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From YouTube: OPEN DATA - POLICE DASHBOARD VIDEO LAUNCH
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A
Alright,
let's
get
started.
Thank
you,
everybody
for
coming
out
to
sort
of
the
formal
launch
of
the
police
dashboard
we
have
had
it
live
for
a
little
bit
and
we've
got
something
that
off
that,
but
this
is
kind
of
like
the
first
look
is
almost
like
the
grand
opening
of
the
dashboard.
So
we
appreciate
you
coming
out
again,
like
I
said:
she's
cook
wanted
to
be
here.
You
couldn't
be
here
he
apologizes
for
not
being
here.
First,
let
me
introduce
myself.
A
My
name
is
commander
Ryan
woo
I'm,
the
executive
officer
for
the
police
department
and
I
want
introduce
a
couple
other
people
Hillary
Giada
from
the
information
technology
division.
She
is
the
technology
brains,
the
table
to
put
kind
of
brief
focus
to
the
dashboard
and
make
it
what
it
is
and
then
to
her
right
is
Sarah
Jones
records,
bureau
manager
and
records.
The
records
group
has
a
big
big
part
of
trying
to
craft
a
desk
or
cassettes
where
all
our
information,
another
person.
That
is
not
here-
that
I
would
like
to
recognize
his
Michelle
Smith.
A
What
do
you?
What
do
you
think?
Maybe
this
works
better
versus
that
putting
a
lot
information
individualization
could
be
a
little
challenging.
What
we
may
think
looks
good
or
make
sense.
Intuitive
may
not
be
what
the
reader
says.
So
she
had
an
important
function
there
with
helping
us
make
some
these
visualizations,
as
real
as
it
could
be.
I
want
to
start
off
a
little
background
on
the
dashboard
at
what
we
see
for
the
future
the
dashboard.
This
is
over
a
year-long
cooperative
effort
between
the
police
department
and
the
city's
information
technology
division.
A
Our
goal
was
to
put
out
information
that
was
as
reliable
and
as
valid
as
it
could
be.
Within
the
limits
of
the
information
that
technology
we
came
to
make
the
visualization
as
intuitive
as
possible
and
again
looking
for
the
dashboard
will
evolve
and
improve,
is
available
technology
formation
come
forward,
and
this
we
learned
lessons.
We
learn
as
a
department
lessons
for
the
dashboard
and
as
we
get
feedback
from
the
community,
so.
A
A
B
A
Increased
transparency
we
also
as
to
increase
awareness
of
the
department's
activities
and
operations
and
kind
of
the
details
that
go
into
that.
What's
the
police
department
doing
what
are
they
handling?
Were
they
coming
in
contact
with
it's
also
a
tool
to
increasing
engagement?
We
want
this
to
be
some
visually
appealing
enough
and
have
information
that
people
are
legitimately
interested
in
that
they're
going
to
visit
this
dashboard,
not
once,
but
maybe
several
times
or
throughout
the
year.
A
C
A
It's
not
an
extensive
breakdown
statistics,
so
you
may
may
read
something
on
there.
You
may
have
a
question
you
may
need
to
follow
up
words
and
that's
perfectly
fine.
We
understand
and
that's
going
to
be
part
of
it,
especially
depending
on
what
what
your
goal
is
when
you
go
there,
if
your
goal
is
a
general
awareness
of
what
is
the
Police
Department
doing,
you
might
be
able
to
go,
there
go
okay,
well,
I'm
good
with
it,
and
somebody
might
go
well.
You
know
with
this.
A
A
B
B
A
Police
say:
Timothy
captures
all
police
activities
and
actions
by
all
members
of
the
police
department.
It's
not
just
patrol
its
detectives
and
it's
all
activities
anywhere
from
a
park
to
complaint
to
a
directed
area
of
patrol
where
an
officer
might
go.
We've
had
some
issues
here
with
a
nuisance.
I'm
gonna
go
park
here,
sign
off
up
into
theft,
arrests
for
violent
crime.
A
A
Means
less
activity,
the
Fourth
Ward
includes
the
police
department
and
because
of
that,
the
fourth
words
numbers
are
going
to
be
a
will,
a
little
skewed
because
there's
a
lot
of
activity.
That's
code,
that's
that's!
Basically
a
is
the
police
department,
a
report
might
be
generated,
people
might
come
in
to
the
front
desk
plus
to
the
downtown
area
itself.
