►
Description
A virtual meetup hosted by Hyperledger Dallas on June 22, 2021 featuring a discussion about openIDL. The open Insurance Data Link is an open blockchain network that streamlines insurance regulatory reporting while providing new insights for insurers, and enhancing timeliness, accuracy, and value for regulators. openIDL is the first open blockchain platform to enable the efficient, secure, and permissioned-based collection and sharing of statistical data. This presentation will include an overview of the business case, a demonstration of the platform, and a deeper dive into the architecture.
More about openIDL is at: www.openidl.org
More about the meetup is at: https://www.meetup.com/Hyperledger-Dallas/events/278607240/
----
Hyperledger – Open Source Blockchain Technologies
Hyperledger is an open source community focused on developing a suite of stable frameworks, tools and libraries for enterprise-grade blockchain deployments.
It serves as a neutral home for various distributed ledger frameworks including Hyperledger Besu, Fabric, Sawtooth, Indy, as well as tools like Hyperledger Avalon, Cactus and libraries like Hyperledger Aries, Ursa. Learn more about Hyperledger projects: https://www.hyperledger.org/use
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#Hyperledger #HyperledgerMeetup #Blockchain
B
B
Okay,
the
live
stream
is
up
so
you're
welcome
to
kick
it
off
all
right,
thanks
everyone
for
joining
quick
housekeeping
items.
Before
we
start
our
speaker
of
the
day,
ken
has
35
years
working
in
the
insurance
industry
as
an
architect
and
he's
worked
with
large
carriers,
vendors
and
now
ai
is
an
advisory
organization.
B
It's
a
pleasure
to
be
hosting
the
session
today.
Ken
welcomes
questions
during
the
session.
So
if
you
would
like
to
pause
and
ask
please
unmute
yourself,
but
if
you're,
not
speaking,
please
mute
yourself
through
the
session
and
just
a
bit
of
introduction
for
this
session
today
is,
is
so
every
time
there's
a
natural
catastrophe
or
a
pandemic
or
a
hurricane
or
an
earthquake,
or
something
like
this
strikes
straight
regulators
require
or
ask
for
insurance
carriers
to
send
them
the
data
about
the
affected
properties.
B
This
data
helps
regulators
model
risk,
monitor
the
market
activity,
protect
consumers
and
plan
for
future
emergencies,
and
god
knows
that
from
since
1980,
united
states
has
suffered
more
than
250
extreme
weather
disasters,
causing
more
than
a
billion
dollars
in
damage
each
and
but
there
is.
These
are
ad
hoc
reports
that
come
on
top
of
routine
quarterly
and
annual
statistics,
and
there
is
no
good
way
to
present
that
data.
A
Okay,
so
as
as
david
mentioned,
questions
are
welcome,
we're
an
insurance
industry.
This
is
not
just
an
insurance
solution
at
the
end
of
the
day.
So,
if
I'm
going
in
the
wrong
direction,
just
ask
a
question:
get
me
going
in
the
direction
answer.
Any
questions
make
sure
you're
getting
what
you
you'd
like
out
of
this
I'm
going
to
try
to
focus
on
we're
using
hyperledger
fabric
for
for
solving
a
very
important
problem.
So
if
I
steer
away
from
that,
just
let
me
know:
okay,
so
open
idl,
why?
A
A
What's
going
on
out
there,
how
many
people
are
covered
for
different
things
so
that
they
can
put
the
proper
precautions
in
place
ahead
of
catastrophes
et
cetera?
So
that's
kind
of
an
ad
hoc
need
for
data
where
a
regulator
of
department
of
insurance
is
trying
to
find
out
what
what's
out
there
and
they're
asking
the
carriers
to
provide
them
information.
A
Another
one
is
statistical
reporting
ais,
as
special
cnn
is
a
statistical
reporter.
We
provide
data
to
the
the
departments
of
insurance,
about
how
much
insurance
is
out
there
for
different
carriers.
So,
as
I
mentioned,
there's
there's
other
applications
that
can
be
used.
You'll
see
it's
a
from
at
its
base,
it's
hypoallergenic
fabric
and
can
be
used
for
depth
a
lot
of
different
purposes.
A
So
I'm
going
to
show
you
from
a
high
level
what
we're
doing.
Why
give
you
a
quick
demo
just
to
give
you
a
sense
of
how
it
hangs
together
and
then
then
we'll
go
in
all
to
the
bubble,
charts
and
things
to
show
you
some
of
the
architecture
decisions
made
and
how
hybrid
your
fabric
fits
into
this
picture.
A
A
A
We're
a
nationwide
agency
that
does
three
main
things:
statistical
reporting
when
carriers
have
to
report
their
information
to
the
regulators
of
how
much,
how
many
claims
and
how
much
premium
they've
gathered
for
different
lines
of
business.
We
do
that,
on
their
behalf,
also,
a
rating
bureau.
