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Description
Did you know local legislation can significantly impact everything from your job to the environment to your safety? Thankfully, a team of developers created Legit-Info to help individuals understand the legislation that shapes their lives. See how this web-based solution uses IBM Watson® Natural Language Understanding service to analyze, inform, and develop policy to reform the workplace, products, public safety, and more.
A
A
Good
morning,
good
afternoon,
good
evening,
wherever
you're
hailing
from
welcome
to
a
special
edition
of
openshift
tv,
this
is
the
call
for
code
for
racial
justice
miniseries
that
we've
been
doing
lately
today.
We're
talking
about
the
legit
info
project
and
to
kind
of
tell
you
more
about
call
for
code
for
racial
justice
and,
more
specifically,
what
we're
talking
about
today.
I
will
hand
it
off
to
demi
timmy.
How
are
you
today.
B
Yeah,
thank
you
hi
everyone.
My
name
is
demi
ajayi,
I'm
the
open
source
community
manager
here
at
call
for
code
for
racial
justice,
and
today
we
have
with
us
a
few
people
from
our
legit
info
team
and
I'll.
Let
them
introduce
themselves
before
telling
you
guys
a
little
bit
more
about
call
for
code
for
racial
justice.
E
B
Excellent,
thank
you
guys
and
again,
as
I
said,
I
am
the
coffer
coach
for
racial
justice,
open
source
community
manager.
If
you've
been
part
of
this
series,
your
notice
that
I'm
a
guest
here,
usually
we
have
sabine
justileine,
who
is
the
product
manager
for
call
for
code
for
racial
justice
hosting
but
she's
unable
to
join
us
today,
she's
flowing
under
the
weather,
so
we're
hoping
she
gets
better
real
soon.
B
So
again,
this
is
our
third
episode
of
this
series,
the
first
two
episodes
we
had
fair
change
and
open
sentencing
as
part
of
the
series,
and
today
we'll
be
talking
about
legit
info,
but
just
a
little
bit
more
about
what
call
for
code
for
racial
justice
is
essentially
we're
currently
all
ibmers.
So
this
emerged
out
of
an
initiative
that
was
launched
by
ibm,
which
is
the
embrace
initiative,
which
is
a
diversity
and
inclusion
initiative
within
ibm.
That
really
wanted
to.
B
You
know,
do
some
work
to
really
make
some
change
so
as
part
of
that,
we
had
a
call
to
action
where
we
launched
a
spot
challenge
for
call
for
code
within
call
for
code,
which
is
our
tech
for
good
platform.
It's
hosted
by
the
david
clarke
cause
that
has
an
annual
event
every
year
to
support
global
challenges
around
social
issues.
B
So
last
year
we
were
focused
on
for
the
spot
challenge
on
tackling
systemic
racism,
and
the
plan
was
essentially
to
have
different
different
people
within
ibm
and
within
red
hat,
to
contribute
to
open
source
to
building
open
source
technologies.
That
would
address
issues
around
three
different
pillars.
B
They're
now
on
the
linux
foundation,
seven
of
our
solutions,
including
legit
info,
which
we'll
hear
about
more
today,
we're
definitely
looking
forward
to
telling
you
more
about
the
solution
about
and
finding
a
way
for
you
guys
to
get
involved
as
well.
So
now
I
hand
it
over
to
the
team
to
talk
through
more
about
the
solution,
how
they
got
to
where
they
are
today
and
we'll
kind
of
try
to
make
this
conversational.
C
D
Citizens
and
impacted
residents
don't
have
a
straightforward
way
of
knowing
what
or
how
policies
and
legislation
affect
them
or
what
they
can
do
in
response,
and
so,
as
we
kind
of
dug
a
little
bit
deeper
into
that
that
problem
statement,
what
we
really
found
is
that
there's
a
couple
of
you
know
there's
several
issues
here,
but
a
lot
of
it
has
to
do
with
legislation
itself
legislation.
One
is
it's
very
hard
to
find.
D
You
know
you
have
government
websites,
but
they
you
have
to
kind
of
sift
through
their
their
pages,
go
through
different
sessions.
You
really
have
to
know
how
to
navigate
to
find
what
you're
looking
for
there's.
Also,
usually
no
good.
You
know
search
mechanisms
there,
so
you're
really
kind
of
limited
to
to
knowing
specifically
what
you're
looking
for
knowing
what
bill
number
you're
looking
for
to
actually
find
to
find
it
on
their
website.
D
Once
you
find
it,
you
run
into
the
other
problem
of
it's
very
hard
to
understand
right.
The
legislation
is
typically
it's
there's
a
lot
of
legalese
there's
a
lot
of
political
speak
in
there.
So
it's
it's
difficult
for
the
average
person
to
really
understand
what
they're
reading
and
get
to
the
kind
of
the
core
of
what
that
legislation
means
and
then,
in
dealing
with
you
know,
conflict
for
racial
justice.
We
also
found
some
impacts
specifically
towards
people
of
color.
You
can
kind
of
see
the
figure
too
over
here
we
have
on
the
right.