Just
generates
the
police
activity.
So
the
fourth
floor
is
going
to
be
darker.
D
A
A
So
if
we
scroll
down
this
is
our
math.
What's
that,
let's
we
got
the
time
freeze
last
year
so
365
days.
So
now
we
still,
we
have
over
a
hundred
nature,
calls
hundred
activity
codes
and
we
put
together
visualization
for
the
top
ten
police
activities
by
type
and
this
would
this
would
be
a
directed
area
of
control.
Traffic
stop
follow
up,
which
would
largely
be
work
done
by
detectives,
maybe
signing
off
to
speak
to
a
witness.
I,
don't
have
to
do
a
canvass
of
an
area
where
earlier
took
place.
A
A
So
we're
going
to
the
next
data
set,
which
is
arrest,
field,
contacts,
victims
and
offenders.
So
here
we
have
a
map
of
where
our
us
take
place.
It's
the
last
365
days,
the
dots
either
you
know,
Dyson
made
an
arrest
or
multiple
arrests
at
location.
If
you
were
to
hover
over
that
diamond,
will
kind
of
tell
you
how
many
arrests
were
there
again.
A
Of
the
4th
ward,
the
downtown
area,
but
again
the
rest
who
occur
to
the
police
department,
police
departments
in
the
4th
Ward
for
1454
all
the
way.
So
there's
going
to
be
an
elevated
amount
of
arrests,
I
think
some
of
some
of
the
locations
that
the
police
department
have
40
46
arrests
there
and
it
may
look
like
there's
a
lot
going
on
there,
but
actually
that's
just
the
police
department.
D
A
A
A
Forty
fifty
one,
forty
nine,
but
it's
about
50/50,
and
they
said
this
is
the
last
twenty
five
months.
If
you
were
to
like,
let's
say
because
you
can
change.
If
you
go
to
this
website,
you
can
change
your
visualizations
yourself.
If
you
already
know
like
well
give
me
the
last
two
years.
One
limitation
here
in
the
last
two
years
will
start
to
draw
it
out
of
the
2017
numbers
and
I'll
look
like
less
happen
at
2017
as
compared
to
80.
A
A
The
pat-downs
field
contact
pat-downs
categorized
by
race
in
the
years
past,
the
chief
of
police
or
chief
Addington
would
once
a
year
go
and
talk
about
our
pat
downs,
our
staffs,
who
we
were
paying
down
coming
in
contact
with
that
was
fun
once
a
year
in
the
council.
This
is
doing
it
in
a
way
that
we
think
that
it's
basic
that's
updating
consistently
and
that
people
can
go
to
and
see
what's
happening
instead
of
having
that
company
information
come
out.
What
see
here.
D
A
Explanation
there
would
be
that
we're
not
we
have
a,
we
don't
were
missing
something
to
2019.
That
still
needs
to
update,
and
that's
why
going
25
months
so
this
morning,
I
wanted
wanted
to
have
visualizations
that
looked
accurate,
valid,
reliable
I
went
29
months
with
24
months.
I
went
a
little
bit
longer
than
25
months,
at
least
when
I
was
doing
it.
It
was
still
picking
up
some
of
the
last
year
or
of
the
year
of
2016.
A
So
for
what
we
do,
when
we
categorize
race
for
traffic
stops
under
us,
we
do
it
by
an
Sara's
here.
Cheating
she's
feel
free
to
correct
it.
Jump
in
and
correct
me
if
I
say
something
incorrect
and
that
if
we
categorized
race,
basically
under
two
different
sets,
the
one
is
what
the
state
requires
us,
how
to
categorize
race
and
then
how
we
do
by
traffic
styles.
The
big
difference
there
is
traffic
stops
will
want
us
to
come,
people
that
are
Hispanic.
A
At
these
numbers,
it
looks
like
Hispanics
are
really
really
underrepresented,
but
the
way
that
we're
supposed
to
categorize
race
and
record
it
for
a
lot
of
these
numbers
is
not
supposed
to
be
Hispanic
at
all.
I
would
say
that
that's
probably
a
limitation
for
what
the
public
would
want
to
see
it's
something
we
might
look
to
work
on
in
the
future,
but
right
now
with
how
we
record
data
and
the
information
about
the
technology
available,
this
is
what
we
have.
This
is.
This
is
how
the
visualization
comes
out.