We
provide
lost
costs
which
are
the
sort
of
the
base
number
used
to
come
up
with
premiums.
A
A
So,
for
example,
for
an
auto
product,
we
provide
all
the
all
the
forms
etc
that
you
might
get
on
your
auto
policy
and
the
reason
we
do
that
is
because
some
small
carriers
or
brokers
or
whatever
might
not
have
the
desire
to
do
all
of
that
work.
We
do
that
in
a
standard
form.
We
have
a
lot
of
experience.
We
provide
forms
that
they
can
use
or
they
can
change
them,
etc.
So
these
are
the
three
main
things
that
we
do
with
not-for-profit.
A
Okay.
So
what
are
the
challenges
that
we're
trying
to
solve
with
open
adl
the
recurring
problems,
the
data
owner?
In
this
case
an
insurance
carrier-
wants
to
keep
their
data
private
and
in
their
control,
but
if
they
have
to
constantly
send
data
across
to
regulators,
then
they're
they're
losing
control
of
that
data,
and
they
don't
want
to
do
that.
A
A
B
No
questions
yet,
but
I
have
one
can
really
from
in
a
standard
point
of
view,
so
every
industry
is
struggling
towards
standardizing.
You
know
whether
it
is
tokens
or
protocols
or
for
interoperability.
You
know
for
future
adoption,
so
is
the
open
idea
also
get
towards
implementing
any
standards,
or
are
you.
A
A
slide
for
that
you're
giving
me
a
sort
of
a
four
slide:
segue,
four
or
five
slides
from
now
I'll,
get
to
that.
There
is
a
data
format
that
we
rely
upon
and
will
become
a
standard
over
time
because
at
some
point,
you've
got
to
agree
on
the
format
of
the
data
in
order
to
have
multiple
carriers
participate
in
a
common.
You
know,
extraction
of
that
data,
so
yeah,
so
the
standard
that
we're
developing
right.
A
A
A
our
inside
ais
responsible
for
that
and
her
information,
I
think,
is
later
on
in
the
in
the
the
presentation
as
well.
Okay,
so
let
me
give
you
a
quick
overview
of
what
the
architecture
of
the
system
is.
What
what
the
different
nodes
are.
So
we
use
the
term
node
to
represent
the
full
package
of
open
idl
for
a
particular
purpose.
A
The
carrier
nodes
are-
and
this
is
one
of
the
most
important
aspects
of
the
open
ideal.
This
is
distributed
network
in
that
this
node
here
is
hosted
by
the
carrier
themselves
right.
We
provide
them
all
of
the
scripts
and
startup
to
get
a
node
started
and
connect
it
into
the
network,
provide
them.
You
know,
create
certificates,
etc,
necessary
to
create
the
organization
and
connect
into
the
different
channels.
A
So
they
host
that,
and
that's
why
data
privacy
is
one
of
the
main
things
we've
accomplished
here
is
the
data
that
is
their
raw
data,
is
in
their
cloud,
not
visible
outside
of
their
cloud,
and
so
each
carrier
will
have
their
own
node
and
therefore
their
raw
data
will
be
managed
only
on
their
node.
I
gotta
speed
this
up
a
little
bit
and
then
the
last
last
thing
is
in
a
data
call
as
we
create
data
calls
and
the
carriers
respond
to
those
data,
calls
saying
you
can
use
their
data.
A
The
regulator
can
see
the
results
of
their
data.
It
all
goes
into
this
analytics
node,
where
it's
combined
and
the
report
is
created
and
sent
out.
That's
all
part
of
the
standard
data
call
process
that
that
we
do
today
where
we
aggregate
all
the
information
from
across
multiple
carriers.
So
this
is
a
very
high
level
view
of
the
system.
A
Let
me
go
into
each
type
of
node,
give
you
a
little
sense
of
what's
in
there,
so
this
this
is
the
diagram
as
it
stands
in
ibm
cloud
right
now
we're
moving
all
of
our
stuff
into
the
amazon
web
services
cloud
with
yusuf.
I
saw
isaac
on
the
call,
we're
utilizing
chain
yard
to
help
us
migrate.
This
application-
and
it's
gone
really
well
so
far.
A
So
thanks
isaac
for
for
for
joining
and
just
a
quick
call
out
that
chain,
yard
and
other
vendors
are
part
of
the
the
community
and
are
available
for
carriers
to
to
utilize,
as
they
start
to
connect
into
this
network
as
well.
So
carrier
node
is
going
to
have
a
couple
of
different
things.
A
carrier
and
this
multi-carrier
node
are
going
to
have
a
database
where
we
capture
the
raw
data
in
the
multi-carrier
node.
A
That's
not
nearly
as
private
as
when
you
have
your
own
though,
but
for
small
carriers
it
might
be
fine.
They
put
enough
data
here
to
get
the
job
done
and
then,
of
course,
there's
some
cloud
specific
services
that
are
required
to
make
this
all
work
like
when
you're
connecting
into
an
application.