D
D
So
basically,
what
this
means
is
we're
trying
to
make
it
easier
to
access
this
legislation,
bills
that
are
upcoming
bills
that
are
existing
now,
things
that
are
about
to
be
voted
on.
We
want
to
make
it
easily
accessible
and
easily
understandable.
We
want
people
to
be
able
to
find
the
information
that
they're
looking
for
without
having
to
jump
through
a
bunch
of
hoops
to
get
there,
and
so
some
of
the
current
features
that
we
have
it's
an
interactive
website,
both
mobile
and
tablet
compatible.
D
Right
next
chart
all
right,
so
a
really
kind
of
high
level
process
of
how
legit
info
works.
First
and
foremost,
we
have
a
collaborative
effort
going
on
with
legiscan,
so
ledger
scan
if
you're
not
familiar
with.
It
is
another
third
party
website
and
they
do
a
really
great
job
of
manually,
collecting
and
collating.
All
this
information
from
all
these
different
state
and
federal
government
websites,
basically
pulling
all
this
legislation
down
and
putting
it
onto
a
single
pane
of
glass
for
people
to
search
on.
D
So
while
they
do
a
really
great
job
of
consolidating
all
that
information,
they
still
don't
really
classify
the
information
or
make
it
easier
to
find
what
you're
actually
looking
for
they
make
it
easier
to
find
because
it's
all
in
one
place,
but
you
still
kind
of
have
to
know
what
you're
looking
for
to
be
able
to
get
to
it.
And
so,
in
our
collaboration
with
legislation,
we
actually
run
a
batch
process
where
we
access
the
arrest
api.
D
Every
week,
we
download
all
the
the
pertinent
legislation
updates
anything
that's
been
updated
over
the
past
week
in
both
pdf
and
html
format,
kind
of,
depending
on
which
state
is
being
scanned
or
which
state
is
submitting
their
data
they
submitted
in
different
formats.
We
take
all
of
this
information
and
we
pre-process
it
to
extract
the
text
from
those
files,
and
then
we
send
that
text
to
watson,
natural
language,
understanding
that
lets
us
identify
the
key
topics
for
each
of
those
legislative
documents
and
then
from
there.
B
Awesome
so
I
just
had
a
few
questions
here.
This
is
cool.
Obviously
I
know
a
little
bit
about
legit
info,
but
it's
always
great
to
hear
from
the
people
who
developed
it
a
little
bit
more.
Can
you
talk
a
little
bit
about
what
challenges
like
what
was
the
biggest
challenge
in
kind
of
trying
to
pull
this
together
as
a
solution.
C
I'll
start,
one
of
the
big
challenges
was
that
we
had
a
very
short
time
window.
We
were
only
given
six
weeks
wow
to
try
to
develop
a
workable
system
and
anyone
who's
worked
with
artificial
intelligence
knows
that
six
weeks
isn't
even
enough
to
train
models
correctly,
and
we
were
also
struggling
at
that
time
before
we
found
legiscan
finding
source
data
to
work
with.
C
You
can't
train
a
model
unless
you
have
actual
source
data
to
work
with
and
the
first
few
weeks,
I'm
not
not
wasted
but
spent
design.
Thinking
who
would
use
the
tool
and
who
are
we
trying
to
deliver
this
for
and
trying
to
to
interview
people
who
would
use
something
like
this
and
come
up
with
what
are
their
requirements?
C
C
We
aimed
for
having
an
advocate
who
would
use
the
tool
and
then
use
that
to
drive
their
next
steps,
their
next
actions
being
able
to
share
that
information
with
their
followers
and,
along
with
the
information,
say,
here's
how
we
need
to
act.
Here's
what
we
need
to
do
next
and
that's
kind
of
the
the
results
of
our
design.
Thinking,
effort.
B
Interesting,
and
did
you
guys
have
any
like
ethical
considerations
as
you
were
developing
this
any
things
you
thought
about
and
how
you
developed
that
you
kind
of
mentioned
anonymous
search.
Are
there
other
things
that
came
up
through
your
design,
thinking
or
through,
like
actual
implementation
of
this
solution,.
C
That
was
the
that
was
the
main
one.
We
we
added
later
the
ability
to
save
register
as
a
user
and
to
be
able
to
do
additional
functions.
If
you
registered
your
information
and
if
you
are
an
activist
you
know,
one
of
the
things
is
that
you
can
be
an
activist
for
people
or
things
that
can't
vote.
You
know
the
people
for
the
ethical
treatment
of
animals
are
are
representing
animals
that
can't
vote.
C
D
One
of
the
other
things
that
I
thought
was
interesting.
You
know
talking
about
like
ethics
while
going
through
this.
You
know
one
of
the
things
that
we're
trying
to
also
do
with
legit
info
is
to
reduce
bias
in
you
know
how
we're
classifying
some
of
these
things.
You
look
at
a
lot
of
bills
and,
depending
on
the
news
source
you
go
to,
you
know
you
can
get
wildly
different
stories
about
what
the
bill
actually
entails.
You
know
something
as
simple
as
a
grant
for
for
public
education.
D
You
have
one
side,
that's
very
pro,
you
know,
education
is
is
positive.