A
So
for
pat-downs
in
2017,
the
percentages
out
there
I
kind
of
broke
the
percentages
now
2%
of
pat-downs
were
people
that
were
age
/
people
that
were
categorized
as
my
Asian
quietly
70%
we're
people
that
are
categorized
as
black
or
african-american
1%
that
were
disbanded,
but
we
Hispanics
should
not
be
in
this
data
set
anyway.
So
we
have
like
one
field
contact
card
there.
So
it's
less
than
1%.
A
A
That's
pretty
much
how
the
data
will
track
year
over
year.
It
does
move
around
a
little
bit,
but
that's
kind
of
the
ratio,
how
it
breaks
down
for
2018,
its
272,
1
124
and
then
for
2019,
which
our
numbers
are
smaller.
It
is
70%
black
26
percent,
white
and
4
percent
everywhere
else.
So
if
it
tracks
around
that
area,
those.
B
A
Passed
out
victims
by
race
and
Evanston
so
before
we
go
further,
I
want
to
bring
your
attention
to
know
value,
and
this
might
be
something
that
we
change
relatively
soon,
the
no
value
when
it
comes
to
victims.
There
was
concern
like
well.
How
is
this
no
value?
What's
going
in
there
like?
What?
Why
is
there?
No
value
and
the
explanation
for
no
value
is
businesses
can
be
victims
and
businesses
don't
have
arrays
there.
B
A
A
A
A
D
A
C
A
I
guess
Sarajevo:
if
we
talk
about
unknown
unknowns,
a
little
bit
easier,
explain
that
whoa,
it's
just
completely
unknown
the
offender's
completely
know.
We
haven't
know
that.
Why
is
there
a
no
value,
no
value
we
think
comes
from
that
comes
from
when
you
have
a
partial
description
like
what
the
person?
What
we
believe
was
a
a
male
okay?
Well,
what
was
it
right?
We
don't
know,
so
that's
not
it.
So
we
have
some
type
of
description
of
our
fender.
What
we're
missing
the
race
behind.
A
B
A
So
what's
going
to
get
percentages
and
we
go
back
to
last
twenty
eight
months
so
of
our
traffic
stops
categorized
by
race,
approximately
60%
of
60%,
of
who
we're
stopping
is
white
31%,
our
black
or
african-american,
the
smaller
percentage
of
Asian
Hispanic.
We
have
a
no
value
unknown
or
other.
What
was
their
explanation
for
in
this,
the
no
value
unknown
or
other.
We
have.
C
C
C
A
Would
do
traffic
stops
under
these
food
court
under
these
parameters?
White,
a
Caucasian
black
or
african-american
American
Indian,
/,
Native,
American,
Hispanic,
Asian,
Native,
Hawaiian
or
Pacific
Islanders?
Those
are
so
in
here.
There
is
a
Hispanic
component.
We
think
that
in
our
traffic
stop
data
because
we
have
we
have
to
report,
we.
A
For
some
incidences
and
this
Lord
would
record
Hispanic
that
we
think
we're
losing.
Probably
then
Hispanic
numbers
being
underrepresented
in
this,
and
that
would
be
a
follow
on
training
issue
for
us
to
take
care
of
and
then
train
our
officers.
I
always
say
that's
probably
right
now,
one
of
the
biggest
I
would
say
something.
That's
been
revealed
us
working
on
this
as
a
training
issue.
We
need
to
go
back
and
retrain
people
how
to
record
towards
the
categorized
race
on
reports
versus
traffic
stops.
A
A
A
A
A
This
approximate
breakdown
following
our
citations,
that
we
write
it's
5%,
Asian,
26%,
black
or
african-american,
1
percent,
Hispanic,
a
4%
unknown,
a
57%,
white
or
Caucasian,
and
then
8%
no
value
and
the
no
value
appears
to
come
from
either
handwritten
tickets
or
see
tickets.
Where
race
is
not
that
put
in
there,
it
should.
A
Yeah
I
mean
like
you
could
be
anywhere
from
a
speeding
ticket
rolling
a
stop
sign,
no
insurance,
only
weapon
if
it.
If
there
was
a
see
ticket
issue,
we
would
not
issues
like
if
somebody's
probably
hand
go
and
I
did.
She
would
see
ticket,
but
there
might
be
some
minor
cannabis
arrests.
We
issue
a
see
ticket
for
dogs
off
the
dishes.
The.
D
D
A
A
Are
taking
we're
taking
some
of
these
cues
for
design?
How
we're
crafting
it?
