we explain an abstract idea well
analogies are helpful because they allow
us to take something abstract and map it
to something concrete and in that way we
can explain for example like when we’re
trying to explain how electricity moves
through a wire we might use the analogy
of water moving through a pipe anecdotes
are also helpful for explaining abstract
ideas think about the classic story of
the Apple falling on Isaac Newton’s head
as a way to understand how gravity
functions in the world around us so
visually we also use analogies and
anecdotes we can think of a chart as a
visual analogy where we denote an
increase in something as a movement
upwards and change over time from left
to right pictures and illustrations are
visual anecdotes that explain a larger
story a picture is worth a thousand
words so oftentimes we think of science
and art as opposites but in reality
they’re more like two sides of the same
coin trying to understand and explain
abstract ideas I work at the complex
system Center at the University of
Vermont complex systems exist in a wide
range of different fields we can kind of
think of them as nodes and linkages or
networks in a system so when we’re
trying to make sense of these networks
while they may be qualitatively
different they have some quantitatively
similar characteristics so the way in
which a contagion spreads through a
school system may be similar actually to
the way that a meme or hashtag spreads
across social media or the way that a
cascading failure causes a power grid
blackout may be mathematically similar
to the way that cancer metastasizes in
cells so the complex system center is
this interdisciplinary research hub
where students faculty and staff
from a whole bunch of different fields
of study come together and talk about
these similar phenomena so I’m a data
visualization artist at that complex
system Center and there are really two
different kinds of visualizations that I
create the first is the communicative
graphic so that’s something where we’ve
found some finding that we want to share
with the scientific community and so we
create a graphic to publish say in a
scientific journal or on a blog post but
then there’s this other kind of graphic
the one that I really get excited about
and that’s the exploratory graphic and
that’s where we have this complex
network we have this huge data set and
we don’t really know what we’re going to
find in it we just need to start pulling
it apart and making sense of the
relationships so to back up a little bit
I’m not a data scientist I studied
graphic design and when I left school I
went to go work as a designer and I was
programming those annoying display
banner ads where the car drives across
the top of your browser I’m sorry but I
started thinking about how I as an
artist was using technology and I ended
up going back to school to Champlain
College where they have an emergent
media master’s program and in that
program they really focus on
interdisciplinary exploration and
celebrate curiosity and playfulness so
today I’d like to share with you two
stories from my time in that program so
synesthesia is this weird phenomenon
where people will map one sense to
another so they may be able to say here
a smell or taste a color and I have
synesthesia for numbers and letters and
days of the week so when I memorize a
phone number I actually think about the
colors of those numbers as I’m
remembering it I’m not really sure why
the associations are the way that they
are
it’s just kind of the way that my brain
works so I was trying to learn how to
play music and I always get really lost
with sheet music because they’re just
like black dots on a white page and they
start swimming in front of my eyes and I
can’t really focus and so I wondered if
it was possible to kind of induce a
different kind of synesthesia and myself
composers throughout history of had
synesthesia where they map the sound to
a color and so I started experimenting
with a color scheme where the C note was
red the II was yellow and the G was blue
I painted the fretboard of my guitar and
I started learning how to play as best I
so in order to test my color system I
was curious what existing compositions
would look like so this one here is ode
and this was the picture that I kind of
generated with an algorithm that matched
that song and I really enjoyed this
picture because I felt like it kind of
captured the the beautiful like joy and
rainbow of that song so to test it on
another piece also by Beethoven
this one is Fur Elise and it sounds like
so looking at these two pieces by the
same composer side-by-side I really felt
like joy at the fact that there were the
attitude of the two different pieces was
kind of captured by these illustrations
so I continued on my visualization track
and I started creating illustrations of
chord diagrams so this is like how
harmonics work when you’re playing a
chord on the guitar and I showed these
to friends of mine who were musicians
and they got really excited they started
showing me other musicians and
visualizations that I should take a look
at one sort of unintended consequence of
this was I found that my existing
synesthesia for letters was being
supplanted by the new system that I had