You
know
pro
for
the
bill,
but
then
another
side,
that's
looking
completely
at
the
financial
aspect
of
it
is
saying
you
know
it's
going
to
increase
your
taxes,
so
you
can
get
positive
and
negative,
and
so
one
of
the
things
that
we're
trying
to
do-
and
while
we
went
more
with
the
machine
learning
approach,
is
it
kind
of
take
away
that
bias
and
just
look
at
what
is
the
core
of
the
bill?
B
Yeah,
that's
a
good
point,
and
actually
that
reminds
me
of
our
other.
Our
other
solution.
Take
two.
You
know
the
one
that's
about
diverse
representation
and
trying
to
identify
that
kind
of
bias,
specifically
racial
bias
in
text.
I'm
wondering
if
there's
actually
possible
synergies
between
your
solution
here
and
maybe
also
like
anything
as
far
as
like
media
articles
yeah.
So
that's
a
great
point
about
natural
language
understanding.
B
C
Sure
the
initial
mvp
minimal
viable
product
we
didn't
have
watson
nou,
so
we
were
hand
curating
all
the
legislation.
We
were
reading,
the
dozens
or
hundreds
of
pages
of
legislation
and
trying
to
summarize
it
into
a
impact
to
say
you
know,
having
read
this
document,
the
impact
is
this
and
so
we
were
hand,
classifying
individual
legislation
and
then
putting
it
in
the
database
and
then
you
could
search
from
that
and
it
was
terribly
manual
I
mean
you
know
it
it's
to
say
the
least.
C
It
wasn't
sustainable
and,
after
the
six
weeks
were
over,
our
team
was
given
the
opportunity
to
enhance
the
tool
to
get
additional
help
from
others
who
were
watson,
nlu,
knowledgeable
to
help
implement
the
nlu
capabilities.
So
currently,
today,
when
we
are
processing
the
pdf
and
html
files,
we
extract
the
wrought
text
and
that
text
is
then
processed
by
nlu.
We
didn't
have
to
train
nlu.
C
It
already
can
read
english
and
understand
english
terminology,
so
that
saved
a
lot
of
training
time
and
what
nlu
does
is,
gives
us
10
phrases
that
it
considered
to
be
the
most
important
phrases
for
this
document.
So
it
could
be
phrases
that
then
reflect
whether
it
is
healthcare
related
or
related
to
safety
or
transportation.
C
E
You
guys
get
content,
go
ahead,
go
ahead.
Oh
I
was
just
gonna.
Add
that
that's
interesting
to
me
that
it's
not
a
classification
exercise.
It's
not
it's
not
like
you're.
Looking
at
a
legislation
and
saying:
does
this
classify
as
healthcare
or
versus
safety
versus
right?
It's
going
the
other
way
around,
so
not
limiting
or
by
the
impacts
that
the
solution
considers
right.
So
so,
in
this
case,
watson
comes
out
with
it.
Does
it
happen,
tony
that
it
comes
comes
up
with
impact
areas
or
words
that
are
not
listed
in
our
impacts.
C
Oh
yeah,
absolutely
in
fact
we
anticipate
that
there's
going
to
be
legislation
that
doesn't
apply
to
the
impact
areas,
we're
interested
in
right.
So,
for
example,
military
spending
well
we're
not
interested
in
military
spending
and
there
could
be
military
spending
bills
and
all
of
the
themes
that
it
comes
up
with
are
military
oriented
and
it
doesn't
match
any
of
our
impact
areas.
So
it
would
be
classified
as
none
as
not
one
of
the
five
impact
areas
we're
interested
in.
So
there
were
quite
a
few
of
those
some
legislation,
for
example,
erected
statues.
C
For
you
know,
famous
people
or
remove
statues
of
famous
people
same
thing
did
not
did
not
classify
as
any
of
the
five
impact
areas
that
we
had.
So
it
gets.
You
know
summarized
as
none
so
absolutely,
rather
than
trying
to
come
up
with
a
traditional
classification
machine
learning
language.
We
thought
this
was
the
better
approach.
It
allows
us
to
add
and
remove
impact
categories
without
having
to
rewrite
or
retrain
the
the
model.
D
D
10
impact
areas
and
80
of
them
have
to
do
with
health
care,
but
then,
for
some
reason
you
have
two
of
them
that
have
to
do
with
finance
or
something
that
that
might
be
a
good
indicator
that
you
actually
have
and
it
dim
them
to
the
bill.
That's
not
really
part
of
the
initial
bill,
but
it's
something
that
you
know
stands
out
exactly.
B
Interesting
all
right,
so
that
brought
up
two
questions.
For
me,
the
first
one
is
related
to
like
the
the
source
of
truth
and
choosing
the
impact
areas
right
like
how.
How
did
you
guys
decide
how
to
what
governs
the
impact
areas
that
you
want
to
show
and
how?
What
might
we
think
about
doing
that
in
the
future?
Right,
for
instance,
maybe
military
spending
we
didn't
think
was
relevant,
but
if
someone
else
in
the
open
source
community
thinks,
like
that's,
actually
relevant,
how
do
you
go
about
deciding
that
so
far
today,
right.
C
C
So
you
can
modify
programmatically
or
not
program
in
the
database.