You
need
to
be
authenticated.
You
need
some
sort
of
authentication
for
that
cloud
and
because
there's
applications
involved
in
here
right,
these
applications
are
running
in
the
kubernetes
cluster.
A
There's
an
application
for
loading
data
and
there's
an
application
for
managing
and
responding
to
data
calls
and
that's
all
inside
of
a
kubernetes
cluster.
As
I
mentioned,
it's
just
javascript
angular,
ui,
javascript
back-ends
and
these
applications.
The
api
specifically
have
access
to
the
to
the
network
through
the
hyperledger
fabric,
api,
so
hyperledger
fabric
is
running
its
components
for
this
particular
node
in
another
cluster,
and
these
apis
call
to
create
transactions
put
stuff
into
the
into
the
ledger
and
get
things
out
of
the
ledger,
etc
and
also
interact
with
the
private
data
collection.
A
So
the
last
type
of
bill,
which
is
different
than
the
other
ones,
is
the
recipient
of
the
process
when,
when
all
the
data
is
consented
and
I'll
I'll
discuss
that
in
a
minute
the
details
of
that
it's
aggregated
here,
there's
some
listeners
to
the
to
the
ledger.
That
say
we
just
got
some
data
in
you
can
do
your
report.
It
runs.
The
report
puts
it
somewhere.
This
is
representative,
not
each
analytics.
Node
may
work
just
slightly
differently.
A
So
so
we've
talked
about
the
three
kinds
of
nodes:
one
for
multiple
carriers
and
one
used
by
ais
and
the
regulators.
That's
the
carrier,
node
a
carrier
node,
which
is
one
per
carrier
and
those
are
all
hosted
by
the
carriers
themselves,
carrier
being
an
insurance
company,
sorry
use
the
insurance
lingo
and
then
the
analytics
node,
which
can
be
hosted
by
anybody
and
for
now
we're
hosting
that
yeah.
It
says
so.
The
life
of
a
data
call
is
a
regulator,
creates
a
data,
call
and
puts
it
out
onto
the
ledger.
A
A
So
the
first
step
in
a
data
call
is
for
the
carriers
to
load
their
data
right.
So
this
harmonized
data
store
inside
their
cloud
is
going
to
hold
all
of
the
raw
data
that
includes
much
more
than
they
really
want
to
share.
But
it's
put
into
a
format,
as
you
mentioned
jody.
This
is
the
format,
for
this
is
the
standard
that
we
are
established
so
that,
when
a
carrier
puts
their
data
in
there,
it's
in
a
data,
a
format
that
when
we
need
to
report
on
it,
we
know
exactly
how
it's
organized.
A
So
we
describe
this
standard
and
there's
a
working
group
in
the
linux
foundation
for
for
managing
that
standard,
and
if
anybody
wants
to
contribute
to
the
standard
more
than
welcome
to
to
participate
in
that
some
contact
information
at
the
end,
so
so
regularly
weekly
monthly
quarterly
the
carriers
are
loading,
their
data
from
the
transactions
that
happen
right.
New
people
create
new
new
policies.
They
have
claims
et
cetera.
A
This
gets
loaded
into
here
over
time
and
then
then
a
regulator
using
the
ais
node
will
come
in
and
create
a
data
call
says
I'd
like
to
see
how
much
insurance
we
have
for
hurricanes
and
south
carolina
creates
the
data
call
and
that
gets
put
onto
the
ledger
right.
So
we
hadn't
put
anything
on
the
ledger,
except
the
knowledge
that
data
was
loaded
in
this
first
step.
A
But
in
the
second
step,
the
data
call
itself
is
just
a
simple
json
document
that
has
text
about
what
what
we
want
to
get
out
of
this
data
call
that
gets
put
onto
the
ledger
so
I'll
show
later
it's
hard
to
show
too
much
on
the
right
amount
on
a
single
screen,
but
there's
two
channels
happening
here:
one
right
now
we're
using
what's
called
the
default
channel
where
all
of
the
carriers,
the
ais
node,
are
all
in
the
same
default
channel.
Therefore,
they're
sharing
a
ledger
and
the
data
call
is
put
onto
that
layer.
A
Do
you
want
me
to
share
those
kind
of
things
and,
at
that
point,
they'll
say
they
like
or
unlike
it,
meaning
that
this
is
something
they
could
respond
to
or
if
they,
unlike
it,
they
might
send
a
note
over
to
the
regulator
and
say
that's
crazy.
We
can't
reshare
that
data.
We
need
to
change
this
a
little
bit
and
we'll
go
through
this
process
of
creating
new
drafts
of
the
data
call
until
everybody's
happy.
So
once
there's
enough
carriers
that
say
this
is
a
good
data.
Call
we'll
do
a
an
issue
of
the
data
call.
