Who Draws the Lines? The Case for Decentralized Map Making

Billions
of
people
rely
on
maps
to
safely
and
efficiently
navigate
our
world.
Maps
aren’t
food,
clothing
or
shelter,
but
they’re
about
as
close
to
a
basic
human
need
as
you
can
get.
As
we
move
from
destination
to
destination,
we
trust
our
navigation
devices
to
chart
the
best
course.
Next
to
our
eyes,
our
phones
and
GPS
systems
provide
the
clearest
view
of
our
world.

Naturally,
we
want
the
maps
we
rely
on
to
be
accurate.
But
do
they
always
present
the
most
truthful
representation?

This
op-ed
is
part
of
CoinDesk’s
new
DePIN
Vertical,
covering
the
emerging
industry
of
decentralized
physical
infrastructure.

No,
not
always.
And
this
poses
a
significant
issue.

Modern
maps
are
data
repositories,
navigation
systems
and
marketing
devices.
In
their
digital
form,
maps
do
much
more
than
just
offer
a
snapshot
of
the
world.
Our
society
has
grown
increasingly
reliant
on
maps
to
source
everyday
information.
According
to

Google,
more
than
1
billion
people
use
Google
Maps
each
month.
Likewise,
a

UnitedTires
study
revealed
that
60%
of
American
drivers
use
a
GPS
service
at
least
once
a
week.
Combined
with
on-demand
delivery,
taxi
services,
and
searches
for
points
of
interest
(POI)
such
as
restaurants,
supermarkets,
and
charging
stations,
maps
impact

most
people
on
a
near-daily
basis.

So,
who
decides
what
data
gets
included
in
a
map?
What
information
is
omitted?
Is
our
navigation
taking
us
down
the
best
path?
Who
draws
the
lines?

To
answer
these
questions,
we
must
look
at
leading
mapmakers
and
their
motivations
for
shaping
our
world.
As
maps
become
more
prominent
in
our
lives,
these
map
makers
hold
significant
influence
over
day-to-day
decisions.
However,
few
alternatives
exist
for
people
to
access
accurate
map
data
as
a
public
good.
Hence,
the
case
for
decentralized
and
open-source
projects
to
overcome
the
siloed
and
gatekept
mapping
ecosystem.

Today,
a

select
group
of
cartography
companies
are
responsible
for
creating
and
maintaining
the
majority
of
mainstream
digital
maps.

Each
map
conveys
a
particular
viewpoint
shaped
by
its
creators.
Plotting
points
and
drawing
boundaries
may
seem
straightforward,
but
these
tasks
involve
numerous
choices
and
inherent
biases.

Maps
can
drive
behavior,
and
creators
of
purpose-built
maps
might
downplay
or
elevate
features
to
create
desired
outcomes.
For
example,
a
restaurant
may
sponsor
a
navigation
feature
that
shows
their
destination
as
“recommended”
despite
distance,
star
rating
and
so
on.
In
this
case,
the
map
forms
a
pay-to-play
ecosystem
where
businesses
that
“sponsor”
dominate
navigation
and
traffic,
despite
not
necessarily
being
the
“best”
option.

Monetizing
a
map
is
not
itself
a
malicious
act,
but
it
does
carry
significant
consequences
if
the
only
free-to-use
consumer
products
are
primarily
directed
by
ad
spend.
On
the
other
hand,
map
companies
must
generate
revenue
to
sustain
map
data
collection
and
innovation.
As
a
result,
most
public
consumer
maps
make
trade-offs
between
corporate
suggestions
and
data
freshness
and
accuracy.

On
the
business-to-business
side,
map
companies
rely
on
proprietary
information
to
remain
competitive.
Therefore,
free-to-access
maps
are
rarely
as
dynamic,
fresh,
and
data-rich
as
they
could
be.

When
it
comes
to
publicly
available
map
environments,
most
of
us
make
do
with
the
few
free
map
sources
at
hand.
These
maps
are
generally
operated
by
large
entities
that
have
long
dominated
internet
search
and
discovery.
While
they
continue
to
update
maps
and
roll
out
new
features,
their
priorities
and
motivations
aren’t
always
aligned
with
the
public’s
interests.