You
can
list
the
locations
and
the
impact
categories.
So
if
you
want
to
add
and
remove
impact
categories,
we
made
that
very
possible
without
having
to
have
anything
hard
coded
into
the
code,
and
as
a
result
of
that,
you
know,
if
we
interviewed
20
different
people,
we
might
have
had
five
different
impact
categories.
You
know
it
just
happened
to
be.
We
spent
the
first
two
weeks
just
trying
to
discuss
who
who
was
the
advocate
and
what
impacts?
B
Okay,
that's
good
to
know,
I
mean
I
guess
it
definitely
creates
like
a
opportunity
for
thinking
more
about
how
we
want
to
develop
this
further
down
the
line
as
well.
Now.
The
other
question
I
had
was
related
to
legiscan.
Can
you
talk
a
little
bit
more
about
how
you
guys
got
connected
with
them
and
it
seems
to
have
made
your
jobs
a
lot
easier,
but
like?
What
can
you
just
like
give
them
a
bit
more
explanation,
as
so
how
you
you
were
connected
with
them.
C
Yeah,
I
would
say
that
we
had
a
real
struggle
trying
to
figure
out
when
it
was
originally
just
curated
data.
If
we
found
legislation
we
could
curate
it
summarize
it
give
it
a
title.
Give
it
a
summary,
give
it
an
impact
and
a
location
and
put
it
into
the
database
manually,
but
when
we
wanted
to
try
to
get
it
more
formalized
with
repositories,
we
found
that
every
state
has
its
own
different
repository
and
a
different
website
and
different
web
page
and
and
screen
scraping
was
just
not
something
we
wanted
to
do.
C
We
also
didn't
want
to
limit
it
to
united
states
only.
We
could
have
used
this
in
the
uk
or
europe
or
or
developing
countries.
So
you
know
we
were
trying
to
decide.
You
know
a
balance
between
individual
locations.
States,
websites
and
some
more
centralized
repository
and
we
reviewed
quite
a
few
attempts
at
trying
to
consolidate
legislation
and
legiscan.
C
We
chose
because
it
had
a
nice
api.
It
has
both
a
free
and
a
paid
version
and
because
we
worked
out
with
legiscan
how
we
could
implement
this
with
just
a
free
user
id.
So
we
wouldn't
have
to
scan
and
cause
too
much
effort
on
their
servers.
We
didn't
want
to
generate
too
much
cpu
load
against
them
for
the
free
scan.
B
C
C
It
could
be
a
tablet,
it
could
be
a
smartphone
and
we
are
able
to
then
access
the
web
pages
do
our
searches.
We
have
the
option
to
save
csv
files
of
the
results.
We
find
we're
also
able
to
email
the
results
to
ourselves
so
that
we
can
then
forward
it
on
to
our
followers,
but
by
adding
some
additional
comments
to
it.
C
So,
rather
than
emailing
it
directly
to
our
followers
randomly,
we
thought
it'd
be
better,
that
you
email
it
to
yourself,
and
then
you
forward
it
on
to
your
team
to
say:
look
at
the
list
below:
let's
take
action,
let's
meet
saturday
to
discuss
it,
let's
you
know,
etc,
etc.
So
we
thought
that
was
a
better
approach,
based
on
our
conversations
with
activists,
our
data
sources.
C
A
C
So
this
is
that
the
legit
info
screen.
Can
everyone
see
that?
Yes,
so
initially,
you
know
you're
not
signed
in
you're,
just
an
anonymous
person
and
as
an
anonymous
person,
you
can
implement
the
search
and
we
can
hit
the
search
button
and
you
could
do
that
now.
We've
made
it
so
that
it
is
fully
responsive
in
that,
if
you're
on
a
tablet
mode,
it
shrinks
down
correctly.
C
If
you're
on
a
smartphone,
the
menu
on
the
top
gets
changed
to
a
pull-down
menu
and
when
it's
a
wider
screen,
then
the
menu
comes
out
on
cross.
All
of
the
choices
here
work,
regardless
of
the
size
of
your
request
and
as
an
anonymous
search.
You
can
say
I'm
interested
in
you
know,
let's
say
tucson
arizona
and
I'm
interested
in
healthcare,
safety
and
transportation.
So
you
can
check
multiple
impact
areas
and
then,
when
you
do
the
search,
it
would
then
identify
the
search
there,
and
you
can
see
the
title.
C
C
So
we
did
that
you
can
at
any
time
print
the
page
out
or
download
it
as
a
csv
file
and
the
csv
file
is
nice
because
then
you
can
run
it
through
other
reports
or
forward
it
on
to
your
team,
or
you
can
go
back
and
say.
I
want
to
search
something
else.
I
want
to
search
ohio,
so
let's
say
we
go
to
columbus,
ohio
and
now
I'm
interested
in
environment
and
jobs,
and
I
can
now
search
a
different
state,
and
here
again
I
have
the
titles
and
the
summaries
of
the
different
things.
C
I
can
say
that
some
of
these
are
based
on
jobs.
Some
of
these
are
classified
as
an
impact
to
an
environment,
so
you
can
see
that
for
that
so
again
at
the
bottom,
you
can
see
that
there
are
thousands
of
legislations
found
that
you
can
do
this
now,
let's
take
a
quick
look
at
which
impacts
we
have.