created so while I previously thought of
like the letter D as pink
I started thinking of it as orange
because I had mapped the D note to the
letter D so I realized that what I
needed to do instead was really just map
the sound to the color and abandoned the
letter system that we had existing for
notes so I then also painted my electric
keyboard and I’ve started quizzing
myself so I’ll press down the key with
my eyes closed and I’ll try and guess
what color it will be I’ve gotten pretty
good at like C and E I keep mixing up B
and F for some reason but this was a
sort of fun project that was a visual
analogy for a complex abstract idea so
another story I’d like to tell you is
about when I was preparing to leave
graduate school and my fellow students
and I were talking about where we wanted
to live after graduation and we were
thinking oh well it would be really cool
to do a data based project and what if
we could answer this question of what
makes a place livable with data so at
first we started thinking about well
well where do we what kinds of criteria
do we want we thought of a affordability
and we’ve pulled some data about cost of
living and incomes and areas but then we
started thinking we’ll wait is the most
affordable place really the best place
to live a place with high incomes and
low cost of living may have a low cost
of living because the only food
available is fast food so we started
asking all of these other questions like
what about the walkability what about
the music scene what about green spaces
in the area originally we thought that
our process would go something like this
we would find a good question and then
we would find an answer what the most
livable place is and that we could share
that opinion with others and then maybe
we would raise awareness about what
makes places liveable we could change
people’s attitude towards those places
and maybe even cause more young people
to move to an area they might not have
considered before that was kind of
ambitious for a summer project so
instead we decided to focus on just
finding good questions this was the most
fun part for us was asking like we’ll
wait but what about this what about that
and then maybe a little bit of finding
good answers but they were all going to
be subjective answers because livability
is a different criteria for different
people so we created this exhibit called
but what about which was a prototype of
an exhibit because the idea is that we
could have this exhibit in different
locations and the kinds of questions
that people were asking would be
different so we created this interactive
map where you could take a whole bunch
of different data sets and overlay them
so potentially income might be blue and
then cost of living would be yellow and
so areas with a high income and a high
cost of living would be green and then
you could maybe add a third layer on to
that of the poverty rate in an area and
so this allowed people to kind of create
their own custom maps that emphasize the
things that they were most interested in
we also had two displays that were sort
of randomly cycling through these maps
that we
I found and this created a really
beautiful teaching moment at one point
we had a map on the top showed the hours
of television watched on average per
household by state and then the map on
the bottom showed the results of the
2016 presidential election and so there
was a student in front of this display
saying well of course that’s the way
that that state voted because look how
much television they watch and so we had
a really beautiful teaching moment of
correlation is not causation and so just
because two things are happening
simultaneously in the same location
doesn’t necessarily mean that one caused
the other so then my favorite part of
the exhibit was that we invited people
to come in and write their own questions
on the walls this kind of created a
really beautiful aesthetic that invited
people into the exhibit who were just
sort of walking through the college and
seeing all of these questions and then
having questions of their own so in my
work as a data visualization artist a
lot of times I say let’s go back to the
drawing board anyone who has ever spent
time with a five-year-old
knows that they’re constantly asking
like why but why and I’m always that
person at the complex system center
that’s asking like we’ll wait what does
that mean what does that mean can we
boil it down to stick figures or to
visual hypotheses of what we think our
chart might look like before we actually
feed any data into it because of the
interdisciplinary nature of a lot of the
research that we do we also wonder
sometimes could we take a chart of one
thing and then sort of port it over into
a totally different discipline so this
is just an example of a graphic of
volatility inducing mechanisms where the
only thing that I’ve changed is the
so I’ve shared two anecdotes with you
and now I’d like to share one analogy if
we think about science technology
engineering and mathematics
STEM fields as the stem of a plant then
the arts can be the leaf free to kind of
blow in the wind and respond to the
environment while still remaining
grounded and I think that this is a tremendous opportunity for growth