A
The
regulator
will
see
that
everybody
likes
it
they'll
issue
the
data
calling
no
and
now
it's
the
request
itself
is
not
changeable,
but
it's
not
quite
executable
yet
right,
because
what
a
data
call
in
the
end
of
the
day
wants
to
do
is
access
this
data
base.
This
private
data
turn
it
into
some
sort
of
shareable
data
that
we
can
get
over
to
the
analytics
node.
So,
let's
see
how
that
happens.
A
When
the
regulator
issues
the
data
call,
it
goes
into
a
state
where
we
can
create
an
extraction
pattern
and
attach
it
to
that.
So
the
extraction
pattern
right
now
is
an
is
a
map
mapreduce
right,
so
in
there's
the
ability
to
do
a
mapreduce,
you
give
it
two
javascript
functions,
it
converts
it
into
a
different
collection
and
the
results
are
there's
some
aggregation
and
some
keys
created.
So
all
the
extraction
pattern
is
is
two
functions.
A
A
So
so
this
is
a
real
important
aspect
of
this
that
the
carrier,
when
they
consent,
will
have
a
chance
to
see
the
data
call
what's
going
to
be
executed
against
the
database.
They
have
actual
code
the
map
and
reduce
functions.
They
can
pull
that
and
download
that
they
can
test
it
make
sure
it
will
do
everything
they
expect
and
nothing.
They
don't
expect,
and
if
it's
true
that
is
they're
happy
with
it,
it
represents
the
data
call.
They
can
then
consent.
A
That's
a
an
event
that
goes
on
to
the
on
to
the
ledger,
so
that
there's
evidence
of
who's
consented
and,
as
a
result,
a
listener
will
say:
oh
they
consented.
I'm
gonna
now
run
the
extraction
pattern.
The
execution
of
the
extraction
pattern
is
basically
on
every
consenting
node.
That
extraction
pattern
is
loaded
up
into
a
program
sent
to
it
runs
the
extraction
pattern
and
the
results
in
the
extraction
pattern
are
put
into
the
private
data
collection,
so
we're
again,
depending
on
hyperledger
fabric,
to
share
the
data.
A
The
private
data
collection
is
on
a
channel,
that's
connected
to
the
analytics
node
for
each
carrier,
node,
and
so
the
data
shows
up
here
and
then
the
left
report
can
run.
I
have
the
diagrams
in
a
little
while
that
that
illustrate
all
this
again.
So
hopefully
that's
not
too
too
big,
but
that's
that's.
What's
going
on
from
a
high
level,
so
the
the
actual
extraction
pattern
itself
when
the
carrier
consents
to
the
data
call.
A
The
extraction
pattern
is
retrieved
from
the
ledger
and
we
put
it
in
the
ledger
and
then
the
extraction
pattern
is
run
against
the
harmonized
data
store
and
at
the
time
this
is
run.
It
has
the
ability,
because
it's
on
the
carrier
node
to
correlate
private
data
with
other
data,
so
in
in
this
case,
we
did
a
proof
of
concept
to
show
some
carriers
how
this
could
be
done.
A
A
If
we
were
to
run
this
in
some
other
part
of
the
architecture
we
wouldn't
have
access
to
the
address,
because
carriers
will
not
share
the
address
so
because
we're
running
it
on
their
node.
We
have
access
the
address.
We
can
correlate
the
ppp
data
and
we
can
share
the
ppp
correlated
data
in
an
aggregated
fashion
and
the
address
is
never
shared,
so
we're
able
to
use
the
address
without
sharing
it
right.
So
that's
a
super.
A
B
A
So
are
yeah?
Okay,
so
let
me
just
answer.
The
the
smart
contracts
are
all
crud
here
right,
most
of
the
most
of
the
the
secret
sauce
to
this
application
is
in
is
outside
the
smart
contracts.
We
update
and
read
from
the
ledger
and
push
to
the
private
data
collection,
but
those
are
just
very
simple:
smart
contracts.
We
haven't
actually
changed
the
smart
contracts
in
a
year
and
a
half.
A
A
We
know
that
the
amazon,
kubernetes
managed
service
doesn't
go
cross-cloud
and
we
need
to
do
multi-cloud
so
so
right
now
we're
not
doing
any
managed
services.
We
probably
will
provide
a
marketplace
component
as
we
make
this
available
in
a
more
open
open
way.
As
of
now
we've
been
building
with
infrastructure
as
code,
but
it's
it's
more
sort
of
as
we
go
building
each
node
in
its
own
way
without
managed
services,
but
we're
we've
looked
to
get
there
and
any
and
chain
yard
we'll
be
helping
with
that.
Among
other
vendors,
as
we
go.
A
A
We've
used
s3
a
little
bit,
but
that's
a
so
one
of
the
tenets
of
this
architecture
is
to
be
cloud
multi-cloud
and
therefore
as
agnostic
of
the
cloud
as
possible,
and
so
we're
trying
not
to
use
s3
per
se
as
a
place
for
files
but
ipfs
where
that
would
fit
in
the
architecture.