These
are
the
five
impacts.
We
have
healthcare,
safety,
environment,
transportation,
jobs
again.
C
That
was
the
result
of
our
design,
thinking
we
needed
to
pick
just
something
that
were
relatively
unique
and
different,
that
we
can
find
legislation
for
and
that's
how
we've
classified
our
legislation.
If
you
look
at
the
locations,
we
have
a
hierarchical
search.
So
in
this
case
all
the
states
relate
to
the
united
states
and
then
counties
relate
to
the
states,
and
then
cities
relate
to
the
counties.
We've
structured
this
so
that
it
can
work
with
all
of
united
states
and
all
of
the
districts
and
and
on
other
countries.
C
C
I
would
find
any
counties
that
were
related
to
franklin
county,
so
it
affects
all
members
of
franklin
county,
including
columbus,
ohio.
I
would
also
look
for
any
statewide
initiatives
for
the
state
of
ohio
and
then
I
would
find
any
federal
legislation
related
to
the
state
of
united
states.
So
when
you
pick
a
location,
it
doesn't
limit
it
to
just
city
ordinances.
C
It
can
actually
find
all
of
the
things
related
to
that
location
at
the
government
hierarchy.
The
way
it's
organized.
So
I
think
that
was
another
key
thing
there.
You
wouldn't
have
to
do
four
searches
I
mean
otherwise.
You'd
have
to
search
columbus
and
then
you'd
have
to
search
franklin
county
and
then
you'd
have
to
search
ohio
and
then
you'd
have
to
search
united
states,
and
we
did
it
all
for
you
on
a
single
search.
B
C
C
C
And
we
can
then
pick
their
location,
we'll
say
that
they
live
in
cleveland,
that
they're
interested
in
cleveland,
and
we
can
save
some
of
their
settings
that
they're
interested
in
these
three
and
we
save
those
changes
and
let's
go
ahead
and
add
all
right.
So
now
we're
logged
in
it
says
hello,
frank
at
the
upper
right
corner.
So
when
I
do
a
search,
I
have
it
all
preloaded.
I
have
it
loaded
with
cleveland
ohio
and
I
have
it,
but
that
doesn't
stop
me
from
doing
other
searches.
C
I
could
say
well,
even
though
I'm
located
in
cleveland
I'm
going
to
search
for
cincinnati,
and
even
though
these
are
my
normal
defaults,
I'm
going
to
add
jobs
and
remove
safety,
and
I
can
still
do
the
search
from
that.
It
just
pre-populates
the
standard
default
for
that.
So
you
can
see
here.
I
have
jobs,
health
care
and
environment
and
again
it
would
be
city
ordinances
for
cincinnati
county
organized
for
the
county.
C
That
cincinnati
is
in
which
is
different
than
the
county,
that
columbus
is
in
and
then
the
state
of
ohio
which
would
affect
everybody
in
ohio
and
then
federal
laws
as
well.
So
that's
you
can
see
very
flexible
way
to
do
it
and
we
designed
it
so
that
advocates
don't
have
to
be
expert
search
ninjas
in
terms
of
trying
to
figure
out
how
to
find
stuff
this.
We
really
try
to
make
it
accessible
and
easy
to
say
these
are
the
impact
areas
I'm
interested
in
these
are
the
locations.
C
This
is
the
communities
of
interest
that
I
that
I,
that
I
want
to
do.
You
can
always
look
at
your
profile
and
if
you
want
to
change
that
profile,
you
can
update
it
to
say.
Okay,
I
want
to
change.
I
I
moved
from
cleveland
ohio
to
cincinnati.
So
now
I
am
less
interested
now
in
safety
and
more
interested
in
transportation,
and
you
can
save
those
changes
and
you
can
now
make
that
possible.
C
We
also
have
the
ability-
and
I
will
sign
out
here,
to
sign
in
as
an
admin,
and
I
already
have
the
user
id
and
password
loaded,
in
which
case
when
you
log
in
as
an
administrator
of
the
application,
you
get
the
admin
button
and
here
in
the
admin
button
you
get
to
actually
see
all
the
database
tables
we
have.
This
allows
you
to
reset
the
passwords
of
individual
users
who
say:
hey.
I
forgot
my
password.
Can
you
reset
it
for
me?
C
C
C
Yeah,
well,
I
would
say,
if
you're
running
the
website
for
a
group
of
activists,
you
would
have
an
I.t
person
who
would
be
in
charge
of
that
you
could.
For
example,
you
know
here's
all
the
locations
if
you
wanted
to
modify
them,
here's
all
the
impacts.
If
you
want
to
add
or
remove
impact
areas,
we
have
tasks
to
do
the
batch
jobs.
C
You
can
schedule
when
those
tasks
run.
For
example,
we
have
our
downloading
the
legiscam
data
sets,
runs
the
next
time,
we'll
be
running
on
the
the
13th
of
of
june
or
or
whenever
the
next
time
is
and
so
on.
You
can
schedule
these
to
run
weekly
monday,
tuesday
wednesday.