analogies are helpful because they allow
us to take something abstract and map it
to something concrete and in that way we
can explain for example like when we’re
trying to explain how electricity moves
through a wire we might use the analogy
of water moving through a pipe anecdotes
are also helpful for explaining abstract
ideas think about the classic story of
the Apple falling on Isaac Newton’s head
as a way to understand how gravity
functions in the world around us so
visually we also use analogies and
anecdotes we can think of a chart as a
visual analogy where we denote an
increase in something as a movement
upwards and change over time from left
to right pictures and illustrations are
visual anecdotes that explain a larger
story a picture is worth a thousand
words so oftentimes we think of science
and art as opposites but in reality
they’re more like two sides of the same
coin trying to understand and explain
abstract ideas I work at the complex
system Center at the University of
Vermont complex systems exist in a wide
range of different fields we can kind of
think of them as nodes and linkages or
networks in a system so when we’re
trying to make sense of these networks
while they may be qualitatively
different they have some quantitatively
similar characteristics so the way in
which a contagion spreads through a
school system may be similar actually to
the way that a meme or hashtag spreads
across social media or the way that a
cascading failure causes a power grid
blackout may be mathematically similar
to the way that cancer metastasizes in
cells so the complex system center is
this interdisciplinary research hub
where students faculty and staff
from a whole bunch of different fields
of study come together and talk about
these similar phenomena so I’m a data
visualization artist at that complex
system Center and there are really two
different kinds of visualizations that I
create the first is the communicative
graphic so that’s something where we’ve
found some finding that we want to share
with the scientific community and so we
create a graphic to publish say in a
scientific journal or on a blog post but
then there’s this other kind of graphic
the one that I really get excited about
and that’s the exploratory graphic and
that’s where we have this complex
network we have this huge data set and
we don’t really know what we’re going to
find in it we just need to start pulling
it apart and making sense of the
relationships so to back up a little bit
I’m not a data scientist I studied
graphic design and when I left school I
went to go work as a designer and I was
programming those annoying display
banner ads where the car drives across
the top of your browser I’m sorry but I
started thinking about how I as an
artist was using technology and I ended
up going back to school to Champlain
College where they have an emergent
media master’s program and in that
program they really focus on
interdisciplinary exploration and
celebrate curiosity and playfulness so
today I’d like to share with you two
stories from my time in that program so
synesthesia is this weird phenomenon
where people will map one sense to
another so they may be able to say here
a smell or taste a color and I have
synesthesia for numbers and letters and
days of the week so when I memorize a
phone number I actually think about the
colors of those numbers as I’m
remembering it I’m not really sure why
the associations are the way that they
are
it’s just kind of the way that my brain
works so I was trying to learn how to
play music and I always get really lost
with sheet music because they’re just
like black dots on a white page and they
start swimming in front of my eyes and I
can’t really focus and so I wondered if
it was possible to kind of induce a
different kind of synesthesia and myself
composers throughout history of had
synesthesia where they map the sound to
a color and so I started experimenting
with a color scheme where the C note was
red the II was yellow and the G was blue
I painted the fretboard of my guitar and
I started learning how to play as best I
so in order to test my color system I
was curious what existing compositions
would look like so this one here is ode
and this was the picture that I kind of
generated with an algorithm that matched
that song and I really enjoyed this
picture because I felt like it kind of
captured the the beautiful like joy and
rainbow of that song so to test it on
another piece also by Beethoven
this one is Fur Elise and it sounds like
so looking at these two pieces by the
same composer side-by-side I really felt
like joy at the fact that there were the
attitude of the two different pieces was
kind of captured by these illustrations
so I continued on my visualization track
and I started creating illustrations of
chord diagrams so this is like how
harmonics work when you’re playing a
chord on the guitar and I showed these
to friends of mine who were musicians
and they got really excited they started
showing me other musicians and
visualizations that I should take a look
at one sort of unintended consequence of
this was I found that my existing
synesthesia for letters was being
supplanted by the new system that I had
created so while I previously thought of
