1
00:00:00,060 --> 00:00:08,429
Hi my name is Eleanor Lutz and I like to
use art and data visualization ah to try

2
00:00:08,429 --> 00:00:13,740
and take scientific topics and share
them with the general public, so my most

3
00:00:13,740 --> 00:00:21,539
recent project was a series of about ten
different maps of astronomy data taken

4
00:00:21,539 --> 00:00:27,900
from open sources like NASA and the USGS
so I'd like to talk a little about some

5
00:00:27,900 --> 00:00:31,380
of the things I learned from making
these maps and then some of the design

6
00:00:31,380 --> 00:00:37,110
decisions behind each one, so to give you
a bit of background when I share these

7
00:00:37,110 --> 00:00:40,770
maps all of the code is open sourced on
github

8
00:00:40,770 --> 00:00:46,410
with tutorials so that anybody who wants
can make the maps themselves. I also have

9
00:00:46,410 --> 00:00:51,059
the maps available as posters and the
people who tend to generally use them

10
00:00:51,059 --> 00:00:55,410
are people who have young kids or our
teachers and classrooms so that's really

11
00:00:55,410 --> 00:01:02,160
the kind of audience that I'm designing
for, this first map shows the orbit paths

12
00:01:02,160 --> 00:01:09,540
of about 18,000 asteroids in the solar
system, so this map was probably the

13
00:01:09,540 --> 00:01:13,590
most difficult one for me because I
needed to pull together data from about

14
00:01:13,590 --> 00:01:20,340
five different open data sources and put
them together and the the question I

15
00:01:20,340 --> 00:01:25,380
really tried to answer while making this
map was what was the the general message

16
00:01:25,380 --> 00:01:32,340
I wanted to get across to these children
or the general public and for me what

17
00:01:32,340 --> 00:01:36,259
was the most awesome thing about this
data was just that there are so many

18
00:01:36,259 --> 00:01:41,640
asteroids all over the solar system and
I'm not actually a space scientist so

19
00:01:41,640 --> 00:01:46,110
this is something that was really
surprising to me so I decided to use

20
00:01:46,110 --> 00:01:51,840
design decisions that would really
emphasize that point so for example I'm

21
00:01:51,840 --> 00:01:57,180
showing you all of the orbits here on a
logarithmic scale with most of the map

22
00:01:57,180 --> 00:02:02,490
focus on the first billion kilometers
from the Sun and this was a design

23
00:02:02,490 --> 00:02:07,200
choice that let me include everything to
the boundaries of the solar system but

24
00:02:07,200 --> 00:02:12,510
still leave enough space to see just how
many asteroids are in the inner

25
00:02:12,510 --> 00:02:14,930
areas

26
00:02:19,319 --> 00:02:26,489
okay so for other projects I had to do
much less data wrangling so this is a

27
00:02:26,489 --> 00:02:33,500
geologic map of Mars some of you might
recognize the data from the USGS map

28
00:02:33,500 --> 00:02:39,780
which basically had all the data I'm
showing here already laid out and

29
00:02:39,780 --> 00:02:46,019
organized the main design choices I did
here was really to work with the

30
00:02:46,019 --> 00:02:51,239
language in the map the original map was
I think intended for scientific

31
00:02:51,239 --> 00:02:56,989
audiences so the labeling and the colors
were very difficult to understand

32
00:02:56,989 --> 00:03:02,549
especially for young audiences so in the
bottom here I've really shortened all

33
00:03:02,549 --> 00:03:07,109
the descriptions and tried to use
vocabulary that everybody could

34
00:03:07,109 --> 00:03:18,030
understand. I also changed the colors of
the map, so here's a zoomed in version

35
00:03:18,030 --> 00:03:22,560
I've decided to really emphasize the
volcanic geologic region so I'm making

36
00:03:22,560 --> 00:03:28,019
them a really bright red and then also
to emphasize the difference between the

37
00:03:28,019 --> 00:03:32,180
northern and southern hemispheres by
putting slightly different color schemes

38
00:03:32,180 --> 00:03:38,010
so I want to point out that sometimes
these design decisions don't necessarily

39
00:03:38,010 --> 00:03:43,199
make the map more legible I think some
of the volcanic regions in particular

40
00:03:43,199 --> 00:03:49,229
can be a little hard to read but because
these maps weren't for a scientific

41
00:03:49,229 --> 00:03:55,409
purpose I could make design decisions
that were a little more creative and

42
00:03:55,409 --> 00:04:01,400
that emphasized the volcanoes or these
other features the planet

43
00:04:05,380 --> 00:04:13,260
sometimes I needed to do a little more
simplification of the data to have the

44
00:04:13,260 --> 00:04:18,900
data fit and look well at the size that
I was going for so this is a geologic

45
00:04:18,900 --> 00:04:25,020
map of the moon the difficulty here was
that because the data for the moon was

46
00:04:25,020 --> 00:04:30,930
much more detailed the geologic features
were a lot finer and many of them

47
00:04:30,930 --> 00:04:35,160
couldn't actually be seen at the scale
that I was showing at these posters

48
00:04:35,160 --> 00:04:41,880
these clusters size, so when I went
through the data I that many of the

49
00:04:41,880 --> 00:04:49,410
smaller geologic features were actually
different ages of the same material and