However,
you
want
to
do
that
so
yeah,
so
somebody
would
have
to
be
the
administrator
at
least
initially
to
set
it
up.
C
For
you
know,
if
you,
if
you
want
to
set
this
up
for
the
state
of
minnesota,
then
you
would
have
somebody
who
would
make
sure
that
minnesota
was
listed,
that
you'd
have
the
impact
areas
that
you
are
interested
in
and
then
make
it
available
to
the
activists
who
needed
to
do
the
searches
that
they
wanted
to
search,
and
that
would
depend
on
you
know.
Whoever
is
sponsoring
this
or
making
this
available
to
their
communities
to
their
advocates.
B
C
We
have
copies
running
in
the
cloud
just
for
our
own
test
purposes,
but
if
we
wanted
to
deploy
this
somewhere,
it's
open
source
people
can
download
it
onto
their
servers
and
try
it
out
for
themselves,
sign
up
for
a
legit
scan
user
id
sign
up
for
watson,
nlu,
sign
up
for
ibm
cloud,
object,
storage
and
completely
have
a
fully
running
system
with
minimal
effort
all
right.
So
that
is
it
in
a
nutshell.
I
think
I
went
through
my
entire
script,
showing
how
that
all
works,
so
I
will
then
go
back
to.
C
C
C
You
could
use
cron
if
you
were
on
a
local
system
as
well
and
a
web
browser
with
a
single
user,
and
you
can
do
all
of
that
with
curated
content
without
having
to
use
ledger,
scan
or
the
watson
nlu,
and
that
might
get
people
started,
so
they
can
see
how
it
works
and
validate
things
and
then,
in
the
transition
phase,
we're
able
to
move
the
local
file
system,
which
contains
all
the
pdf
and
html
of
the
legislation
we've
downloaded
into
either
a
network
attached,
storage,
nas
or
we're
using
ibm
cloud
object.
Storage.
We
can.
C
We
can
support
either
of
those
and
instead
of
just
sqlite3
we're
using
a
more
robust
database
called
postgresql
that
we
have
running
in
the
cloud.
So
it's
a
centralized
repository
and
now
what's
on
premise,
is
just
the
application,
we're
switching
from
the
run
server
to
a
more
formal,
unicorn
and
continuing
with
the
queue
cluster,
but
this
now
with
unicorn
allows
us
to
have
multiple
users.
C
In
this
case,
you
could
have
a
browser
tablet
and
mobile
phones
accessing
the
application
to
make
sure
that
everything
looks
responsive
and
is
spaced
and
positioned
correctly
and
then
once
you're
finally
ready
to
run
in
production
here.
What
we
do
is
we
move
the
application,
the
unicorn
and
the
batch
processing
with
the
q
cluster
in
the
cloud,
and
so
the
only
thing
you
have
locally
would
be
your
browser,
your
tablet
or
your
mobile
phone,
and
so
this
transition
really
helped
getting
people
on
board.
C
People
could
download
the
code
and
do
the
development
and
testing
locally
get
familiar
with
it
without
affecting
anybody
and
then
getting
into
transition
mode
learning,
postgresql,
learning
cloud
object,
storage,
learning,
the
watson,
nlu
algorithms,
and
keeping
the
application
itself
running.
On
premise,
so
you
can
still
debug
it
stop
and
and
trace
activity
there
and
then,
once
you
are
ready
to
move
all
of
that
into
the
cloud
for
production
you're
in
a
much
better
position.
E
E
E
Gotcha,
okay,
so
but
the
link's
right
on
top.
That's
that's
the
first
thing.
So
if
you
want
to
try
it
out
on
your
own
later
on
bill
chris,
if
you
don't
mind
sharing
that
link,
I
already
did
in
the
chat
yeah.
Thank
you
all
right.
So
when
you
land
on
this
page,
there's
a
button
to
log
into
the
lab
environment
and
you
have
a
couple
of
different
choices
or
options
here
to
log
in,
I
have
an
ipm
id.
So
if
you
I
use
that
a
lot
of
folks
use
github.
E
There
is
no
cost
to
the
lab,
it's
self-faced,
it's
self-paced
and
the
next
screenshots
they'll
show
you
it's
a
very
sort
of
guided
concept.
So
thank
you.
So
you
can
see
this
is
the
lab
environment
works
in
the
browser?
That's
all
you
need
to
to
start
it.
On
the
left
hand,
side
we
have
the
different
steps
that
you
can.
E
You
will
go
through
if
you,
if
you
do
the
lab
and
on
the
right
side,
we
have
a
editor,
looks
very
much
like
vs
code,
and
so
you
can,
if
you're
familiar
with
that,
you
know
you
can
open
the
terminal.
You
can
click
on
the
the
little
files
thing
to
see
all
of
the
files
that
are
in
this
lab
and
then
at
the
end
of
the
lab.
C
E
Nice,
that's
correct,
so
it's
a
it's
a
like
it's
a
it's,
a
lab
environment
that
has
python
already
installed
the
steps
go
through
installing
some
of
the
other
dependencies
that
the
lab
needs
of
the
solution
is
built
on,
for
example,
django
right
and
then
it
it
has
a
couple
of
other
utilities.
