic regions in particular

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can be a little hard to read but because
these maps weren't for a scientific

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purpose I could make design decisions
that were a little more creative and

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that emphasized the volcanoes or these
other features the planet

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sometimes I needed to do a little more
simplification of the data to have the

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data fit and look well at the size that
I was going for so this is a geologic

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map of the moon the difficulty here was
that because the data for the moon was

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much more detailed the geologic features
were a lot finer and many of them

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couldn't actually be seen at the scale
that I was showing at these posters

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these clusters size, so when I went
through the data I that many of the

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smaller geologic features were actually
different ages of the same material and

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this was causing a lot of noise in areas
that had been sampled many times, so what

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I decided to do for this map was to
simplify it to a level where you could

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see individual geologic features, so this
map doesn't actually include the

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different ages of the materia,l it's
combined the material the same type of

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geologic material for many different
ages

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okay, I also had to combine I think six
different data sets for this moon

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geology map, you can actually see the
boundaries here where some of the data

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sources don't agree with each other, so
that was a part where in the previous

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map I also decided to include the
different data sources as a reference

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for why those differences existed

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okay I also designed a series of
topographic maps of the rocky planets

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and the moon
so for these maps I use the digital

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elevation model from the USGS as well as
a database of names that I could

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download and plot onto each of these
maps in Python, so one of the challenges

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of making topographic maps for space was
that I found it was very difficult to

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kind of understand the scale of the
planet because there are no oceans or

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other large differences in the in the
surface, so what I try to do with these

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maps is use a color scale that was very
variable from the the lowest parts here

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in Navy
to the highest parts of the planet and

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orange and yellow and making these
double color decisions for each of the

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planets I think really helped emphasize
the scale of the planet by adding a

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little more interest in by helping
differentiate between the different

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elevations

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I also made a map of the earth so if you
look at this online it's actually

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animated so that each of the frames
shows the Arctic ice for that particular

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month of the year and this is using blue
marble data from NASA

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okay and this

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final set of maps I want to talk about
is a map of the constellations as seen

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from Earth, so this was one of my
favorite maps to work on because there's

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just a huge amount of data available,
here I've already limited the data I'm

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showing to the 8,000 or so stars you can
actually see from Earth but there's

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still a lot of data a lot of information
about the size of the stars and as well

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as the constellations and the names of
each star this map is actually part of a

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series, so here is just the you know the
scientific data without the labels and

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the lines that people have added and
what I realized here was that these

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constellations, come from many different
cultures so here I'm showing you the

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same stars but in this map I'm showing
also the constellations from about 30

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different cultures or civilizations from
around the world each color here is data

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from a different culture this is from an
open database called Stellarium and what

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I really like about this map is that
even though it's kind of a tangled mess

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of lines you can see that some stars are
really popular the ones the large ones

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circled with large outlines with a most
popular but some constellations are also

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very unique so the stars outlined in an
outline with just one cultures color is

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not used by any other culture in this
database so I really enjoyed this

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project in particular because I was able
to combine scientific data from this

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large
database with cultural data and kind of

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the human history of how we've been
looking at stars and working with

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astronomy for many hundreds and
thousands of years so as I said again

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all of this code is available open
source please feel free to find me

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afterwards if you're interested in
learning more about the project and

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thank you so much for everyone for
listening and for NASA and AGU for

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letting me come here