I'm
not
sure
I'd
have
to
have
to
a
separate
discussion.
So
sorry,
I
couldn't
answer
that
one.
B
A
Yeah,
prior
to
this
project,
we
had
something
called
statistical
plans,
which
is
how
we
would
capture
data
from
our
customers,
they're,
very
old.
We
wanted
to
modernize
those
and,
as
part
of
the
modernization,
we're
defining
those
standards
as
we
go
as
part
of
the
open
ideal
yeah
we
do,
we
do
try
to
base
it
on
other
standards
and
and
point
to
other
standards,
but
there's
all
kinds
of
things
that
are
outside
my
sort
of
expertise
as
to
whys
and
what
force
of
how
those
standards
will
be
developed.
A
Yeah,
so
we
had
an
earlier
call
where
one
of
the
carrier-
architects,
like
why
are
we
using
blockchain?
You
just
want
to
use
the
term
right,
and
the
answer
is
it's
funny.
I
was
that
person
inside
ais
right
and
I
was
like:
why
are
we
using
blockchain?
We
could
do
this
ourselves,
so
blockchain
has
some
inherent
trust
associated
with
it
that
if
a
carrier
comes
along
and
hears
the
word
blockchain,
they
know
there's
something
going
on
there
about
privacy
and
trust,
etc.
A
Hyperledger
fabric
is
an
open
source,
well-known
thing
that
it
does
this
pretty.
Well,
I
I'm
not
going
to
tell
you
that
there's
not
a
better
option
for
what
we're
doing
here.
It
fits
well
and
we're
not,
I
don't
think
we're
overusing
it
and,
as
we
get
into
the
diagrams
I'd
be
happy
to
get
feedback
on
like
you.
A
Didn't
really
need
hyperledger
fabric
for
that
and
the
answer
is
clearly:
we
didn't
need
to
use
hyperledger
fabric,
but
if
we
built
it
ourselves,
then
that
would
be
a
that
would
be
a
red
flag
for
a
lot
of
people,
but
some
of
the
other
technologies
there's
a
history
to
any
project.
To
the
people
who
initially
built
the
system,
you
know
they
use
hyperledger
fabric
and
we
haven't
seen
a
reason
to
to
change
course
on
that.
A
Yeah
we'll
get
into
more
detailed
pictures
which
we
all
like
to
see.
So
so
let
me
do
a
quick
walkthrough,
I'm
not
going
to
do
the
full
flow.
It's
like
a
10-15
minute
flow,
but
I'll
give
you
a
sense
of
what's
going
on
at
any
one
time
right.
So
the
first
step
in
the
process
is
for
a
regulator
to
create
a
create
a
data
call.
So
this
is
the
ais
node
we
mentioned
before
sorry
ais
right,
so
the
name
is
indicative
up
here.
A
A
A
Again
carrier
is
an
insurance
company.
I
just
use
that,
but
so
they
see
these
same
draft
data
calls
they
can
go
in,
take
a
peek
at
it
and
say
yeah.
I
see
what
you're
trying
to
do
right.
This
is
all
verbiage
at
this
point
right,
there's
no
code
to
run,
but
this
is
something
that's
been
put
onto
the
blockchain
and
I,
as
a
carrier
can
say
I
do
or
don't
like
it.
A
I
can
put
this
like
to
like
the
data
call
and
then,
when
the
regulator
comes
back
in
and
looks
at
that,
I
know,
there's
a
little
bug
here.
They'll
see,
see
the
lights,
increase
and
eventually
they'll
say
that's
good
and
the
regulator
at
one
point
will
say:
I'm
going
to
issue
this
right.
So
there's
a
few
functions
here
available
to
the
regulator
because
of
their
role
that
aren't
available
to
a
carrier.
They
can't
they
can
create
new
data
calls
they
can
issue,
etc
right.
A
So
so
this
here,
while
we're
running
it
in
our
own
cloud
right
now
for
a
proof
of
concept
purpose.
This
is
the
code
and
the
whole
node
that
would
be
running
inside
the
carrier's
cloud.
Right
this
would
be
on
amazon
or
google
or
azure,
and
maybe
the
ibm
cloud.
We
don't
get
a
lot
of
calls
for
ibm
cloud,
but
this
will
be
running
on
their
their
cloud.
A
So
once
enough
carriers
are
happy
with
it.
The
data
call
is
issued
and
once
issued,
the
data
calls
are
are
available
for
consent
right.
So
so
up
to
now
a
carrier
hasn't
done
anything
to
to
say
I
want
you
to
use
my
data.
They
have
to
look
at
the
extraction
pattern,
so
here's
the
extraction
pattern.
I
can
look
at
what
the
code
was
written
to
implement
the
language
that
we
saw.