So,
for
example,
ibm
cloud
cli
there
is
a
portion
in
the
lab
that
has
have.
E
Has
you
deploy
this
application
on
ibm
cloud
under
your
own
account
as
a
cloud
foundry
application,
and
so
that
ibm
cloud
cli
is
also
in
there
so
yeah?
It's
the
the
reason
for
doing
it.
This
way
was
you
know,
versus
the
other.
The
other
route
you
can
take,
of
course,
is
go
through
the
readme
file
and
do
it
locally
on
your
system.
But
then
you
have
to
install
those
different
things.
So
all
of
that
is
given.
E
It
would
be
the
same
steps,
correct
yeah,
so
if
we
go
one
more
there
we
go
and
then
this
is
the
other
thing
we
we
try
to
make
it
easier
for
our
users
right.
So
I
think
jimmy
mentioned
part
of
this
is
you
know,
you're
interested
in
in
helping
out
with
this
with
this
project,
but
also
you
might
want
to
learn
more
right.
E
E
So
it's
a
good
learning
opportunity
as
well,
so
to
make
that
a
little
bit
easier,
the
instructions
we
kept
them
short
on
the
left
hand,
side,
there's
the
next
and
previous
or
previous,
and
continue
button
that
you
can
use
to
move
back
and
forth
between
the
instructions
and
then
any
command
that
we
want
you
to
type
there's
a
handy
copy
button.
So
you
click
on
that
copy
button
and
then
you
can
paste
it
in
the
terminal
which
is
shown
on
the
next
slide.
E
C
A
C
C
E
I
have
the
lab
open
here
by
the
way,
thanks
to
tony
I'm,
I've
been
using
linux
for
like
what
five
months
now
I
thought
tony
using
it,
it
looked
pretty
cool,
so
I'm
like
okay,
I'm
gonna
go
full
time.
I
haven't
opened
my
macbook
for
for
a
bit
now
nice
and
it's
been
it's
been
great,
all
right,
so
here's
the
lab.
Actually,
let
me
open
the
other
window
just
like.
C
That
I
should
mention
that
we've
designed
this
tool,
while
you're
doing
that
that
the
python
and
django
can
run
natively
on
linux,
windows
or
mac.
The
way
it's
structured
so
that
I
know
all
the
instructions
are
based
on
linux.
But
don't
let
that
scare
you
it
can
be
implemented
on
windows
or
mac
as
well,
fully
supported.
So
if
you
have
a
windows,
machine
or
a
mac
machine,
you
want
to
download
the
code
and
run
it
locally
with
your
own
local
python,
compiler
and
your
own.
E
Cool
all
right,
of
course,
I'm
super
secure
this
way,
so
I'm
going
to
switch
to
the
other
window
where
I'm
already
signed
in
instead
of
pulling
up
my
phone
and
the
authentication
app
and
all
of
that
so
I'm
already
signed
in
here.
So
let
me
do
another
access,
quick
lab.
This
should
open
the
environment.
E
We
do
say
this
lab
takes
120
minutes
to
complete,
but
we
noticed
you
can
get
through
it
a
lot
faster
as
well.
That
120
minutes
is,
you
know
if,
if
you
want
to
learn
more
about
the
different
components
and
the
technologies
used,
so
you
know
you
might
do
step
one.
Then
you,
google,
a
bunch
of
stuff
to
learn
more
and
come
back,
but
yeah,
I
think
maybe
20
to
30
minutes
is,
is
generally
good
to
go
through
the
lab
good
enough.
D
E
E
So
get
version
I
copy
it
here
and
I
can
paste
it
here
and
enter
boom.
I
have
git
installed,
which
is
nice
oops.
Let
me
go
back
one
one
more
and
let's
see
if
I
have
python
here
and
I
do
have
python
3.6.9
that
comes
with
the
environment
and
then
we
are
using
piping
v
to
create
a
virtual
environment
and
manage
all
of
our
packages
in
that
virtual
environment.
E
So
if
you
go
one
more
step-
and
this
is
probably
the
last
thing-
I
want
to
show
you
so
cd
into
home
project
and
then
git
clone
the
actual
code,
the
legit
info
code.
So
as
soon
as
I
do
that,
let
that
finish,
you'll
see
if
I
now
open
the
browser
or
the
file
browser
in
vs
code
here
are
once
that
finishes.
E
Here
are
all
my
files
that
come
with
the
git
clone
right
and
again,
you
can
read
through
tony
and
team
and
tommy
did
a
wonderful
job
documenting
all
of
this
in
the
different
readmes
that
are
in
the
repo.
So
take
your
time
go
through
that
I'm
gonna
go
into
legit
info
and
then
create
my
virtual
environment
with
pepe
and
v
shell,
and
we
also
right
in
here.
We
did
try
and
describe,
or
put
a
little
bit
more
writing
on
what
these
different
things
are
right,
so
pippy
and
v.
E
What
is
it
doing?
Pippi
and
the
install
and
then
the
one
thing
I
do
love
that
tony
did
here
was
using
all
these
scripts.
So
you
can
see
here
this.
