Hi my name is Eleanor Lutz and I like to use art and data visualization ah to try
and take scientific topics and share them with the general public, so my most
recent project was a series of about ten different maps of astronomy data taken
from open sources like NASA and the USGS so I'd like to talk a little about some
of the things I learned from making these maps and then some of the design
decisions behind each one, so to give you a bit of background when I share these
maps all of the code is open sourced on github
with tutorials so that anybody who wants can make the maps themselves. I also have
the maps available as posters and the people who tend to generally use them
are people who have young kids or our teachers and classrooms so that's really
the kind of audience that I'm designing for, this first map shows the orbit paths
of about 18,000 asteroids in the solar system, so this map was probably the
most difficult one for me because I needed to pull together data from about
five different open data sources and put them together and the the question I
really tried to answer while making this map was what was the the general message
I wanted to get across to these children or the general public and for me what
was the most awesome thing about this data was just that there are so many
asteroids all over the solar system and I'm not actually a space scientist so
this is something that was really surprising to me so I decided to use
design decisions that would really emphasize that point so for example I'm
showing you all of the orbits here on a logarithmic scale with most of the map
focus on the first billion kilometers from the Sun and this was a design
choice that let me include everything to the boundaries of the solar system but
still leave enough space to see just how many asteroids are in the inner
areas
okay so for other projects I had to do much less data wrangling so this is a
geologic map of Mars some of you might recognize the data from the USGS map
which basically had all the data I'm showing here already laid out and
organized the main design choices I did here was really to work with the
language in the map the original map was I think intended for scientific
audiences so the labeling and the colors were very difficult to understand
especially for young audiences so in the bottom here I've really shortened all
the descriptions and tried to use vocabulary that everybody could
understand. I also changed the colors of the map, so here's a zoomed in version
I've decided to really emphasize the volcanic geologic region so I'm making
them a really bright red and then also to emphasize the difference between the
northern and southern hemispheres by putting slightly different color schemes
so I want to point out that sometimes these design decisions don't necessarily
make the map more legible I think some of the volcanic regions in particular
can be a little hard to read but because these maps weren't for a scientific
purpose I could make design decisions that were a little more creative and
that emphasized the volcanoes or these other features the planet
sometimes I needed to do a little more simplification of the data to have the
data fit and look well at the size that I was going for so this is a geologic
map of the moon the difficulty here was that because the data for the moon was
much more detailed the geologic features were a lot finer and many of them
couldn't actually be seen at the scale that I was showing at these posters
these clusters size, so when I went through the data I that many of the
smaller geologic features were actually different ages of the same material and
this was causing a lot of noise in areas that had been sampled many times, so what
I decided to do for this map was to simplify it to a level where you could
see individual geologic features, so this map doesn't actually include the
different ages of the materia,l it's combined the material the same type of
geologic material for many different ages
okay, I also had to combine I think six different data sets for this moon
geology map, you can actually see the boundaries here where some of the data
sources don't agree with each other, so that was a part where in the previous
map I also decided to include the different data sources as a reference
for why those differences existed
okay I also designed a series of topographic maps of the rocky planets
and the moon so for these maps I use the digital
elevation model from the USGS as well as a database of names that I could
download and plot onto each of these maps in Python, so one of the challenges
of making topographic maps for space was that I found it was very difficult to
kind of understand the scale of the planet because there are no oceans or
other large differences in the in the surface, so what I try to do with these
maps is use a color scale that was very variable from the the lowest parts here
in Navy to the highest parts of the planet and
orange and yellow and making these double color decisions for each of the
planets I think really helped emphasize the scale of the planet by adding a
little more interest in by helping differentiate between the different
elevations
I also made a map of the earth so if you look at this online it's actually
animated so that each of the frames shows the Arctic ice for that particular
month of the year and this is using blue marble data from NASA
okay and this
final set of maps I want to talk about is a map of the constellations as seen
from Earth, so this was one of my favorite maps to work on because there's
just a huge amount of data available, here I've already limited the data I'm
showing to the 8,000 or so stars you can actually see from Earth but there's
still a lot of data a lot of information about the size of the stars and as well
as the constellations and the names of each star this map is actually part of a
series, so here is just the you know the scientific data without the labels and
the lines that people have added and what I realized here was that these
constellations, come from many different cultures so here I'm showing you the
same stars but in this map I'm showing also the constellations from about 30
different cultures or civilizations from around the world each color here is data
from a different culture this is from an open database called Stellarium and what
I really like about this map is that even though it's kind of a tangled mess
of lines you can see that some stars are really popular the ones the large ones
circled with large outlines with a most popular but some constellations are also
very unique so the stars outlined in an outline with just one cultures color is
not used by any other culture in this database so I really enjoyed this
project in particular because I was able to combine scientific data from this
large database with cultural data and kind of
the human history of how we've been looking at stars and working with
astronomy for many hundreds and thousands of years so as I said again
all of this code is available open source please feel free to find me
afterwards if you're interested in learning more about the project and
thank you so much for everyone for listening and for NASA and AGU for
letting me come here