A
recent

X
post
by
a
former
Senior
UX
Researcher
for
Google
Maps,
Kasey
Klimes,
highlighted
this
issue.
Klimes
explains
the
internal
rationale
behind
Google
Maps
not
including
“scenic”
or
“safe”
navigation
options.
The
thread,
which
has
since
amassed
millions
of
views,
is
filled
with
critics
questioning
the
company’s
motivations
for
omitting
these
highly
requested
features.

The
decisions
made
by
cartographers
reflect
their
understanding
and
the
data
they
have.
Most
maps
today
are
not
a
singular
perspective
but
rather
a
patchwork
of
data
from
“trusted
sources.”
While
map
companies
can
cross-reference
sources
to
improve
accuracy,
it’s
an
imperfect
system.

Despite
their
best
efforts,
mapping
companies
have
faced
significant
challenges
in
verifying
the
truth
and
accuracy
of
their
data.
Geographic
disputes,
censorship,
accidental
additions/omissions,
and
bad
actors
seeking
financial
or
political
gain
all
present
opportunities
for
data
corruption.

For
example:

We’d
like
to
believe
that
most
map
companies
would
never
intentionally
mislead
the
public,
but
it’s
naive
to
think
that
external
sources
and
authorities
might
not
exert
control
over
map
entities.
Mark
Monmonier
said
it
best
in
his
book

How
to
Lie
with
Maps:
“Because
most
map
users
willingly
tolerate
white
lies
on
maps,
it’s
not
difficult
for
maps
to
also
tell
more
serious
lies.”

Blindly
trusting
a
single
source
of
information
is
a
recipe
for
disaster.
As
technology
creates
more
sophisticated
ways
for
compromised
data
sets
to
infiltrate
map
providers,
companies
are
looking
for
better,
more
efficient
ways
to
verify
information
at
scale.

In
2004,

OpenStreetMap
(OSM)
proposed
the
first
major
open-source
solution
to
the
map-making
bias
problem.
It
relied
on
the
collective
intelligence
of
global
volunteers
plotting
geospatial
data
for
anyone
to
use
and
reference.

OSM
has
been
a
significant
step
in
the
right
direction
for
mapping.
Hivemapper
and
almost
every
other
cartography
agency
enthusiastically
support
and
use
the
OSM
database
to
create
mapping
foundations.
As
an
open
initiative,
OSM
doesn’t
house
any
overt
bias
and
allows
the
entire
network
to
determine
what
is
true
and
accurate.

However,
it
is
not
without
its
issues.
Lacking
direct
incentives
or
remuneration
for
independent
contributors,
the
OSM
platform
today
runs
mostly
on
old
or
donated
imagery
from

major
corporations.
While
the
system
remains
open
for
edits,
buffering
against
blatant
corruption
of
geospatial
data,
OSM
still
struggles
to
keep
pace
with
modern
cartography
efforts.

Read
more:
Daniel
Andrade
–



DePIN
Is
the
Sharing
Economy
2.0

Many
errors
and
biases
slip
through
the
cracks,
burdening
map
makers
with
a
constant
game
of
whack-a-mole.
Although
the
solution
is
more
immune
to
singular
manipulation,
it
is
not
completely
impervious.
Cartographic
data
warfare
remains
an
issue,
and
independent
users
can
periodically
corrupt
map
information,
as
seen
with
the
mysterious
user

editing
OSM
in
China’s
favor.

In
a
perfect
world,
who
would
draw
the
lines?

We
would
—
all
of
us.
Not
just
a
select
group
of
cartographers.
If
given
equal
opportunity
to
access
fresh
and
accurate
data,
we’d
throw
off
the
shackles
of
siloed
and
gatekept
mapping
ecosystems
and
create
a
complete,
fresh,
and
infinitely
customizable
map
experience.

It
all
amounts
to
data.