50
00:04:49,410 --> 00:04:57,090
this was causing a lot of noise in areas
that had been sampled many times, so what

51
00:04:57,090 --> 00:05:01,680
I decided to do for this map was to
simplify it to a level where you could

52
00:05:01,680 --> 00:05:07,140
see individual geologic features, so this
map doesn't actually include the

53
00:05:07,140 --> 00:05:12,450
different ages of the materia,l it's
combined the material the same type of

54
00:05:12,450 --> 00:05:17,420
geologic material for many different
ages

55
00:05:26,060 --> 00:05:31,730
okay, I also had to combine I think six
different data sets for this moon

56
00:05:31,730 --> 00:05:35,840
geology map, you can actually see the
boundaries here where some of the data

57
00:05:35,840 --> 00:05:41,120
sources don't agree with each other, so
that was a part where in the previous

58
00:05:41,120 --> 00:05:47,240
map I also decided to include the
different data sources as a reference

59
00:05:47,240 --> 00:05:50,160
for why those differences existed

60
00:05:56,120 --> 00:06:01,490
okay I also designed a series of
topographic maps of the rocky planets

61
00:06:01,490 --> 00:06:04,729
and the moon
so for these maps I use the digital

62
00:06:04,729 --> 00:06:10,639
elevation model from the USGS as well as
a database of names that I could

63
00:06:10,639 --> 00:06:16,370
download and plot onto each of these
maps in Python, so one of the challenges

64
00:06:16,370 --> 00:06:21,650
of making topographic maps for space was
that I found it was very difficult to

65
00:06:21,650 --> 00:06:25,760
kind of understand the scale of the
planet because there are no oceans or

66
00:06:25,760 --> 00:06:32,540
other large differences in the in the
surface, so what I try to do with these

67
00:06:32,540 --> 00:06:39,470
maps is use a color scale that was very
variable from the the lowest parts here

68
00:06:39,470 --> 00:06:42,050
in Navy
to the highest parts of the planet and

69
00:06:42,050 --> 00:06:51,500
orange and yellow and making these
double color decisions for each of the

70
00:06:51,500 --> 00:06:56,180
planets I think really helped emphasize
the scale of the planet by adding a

71
00:06:56,180 --> 00:06:59,840
little more interest in by helping
differentiate between the different

72
00:06:59,840 --> 00:07:02,050
elevations

73
00:07:05,670 --> 00:07:10,620
I also made a map of the earth so if you
look at this online it's actually

74
00:07:10,620 --> 00:07:14,880
animated so that each of the frames
shows the Arctic ice for that particular

75
00:07:14,880 --> 00:07:19,580
month of the year and this is using blue
marble data from NASA

76
00:07:23,040 --> 00:07:25,280
okay and this

77
00:07:25,290 --> 00:07:30,180
final set of maps I want to talk about
is a map of the constellations as seen

78
00:07:30,180 --> 00:07:36,330
from Earth, so this was one of my
favorite maps to work on because there's

79
00:07:36,330 --> 00:07:41,160
just a huge amount of data available,
here I've already limited the data I'm

80
00:07:41,160 --> 00:07:47,550
showing to the 8,000 or so stars you can
actually see from Earth but there's

81
00:07:47,550 --> 00:07:53,760
still a lot of data a lot of information
about the size of the stars and as well

82
00:07:53,760 --> 00:08:00,210
as the constellations and the names of
each star this map is actually part of a

83
00:08:00,210 --> 00:08:07,350
series, so here is just the you know the
scientific data without the labels and

84
00:08:07,350 --> 00:08:14,190
the lines that people have added and
what I realized here was that these

85
00:08:14,190 --> 00:08:20,700
constellations, come from many different
cultures so here I'm showing you the

86
00:08:20,700 --> 00:08:26,400
same stars but in this map I'm showing
also the constellations from about 30

87
00:08:26,400 --> 00:08:33,599
different cultures or civilizations from
around the world each color here is data

88
00:08:33,599 --> 00:08:39,960
from a different culture this is from an
open database called Stellarium and what

89
00:08:39,960 --> 00:08:45,240
I really like about this map is that
even though it's kind of a tangled mess

90
00:08:45,240 --> 00:08:50,850
of lines you can see that some stars are
really popular the ones the large ones

91
00:08:50,850 --> 00:08:57,420
circled with large outlines with a most
popular but some constellations are also

92
00:08:57,420 --> 00:09:04,560
very unique so the stars outlined in an
outline with just one cultures color is

93
00:09:04,560 --> 00:09:11,220
not used by any other culture in this
database so I really enjoyed this

94
00:09:11,220 --> 00:09:16,860
project in particular because I was able
to combine scientific data from this

95
00:09:16,860 --> 00:09:21,280
large
database with cultural data and kind of

96
00:09:21,280 --> 00:09:25,960
the human history of how we've been
looking at stars and working with

97
00:09:25,960 --> 00:09:33,430
astronomy for many hundreds and
thousands of years so as I said again

98
00:09:33,430 --> 00:09:37,990
all of this code is available open
source please feel free to find me

99
00:09:37,990 --> 00:09:42,430
afterwards if you're interested in
learning more about the project and

100
00:09:42,430 --> 00:09:46,480
thank you so much for everyone for
listening and for NASA and AGU for

101
00:09:46,480 --> 00:09:49,200
letting me come here