This
command
is
calling
the
stage
one
script
and
passing
in
an
argument,
and
you
can
go
in
here
into
the
files
and
look
at
stage
one.
So
you
can
just
open
that
and
see
what's
happening
there
right.
So
it's
really
it's
it's
very
open,
transparent
and
again.
I
thought
this
was
a
great
way
to
learn.
E
So
once
you
have
followed
all
the
directions
you
use,
this
launch
application
button
on
top
give
it
a
port-
and
basically
you
see
this
so
you'll
see
the
legit
info
solution
that
tony
was
demoing
before
and
then
the
next
couple
of
sections
explore.
The
application
goes
to
the
different
panels.
The
different
admin
things
you
can
do
exploring
different
different
parts
of
the
solution.
E
So
that's
this
this
whole
step
and
then
we
also
have,
as
I
mentioned
before,
we
have
a
step
to
run
this
application
as
a
cloud
foundry
application
in
ibm
cloud
again
using
sqlite3
we're
not
hooking
into
postgres
at
this
point,
but
the
steps
go
through,
deploying
the
application
on
ibm
cloud
and
then
finally,
we
have
some
challenges.
So
one
of
the
challenges,
for
example,
is
update.
The
location
so
add
a
new
location.
What
does
that
look
like?
There
are
other
challenges
at
the
bottom
as
well
update
and
impact,
that's
another
one.
E
E
You
know,
apart
from
the
education
bit,
you
know,
learning
about
these
different
things
is
also
hopefully
at
the
end
of
what
is
this
step
nine
of
ten,
I
think
step
nine
yeah
yeah,
step
nine,
so
hopefully,
by
the
end
of
it
right,
you
are
at
a
place
where,
if
you
wanted
to
contribute
back
into
the
solution,
you
understand
the
different
components
and
the
technologies
that
are
being
used
and
it
makes
it
easier
for
you
hopefully
to
contribute
back.
That's
it
the
next
steps,
then
you
know
once
you've
done
this
again.
E
If
you
want
to
join
the
community
call
for
good
for
reach
this
community,
you
can
do
so
by
going
here,
but
I
also
know
demi
has
a
slide
on
that
and
then,
if
you
want
to
see
what
the
team
is
working
on
the
different
issues
that
you
can
pick
up,
then
you
can
go
to
this
issue
section
of
the
repo
right.
So
let
me
bring
that
up
real
quick.
E
So
a
lot
of
these
you
know
the
team
has
been
working
on.
We
also
have
quite
a
few
of
these
are
actually
feature
requests
and
not
bugs
so
and
and
properly
labeled
as
enhancements
and
then
tony's
gone
through,
and
we
have
marked
quite
a
few
of
these
as
help
wanted
or
good
first
issue
for
folks
who
are
new
to
open
source
to
come
to
contribute
back.
E
B
All
right
so
ukar
has
done
a
great
job,
walking
us
through
the
lab,
and
thank
you
tony
and
tommy
as
well,
for
getting
us
through
what
legit
info
is.
I
also
learned
a
little
bit
through
this
and
I
have
like
a
lot
of
ideas
as
well.
You
guys
have
done
such
a
great
job
with
this
and
there's
a
lot
more
that
we
can
do.
I
just
see
so
many
possibilities
where
we
can
take
this.
So
we
want
people
to
join
us
in
this
effort.
B
So
if
you're
interested
in
learning
more
about
legit
info
or
call
for
code
for
racial
justice
in
general,
you
can
follow
along
with
the
link.
It
should
be
in
the
chat.
It's
also
on
the
screen.
Here,
you
can
use
your
phone
to
scan
the
qr
code
and
that
will
basically
give
you
access
to
our
slack
community.
B
First,
you
will
register
on
through
our
ibm
cloud
platform
and
then
from
there
you
get
information
about
opting
into
the
slack
community
and
then
you'll
be
joining
the
racial
justice
general
channel
and
then
we'll
get
you
plugged
into
our
solution.
So
we
are
looking
for
all
sorts
of
skills,
whether
you're
technical
or
not.
As
you
heard
today,
we
are
interested
in
more
like
design
thinking
around
these
things.
If
you're
a
policy
expert,
you
can
also
lend
your
voice
that
way.
B
A
A
A
C
Actually,
it's
all
automated
now,
so
we
take
the
pdf
file,
we
extract
the
text
and
we
run
it
through
the
tool
and
occasionally
it'll
spit
out
a
phrase
that
we're
didn't
see
before.
We
need
to
add
it
to
a
little
list.
So
we
have
a
list
of
phrases
we've
seen
and
what
impact
we
would
associate
that
with
okay
and
other
than
that,
we're
seeing
about
the
same
3000
phrases.
So
we
are
able
to
classify
them
correctly.
C
Of
course,
if
we
add
a
new
state,
a
new
phrase
might
pop
up
that
we
never
saw
before
we'd
have
to
make
some
updates.
But
we
have
it's
a
it's
a
table
that
anyone
can
edit
a
csv
file.
That
says
for
this
phrase,
you
know,
consider
it
to
be
part
of
this
impact
and
that's
what
we
used
to
to
standardize
it
and
we
had
to
standardize
it
because
we
can't
process
3,
000
phrases
right.