Based
on
the
feedback
to
the
concerns
we
got
from
the
community?
And
it's
not
to
say
that
in
the
future,
like
age
would
not
be
a
component
or
something
we
could
categorize
fathe?
What
race
and
the
race
of
the
people
that
were
coming?
The
police
department
coming
in
contact
with
arrests
of
patents
have
been
clearly
communicated
us
as
a
concern
for
the
community
and
something
that
they
want
to
see
in
information
is
available
and
moving
that
information
for
me
once
a
year.
A
Presentation
that
the
chief
we're
doing
a
city
council
to
kind
of
having
it
or
that
kind
of
to
having
it
available
pretty
much.
Whenever
people
want
to
look
at
it
and
have
it
reasonably
updated
current
that
once
a
year,
but
as
much
as
our
system
is
updating
is
one
of
the
things
in
line.
These
datasets
will
update
very
frequently
having.
A
A
Here,
when
cicerone
the
record
row
manager
says
the
state
collects
this
information
by
rate
and
it's
not
to
say
that
maybe
number
well,
we
couldn't
do
something
pi
age,
but
this
this
is
my
rate.
This
is
my
race.
That's
how
the
state
wants
us
to
collect
it.
So
a
lot
of
them.
We
don't
make
a
whole
lot
of
unilateral
decisions
of
how
we
keep
records.
It's
pretty
well
regulated
and
governed
by
whether
it's
the
FBI,
the
state
in
various
entities.
In
this
day,
one
of
either
comes
to
traffic
stops
for
us.
How
we're
doing
so!
A
Yeah
and
each
is
an
important
component
when
you're,
when
you're
like
I'm,
not
going
to
be
to
say
that
it's
not
there,
it's
not
important.
It
is
important.
Maybe
this
could
be
important.
It's
important
thing
to
know
just
what
we
have
with
our
limitations,
we're
trying
to
visualize
right
now,
right
now
with
the
dashboard,
maybe
the
future.
We
can
have
that,
but
just
right
now.
This
is
what
we're
anything
yeah,
but
no
you're
right
age,
especially
when
it
comes
to
youth
and
who
the
police
are
coming
in
contact
with,
is
an
important
problem.
D
A
A
We
we
I
want
to
say
struggle,
but
we
we
find
initially
the
best
information
to
get
was
going
to
be
what
are
the
top
10
intersections
in
Evanston.
They
have
the
most
crashes
and
there's
a
couple
of
things
that
came
up
with
that
that
proving
problematic
one
is
with
the
issue
of
validity.
What
is
it
with
the
issue
with
technology
and
what
is
the
way
we
record
the
way
the
police
reports
are
written
for
traffic
accidents.
It
doesn't
necessarily
lend
itself
to
intersections.
A
Was
number
two
ever
sit
was
number
three
and
also
when
you're
looking
at
intersections,
it's
like
well
is
an
intersection
that
has
100
thousand
cars
going
through
the
going
through
a
year
or
a
week
or
whatever
it
is
versus.
Maybe
an
intersection
has
less
cars,
but
a
higher
percentage
of
access,
and
that's
something
we're
not
going
to
capture.
Let's
basically
do
a
traffic
study
on
every
intersection
in
Edison,
so
we
thought
we.
We
came
to
the
conclusion
that
a
reliable,
valid
and
useful
thing
to
presume
anything,
a
traffic
crisis
was
a
contributing
factor
or
circumstance.
A
C
A
This
one
is
for:
why
do
we
have
a
unable
to
determine
dynamic?
Why
is
that
up
there
as
far
as
a
cause
and
one
is
hit-and-runs
to
come
back
and
you
find
your
car
hit,
you
make
the
report,
you
know
what
the
trimming
factor
was,
what
the
offender
did
they're,
not
there.
We
have
an
incomplete
picture.
We
have
to
get
on
the
other.
One
has
dust
reports
that
don't
capture
the
information
as
far
as
like
we
had
an
accident
and
that's
kind
of
that's
kind
of
the
end
of
it.
So.
A
A
A
B
A
We'll
come
back
to
that
rifle
37,
shotgun,
31,
930,
toy
BB,
gun
replica
started
anything
it's
good
for
the
moment
to
have
an
awareness
that
we
do
come
in
contact
with
people,
offenders
subjects
on
the
street.
There
are
10
that
are
carrying
guns
that
are
not
real,
but
look
very
real.