Let
me
just
say
this
real
quick,
so
the
code
it's
it
can
be
very
complex,
but
it's
really
just
like.
A
I
said
a
mapreduce
function,
so
this
is
just
a
way
to
share
it
as
a
string.
So
a
carrier
can
take
this
and
say:
oh,
I
see
the
map
function.
I
see
the
reduced
functions
down
in
here
too,
and
take
this
code
put
it
into
their
development
environment
point
to
their
database
run.
It
see
what
would
result
because
it's
just
a
standard
way
of
executing
something
against
and
they
can
basically
test
it
and
verify
that
it
is
what
they
expect
and
once
they
agree
that
it
is
what
they
expect.
A
Sorry
again,
then
there's
a
consent.
I've
already
consented
to
this
there's
a
consent
button
over
here
that
says
I
can
send
to
that
and
at
that
point
the
consent
will
will
run
the
extraction
pattern
against
their
database.
So
let
me
give
you
a
quick
look
at
what
the
database
looks
like,
so
this
is
just
a
little
test
database
that
I
use,
but
so
this
is
a
the
insurance
carrier's
data.
A
A
Yeah,
so
here's
here's
information
that
is
private
for
the
carrier
for
this
particular
policy.
They
have
provided
a
an
address
that
that
they
don't
want
to
share
with
the
with
the
regulators,
but
when
we
run
the
data
call,
we
do
want
to
use
that
address
to
see
if
there's
a
ppp
loan
associated
with
that.
So
when,
when
the
extraction
pattern
ran,
it
results
in
another
collection
and
that's
what
this
collection
is
is
basically
taking
that
input.
A
A
Which
is
this
ppp
information?
You
can
see
here
that
we
were
able
to
use
the
address.
We
don't
share
the
address
itself
now
on
the
output,
but
we
use
the
address
to
find
the
ppp
loan.
You
know
the
no
the
low
we
can
get
the
loan
number
etc,
but
we
can
get
how
much
the
loan
was
for
some
race
information,
all
kinds
of
extra
information
that
the
address
was
used
for
but
didn't
share
the
address
right.
So
that's
really
important.
A
So
then
what
happens
is
one
of
the
one
of
the
components
in
the
in
the
carrier?
Node
will
then
take
this
collection
and
put
that
into
a
private
data
collection.
Data
collection
goes
over
to
the
analytics
node
and
then
the
report
can
be
executed
and
then,
after
a
certain
period
of
time,
we
throw
away
the
data
on
the
analytics
now.
So
I
know
that's
not
the
full
fledged
start
to
finish
demo.
A
A
A
It's
very
important
that
the
carriers
trust
that
their
data
is
not
going
to
be
messed
with
and
if
they,
if
they
do
something
that
nobody
can
change
that
like
what,
when
they
consent
to
something
somebody
can't
say
they
didn't
consent,
it
need
to
be
performed,
of
course,
needs
to
be
secured.
It's
got
to
be
permission.
We
need
to
know
who's
in
this
blockchain
network.
That's
why
we're
using
hydrologic
fabric.
It's
permissioned
network
needs
to
be
distributed.
A
We're
going
to
have
nodes
that
are
not
running
in
our
cloud
and
that
other
cloud
could
be
aws
could
be,
azure
could
be
google,
it
might
not
even
be
a
cloud,
I'm
not
sure
we
want
to
support
the
non-cloud
sort
of
running
on
on-prem
model,
but
it's
definitely
a
possibility
and
it
needs
to
be
manageable.
So
when
I
talked
about
the
ppp
aggregation,
there's
there's
a
lot
of
different
data
sources.
That
might
be
pointed
to.
Maybe
it's
just
a
call
to
a
uri.
Maybe
it's
a
whole
data
set.
A
Maybe
it's
a
component
that
needs
to
be
added.
We
need
to
be
able
to
manage
nodes
that
are
distributed.
We
need
to
be
able
to
go
to
that
carrier
and
say
we
need
to
give
you
a
new
version
of
open
idle
that
gets
installed
in
your
cloud
and
runs
the
way
we
expect
right.
So
it's
a
very
important
part
of
this
process
too.
A
A
It's
all
in
the
ledger
and
nobody's
hiding
anything.
There's
no
secret
things
going
on.
As
far
as
the
correspondence
between
the
different
people
on
the
network
and
then
keeping
the
data
in
place
is
really
the
one
of
the
main
reasons
we
started
looking
at
open
idle.
How
does
how
can
a
carrier
keep
their
address
but
make
it
usable
for
for
connecting
to
other
data?
And
how
can
we
keep
that
from
going
data
from
going
across
the
network
that
shouldn't
that
doesn't
need
to
right?
We
don't
they
don't.
A
A
Okay,
so
the
application
architecture
kind
of
gone
through
a
little
bit
of
this
right.