like the letter D as pink
I started thinking of it as orange
because I had mapped the D note to the
letter D so I realized that what I
needed to do instead was really just map
the sound to the color and abandoned the
letter system that we had existing for
notes so I then also painted my electric
keyboard and I’ve started quizzing
myself so I’ll press down the key with
my eyes closed and I’ll try and guess
what color it will be I’ve gotten pretty
good at like C and E I keep mixing up B
and F for some reason but this was a
sort of fun project that was a visual
analogy for a complex abstract idea so
another story I’d like to tell you is
about when I was preparing to leave
graduate school and my fellow students
and I were talking about where we wanted
to live after graduation and we were
thinking oh well it would be really cool
to do a data based project and what if
we could answer this question of what
makes a place livable with data so at
first we started thinking about well
well where do we what kinds of criteria
do we want we thought of a affordability
and we’ve pulled some data about cost of
living and incomes and areas but then we
started thinking we’ll wait is the most
affordable place really the best place
to live a place with high incomes and
low cost of living may have a low cost
of living because the only food
available is fast food so we started
asking all of these other questions like
what about the walkability what about
the music scene what about green spaces
in the area originally we thought that
our process would go something like this
we would find a good question and then
we would find an answer what the most
livable place is and that we could share
that opinion with others and then maybe
we would raise awareness about what
makes places liveable we could change
people’s attitude towards those places
and maybe even cause more young people
to move to an area they might not have
considered before that was kind of
ambitious for a summer project so
instead we decided to focus on just
finding good questions this was the most
fun part for us was asking like we’ll
wait but what about this what about that
and then maybe a little bit of finding
good answers but they were all going to
be subjective answers because livability
is a different criteria for different
people so we created this exhibit called
but what about which was a prototype of
an exhibit because the idea is that we
could have this exhibit in different
locations and the kinds of questions
that people were asking would be
different so we created this interactive
map where you could take a whole bunch
of different data sets and overlay them
so potentially income might be blue and
then cost of living would be yellow and
so areas with a high income and a high
cost of living would be green and then
you could maybe add a third layer on to
that of the poverty rate in an area and
so this allowed people to kind of create
their own custom maps that emphasize the
things that they were most interested in
we also had two displays that were sort
of randomly cycling through these maps
that we
I found and this created a really
beautiful teaching moment at one point
we had a map on the top showed the hours
of television watched on average per
household by state and then the map on
the bottom showed the results of the
2016 presidential election and so there
was a student in front of this display
saying well of course that’s the way
that that state voted because look how
much television they watch and so we had
a really beautiful teaching moment of
correlation is not causation and so just
because two things are happening
simultaneously in the same location
doesn’t necessarily mean that one caused
the other so then my favorite part of
the exhibit was that we invited people
to come in and write their own questions
on the walls this kind of created a
really beautiful aesthetic that invited
people into the exhibit who were just
sort of walking through the college and
seeing all of these questions and then
having questions of their own so in my
work as a data visualization artist a
lot of times I say let’s go back to the
drawing board anyone who has ever spent
time with a five-year-old
knows that they’re constantly asking
like why but why and I’m always that
person at the complex system center
that’s asking like we’ll wait what does
that mean what does that mean can we
boil it down to stick figures or to
visual hypotheses of what we think our
chart might look like before we actually
feed any data into it because of the
interdisciplinary nature of a lot of the
research that we do we also wonder
sometimes could we take a chart of one
thing and then sort of port it over into
a totally different discipline so this
is just an example of a graphic of
volatility inducing mechanisms where the
only thing that I’ve changed is the
so I’ve shared two anecdotes with you
and now I’d like to share one analogy if
we think about science technology
engineering and mathematics
STEM fields as the stem of a plant then
the arts can be the leaf free to kind of
blow in the wind and respond to the
environment while still remaining
grounded and I think that this is a tremendous opportunity for growth
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