We
do
have
people
that
do
commit
crimes
with
with
guns
that
are
not
real
thing.
Yet
in
that
figure
our
box
cutter
BB
gun,
so
we
go
back
to
other
weapon,
so
a
yellow
weapon.
So
what
is
another
weapon?
B
A
A
In
complaints,
this
is
kind
of
this
is
relatively
self-explanatory.
Commendations
is
a
number
of
compliments
or
commendations.
We
get
from
the
public
or
other
agencies
about
officer's
conduct
and
the
complaints
is
going
to
be
the
number
of
Department
inquiries
or
complaint
registered
numbers
that
we
have
generated
based
on
citizen.
B
A
B
A
A
In
so
we
come
over
taser,
that's
for
non-intact
4,
8,
11
13,
so
we've
had
10
use
of
force.
We
have
13
types
of
use
of
force
used
so
far
this
year,
and
why
would
you
have?
Why
would
the
number
of
13
be
greater,
then
and
I
mean
the
answer?
There
is
if
an
officer
has
to
use
the
force
every
every
every.
A
Recorded
and
there
may
be
a
use
of
force
incident,
but
within
that
incident
there
may
be
more
than
one
type
of
force
use.
So
if
an
officer
is
in
a
fight
with
somebody
and
they
initially
strike
them
with
their
fists,
that
would
be
recorded
as
a
weapon,
less
impact
and
if
they
move
towards
a
taser
and
then
we
record
the
taser
deployment,
it's
one
incident
with
two
types
of
force
used
within
that
incident
and
that's
why
they
know
that.
C
A
This
is
not
an
automatic
feed.
This
is
something
speaking
of
dinner
manually.
So
if
a
member
of
the
press
wanted
to
do
something
with
this,
I
would
highly
recommend.
They
call
me
and
make
sure
that
that's
current,
because
it
would,
this
will
probably
be
a
once
a
month
update.
So
if
you're
getting
later
in
the
month,
you.
A
A
E
A
Have
some
immediate
adjustments
that
we're
gonna
make,
but
then
we're
gonna
kind
of
let
it
run
for
a
while
as
long
as
nothing
is
inaccurate
and
as
far
as
style
of
style
and
how
it's
crafted
and
how
its
presented
we're
gonna
want
to,
let
it
run
for
a
while
get
feedback,
see
what
our
feedback
tells
us
and
then
make
adjustments
accordingly
down.
We
don't
want
to
get
like
two
to
P.
You
know
two.
A
A
It's
a
signet,
you
know
we
want
to
let
it
run
for
a
while.
It
doesn't
mean
that
we
want.
You
know
that
if
there's
something
you
can
accurate
or
something
we
can
kind
of
go
in
there
and
change.
That's
like
whoa,
that's
pretty
op!
That's
pretty!
Obviously
something
needs
to
be.
That's
not
that's
an
objective
issue
versus
like
a
subjective
style
style
point.
We.
A
A
E
B
A
A
Tell
you
what
state
was
it,
but
not
exactly
so,
I
think
with
the
plans,
one
of
us
well.
This
is
what
this
this
this
departments
doing
and
then
we
could
go,
look
at
it
and
see
what
well.
We
would
like
to
do
that
and
we
can
do
that
within
our
limits
of
technology,
but
they
might
be
doing
something
else
that
we
don't
have
available.
A
B
A
Statistical
sample
in
year-over-year
comparison,
so
you
know
we're
talking
about
what
we're
stopping,
how
many
pat-downs
tribes
of
traffic
stops.
Those
are
pretty
big,
those
are
bigger
numbers,
so
I
think
we
can
look
at
that
and
maybe
you
know,
come
up
with
a
couple,
but
why
is
this
happening?
Why
is
this
change
mom,
with
a
couple
likely
reasons
circulating.
A
A
A
A
A
A
C
E
A
For
us,
it
was
like
what
we
thought
would
be
a
good
way
to
visualize
data.
We
just
realized,
it
wasn't
gonna
work
and
sometimes
we
had
to
either
keep
it
simpler
or
just
almost
take
it
like
the
use
of
forest,
and
then
we
use
we
try
to
do
some
other
wood
that
we
thought
was
I
want
to
say
clever,
but
maybe
we
try
to
do
other
things
and
then
we
just
it
just
was
like
the
way
we
need
to
present.
This
data
is
the
way
that
we
record
and
that's
the
most
reliable
on
that.