It's
using
distributed
ledger
technology,
the
hyperledger
fabric,
so
that
anything
we're
doing
with
other
carriers
or
nodes
is
all
managed
and
evident
on
the
the
ledger
itself,
and
any
data
that
goes
across
to
the
analytics,
node
or
et
cetera,
will
be
using
private
data
collection.
So
this
is
not
code,
reload
right
we're
just
building
on
top
of
hyperledger
fabric.
A
A
A
So
how
does
the
data
flow?
The
carrier
data
is
something
that
we
don't
control
right.
So
this
the
harmonized
data
store
is
the
data
in
the
format
that
we
understand
is
carrier
data.
We
don't
know
where
that
comes
from
where
they
keep
it,
but
we
help
them
to
build
a
mapping
layer
right.
So
we're
going
to
provide.
A
A
A
So
we
need
to
be
multi-cloud,
we're
using
kubernetes
and
and
then
there's
some
services
specific
to
the
cloud.
This
is
kind
of
an
in-depth
look,
a
little
bit
more
in-depth,
there's
an
even
deeper
level,
of
course,
when
we're
talking
about
all
the
different
pieces
of
amazon
web
services
that
we're
using
to
provide
that.
But
these
are
all
the
different
nodes
and
different
channels
that
they
contribute
to
and
all
that
applications.
So
so
the
interaction
between
the
nodes
is
all
hyperledger
fabric
right,
there's,
no,
no
open
check
channels
or
anything
like
that.
A
And
here's
a
sort
of
a
detailed
picture
of
how
the
architecture
is
getting
mapped
into
amazon.
This
is
one
of
the
deliverables
from
chain
yard.
Helping
us
define
how
the
amazon
web
services
are
used
to
to
provide
this
to
support
the
system.
Okay,
so
deadlocks
is
something
we're
working
out
as
we
go
and
our
question
earlier.
Do
we
use
managed
services?
I
was
just
having
a
conversation
earlier
where
we
might
create
a
you
might
decide
to
create
a
an
amazon
managed
product
right.
That
is
the
open
idle
which
includes
the
terraform
etc.
A
A
So
that's
the
devops
picture.
So
how
do
we?
How
are
we
addressing
these
particular
things
right,
we're
using
hyperlogic
fabric,
because
it's
kind
of
a
trusted
network,
kubernetes
and
auto
scaling
etc?
And
it's
it's
very
robust
architecture
right,
it's
resilient
and
recreates
pods
when
they
go
down
all
those
kind
of
things.
So
kubernetes
is
we're,
depending
on
queries,
for
a
lot
of
that.
A
lot
of
security
is
built
into
the
fact
that
we
have
distributed
nodes
right.
A
We
don't
we
don't
need
to
worry
about
cordoning
off
data
for
carrier,
one
because
we
can't
even
see
that
database
right.
All
we
have
to
do
is
make
sure
that
they
agree
that
none
of
that
data
has
any
way
to
get
outside
of
their
node
permission
right.
So
everybody
on
the
system
has
to
have
the
appropriate
permissions,
as
defined
by
hierarchical
fabric,
to
even
contribute
to
the
network
and,
of
course,
hyperledger
fabric
is
the
only
way
we're
getting
data
across
the
wires
it's
distributed.
A
Hydrogen
fiber
supports
that
and
that's
one
of
the
big
decisions
you
know
back
to
an
earlier
question
about
managed
services
to
manage
kubernetes
service
and
amazon
doesn't
support
other
clouds.
Maybe
that's
changed
since
we
had
that
discussion,
but
this
is
a
very
important
aspect
of
the
of
the
architecture.
A
As
I
mentioned,
we're
going
to
be
pushing
changes
to
remote
clouds,
so
it
we
need
to
put
in
place
something
to
do
that
and
then,
of
course,
transparent
everybody
who's
going
to
use
this
system
needs
to
know
exactly
what's
being
put
into
their
cloud
because
because
we're
not
hosting
it,
we
need
they
need
to
know
exactly
what's
going
on
in
their
cloud.
So
the
infrastructure
is
code
is
self
documenting
and
then
they
keep
that
data
in
place
again,
because
it's
a
carrier
node
we
never
get
to
handle
their
data.
All
right.
A
We
have
a
couple
more
quick
slides.
We
provided
a
reference
implementation
running
on
mini
cubes,
so
you
can
kind
of
kick
the
tires
and
get
a
sense
of
how
things
work
without
committing
to
the
cloud
and
we'll
also
have
a
reference
implementation
in
aws
as
a
result
of
our
work
with
chain
yard,
so
that
somebody
using
aws
can
immediately
get
up.
Other
clouds
are
later
on
in
the
in
the
road
map.
A
So,
as
your
question
asked
before,
maybe
there's
more
than
five
slides
right.
What
is
the
standard?
The
harmonized
data
store
is
not
one
standard,
but
it's
a
standard
for
every
use.