We
have
the
model
for
openness
from
OSM,
but
it
doesn’t
overcome
the
issues
of
collecting
and
vetting
unbiased
data
while
maintaining
a
network
of
valid
sources.
Unfortunately,
human
intermediaries
are
fallible.
Middlemen
corrupt
sources,
keep
fresh
data
behind
lock
and
key,
and
inject
maps
with
their
own
biases.

But
what
if
the
“human”
element
was
minimized?
What
if
we
could
create
a
self-regulating
map
network
that
only
presented
honest
information?
With
blockchain
technology,
this
type
of
map
network
is
no
longer
a
pipe
dream.

In
simple
terms,
a
blockchain
is
a
ledger
that
accurately
tracks
contributions
to
a
network.
Similarly,
cryptocurrencies
use
smart
contracts
to
automate
incentives
within
that
network,
proportionally
rewarding
contributions.
These
contributions
can
also
extend
to
primary
source
hardware,
such
as
dashcams.

Projects
like
Hivemapper
have
leveraged
blockchain-based
rewards
to
recruit
large
networks
of
map
data
contributors.
However,
these
map
contributors
do
not
act
as
middlemen,
nor
do
they
exert
bias
within
the
network.
Contributions
are
automated
through
purpose-built
hardware
and
AI
software,
programmed
to
collect
raw
objective
map
data.

In
Hivemapper’s
case,
contributions
are
attached
to
dashcams
that
capture
and
vet
street-level
imagery,
and
reward
camera
owners
with
cryptocurrency.
Outside
of
the
initial
installation
of
the
camera,
human
elements
are
minimized.
Instead,
the
high-definition
imagery
captured
by
the
dashcams
does
the
heavy
lifting
of
identifying
and
plotting
map
features.

Thousands
of
people
drive
on
roads
every
day,
the
very
roads
we
aim
to
map
and
analyze.
So,
naturally,
we
have
map-ready
fleets
at
our
disposal.
By
supplying
purpose-built
dashcams
that
double
as
map-making
machines,
Hivemapper
is
able
to
automate
map
data
collection
at
a
global
scale.

Read
more:
Sean
Carey
–



Every
DePIN
Has
a
Story

It’s
an
unbiased
system
that
cross-validates
imagery
from
multiple
drivers
and
gamifies
participation
with
regional
incentives.
By
minimizing
the
human
element,
trust
is
no
longer
a
factor
but
rather
a
variable
within
the
network
that
is
constantly
weighed.
Any
bad
actors
looking
to
inject
false
data
into
the
network
are
easily
identified
as
other
drivers
retrace
mapped
roads
and
confirm
or
reject
preceding
map
contributors.
Those
contributors
that
provide
high-quality
data
to
the
network
maintain
regular
rewards.
Those
that
taint
the
data
pool
are
removed
from
the
network
and
omitted
from
the
reward
cycle.

Yes,
people
will
warp
and
shape
data
to
meet
their
desired
outcomes.
That
isn’t
something
we
can
change
outright.
But
if
we
provide
everyone
with
equal
access
to
fresh,
accurate,
and
affordable
map
data,
we
disrupt
the
monopolies
that
currently
dominate
the
mapping
world.

Certain
map
components
are
objective,
dependent
on
factual
truths.
Things
like
street
names,
road
conditions,
and
sign
locations
are
rarely
the
subject
of
debate.
Starting
with
basic
geospatial
data,
we
can
create
an
honest
foundation
for
maps.

From
there,
users
can
layer
on
additional
data
for
navigation,
points-of-interest,
business
needs,
etc.
Through
a
decentralized
network,
we
can
automate
elements
of
map
freshness
and,
with
open
APIs,
developers
can
continually
innovate
and
create
dynamic
filters.
Then,
the
public
can
access
open
marketplaces
of
maps
and
self-determine
which
maps
best
fit
their
needs.

Note:
The
views
expressed
in
this
column
are
those
of
the
author
and
do
not
necessarily
reflect
those
of
CoinDesk,
Inc.
or
its
owners
and
affiliates.