Right.
If
you
have
a
data,
call
that's
for
auto
a
data,
call
that's
for
a
different
line
of
business.
They
can
probably
use
the
same
basic
standard,
but
there
may
be
different
ways
to
get
the
data
in
there
and
they
may
need
slightly
different
things.
But
if
we're
using
this
for
different
purposes
like
for
regulatory
reporting,
the
format
of
the
data
could
change.
A
So
each
use
of
this
system
could
lead
to
a
different
standard
and,
as
I
mentioned,
dana
burgess
is
our
director
of
bi
here,
at
ais
and
in
charge
of
the
data
standards
for
open,
idl
and
she'll,
be
on
a
one
of
the
steering
committees
for
the
hyperledger
fabric.
Sorry
for
the
open
idle
project
in
in
the
linux
foundation,
so
that
there
will
be
a
conversation
about
all
of
that
over
there.
A
So
now
we
talked
about
harmless
data
store.
So
how
can
you
contribute
the
data
models
right,
we'll
need
and
want
very
much
the
input
of
everybody
using
these
this
network
to
share
data
to
participate
in
these
these
use
cases.
Those
data
models
are
going
to
need,
help
from
everybody
to
make
sure
that
they're
robust
and
include
everything
we
need
the
architecture
right
as
we
go
into
new
clouds,
we'll
need
help,
building
the
different
cloud
footprints
implementations
of
application
components
as
they
come
along
accessing
ppp
access
and
census
data.
A
The
there
is
some
technical
debt
in
the
system,
of
course,
that
that
will
need
somebody
to
do.
Ais,
of
course,
doesn't
want
to
be
the
only
one
contributing
to
this
chain
yard
is
an
example
of
an
external
vendor.
That's
helping
out
and
other
vendors
have
agreed
to
participate
as
we
get
new
components
or
if
we
get
new
organizations
wanting
to
be
part
of
the
network,
those
will
need
contributors,
contributors
to
help
them
get
onboarded
and,
of
course,
support
documentation,
testing
all
things
that
that
we
can
use
help.
A
This
is
a
totally
open
source
project,
all
the
code's
available
in
in
github
and
and
available
for
for
viewing,
etc.
So
so
what
are
we
doing
right
now?
We're
migrating
from
my
the
ibm
cloud
to
aws
and
again
with
the
chain.
Words
help
we're
creating
the
reference
implementations,
establishing
those
property
and
casualty.
A
Hd,
harmonized
data
store
standards
and
we're
building
regulatory
reporting.
We
currently
have
an
internal
system
that
does
regulatory
reporting
we're
building,
pushing
that
over
to
open
ideal
so
that
we
can
improve
our
footprint,
make
this
more
open
the
way
that
works
all
right.
Okay,
I
think
that
is
yeah
wait.
I
want
to
go
on
back
yeah
there
we
go
so
here's
some
urls
for
for
getting
involved.
Openidl.Org,
I
don't
have
a
github.
A
The
github
account
is,
do
it
real
quick
is
open,
ideal,
org,
open
idle
main
and
all
of
the
code
for
all
of
this
stuff
is
out
there
and
we
also
have
a
slack
channel
if
anybody's
interested.
You
can
contact
me
ken
s,
ais,
online
dot,
com
and
and
or
truman,
and
you
can
go
out
to
the
open
idea.org
to
see
more
information
about
the
system
and
you
can
become
a
linux
foundation.
A
B
B
Hi,
this
is
raj
sigamani,
excellent
presentation,
great
work.
I
think
we
are
making
big
progress
with
the
linux
foundation.
Slash
hyperlogic
fabric-
also,
I
guess
with
ibm
donating
all
of
those
free
store,
open
source
is
really
excellent.
I
had
quick
question
for
you
in
terms
of
the
private
data
collection
versus
channel
data
where
and
how
are
you
using
them
differently?.
A
B
A
Hi,
this
is
angel,
great
job,
real
quick.
Can
you
just
give
us
a
little
high
level?
What
what
type
of
what
does
your
team
look
like
before
you
started
this
project?
What
does
it
look
like
today
and
from
a
technical
skill
set
or
upscaling
standpoint?
What
are
the
areas
that
you
had
to
invest
in
or
bring
in
new
people
sure
we
started
with
ibm
ibm
being
they?
I
believe
the
originator
or
a
hyperledger
fabric
could
correct
me.
If
I'm
wrong,
I
don't
know
the
whole
history.
I
think
they
contributed
it
to
the
linux
foundation.
A
A
You
know
I
mentioned
them
more
than
I
they
probably
could
have
hoped
for,
but
they're
they're
experts
and
and
all
the
technologies
that
we're
using.
We
have
also
engaged
with
other
vendors.
So
our
our
model
going
forward
is
to
have
a
very
small
footprint
inside
ais
and
depend
on
vendor
partners
and
the
open
source
community
to
build
this.