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From YouTube: Trade Finance Digitalisation: Do we understand our data?
Description
A presentation at the Hyperledger Trade Finance Special Interest Group on May 11, 2021 featuring Harri Rantanen from SEB.
Data without meaning is worthless and therefore applying a semantic model makes it as information, knowledge and wisdom. With Knowledge Graphs meaningful information can be linked over the internet and create basement for both machine and human readable and understandable context. Harri Rantanen will explain, with some examples, how semantic modeling, Standardised Trust community and secure corporate data sharing methods, technology and applicable rulebooks may boost also Trade Finance digitalisation. All this will require collaboration and agreement on used international standards and market practices.
More about the call is at: https://wiki.hyperledger.org/display/TFSIG/TF-SIG+Meeting+-+2021.05.11
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A
B
B
The
linux
foundation
trust
policy,
you
know,
as
for
customs,
the
linux
foundation
and
trust
policy.
Linux
foundation
meetings
involve
participation
by
industry
compatibles,
and
it
is
the
intention
of
the
linux
foundation
to
conduct
all
of
its
activities
in
accordance
with
applicable
and
trust
and
competition
laws.
B
If
you
have
questions
about
these
matters,
please
contact
your
company
council
or,
if
you're,
a
member
of
the
linux
foundation,
feel
free
to
contact
andrea
up
the
grove
of
the
firm
of
gaster
of
the
globe
llp,
which
provides
legal
counsel
to
the
linux
foundation.
Hyperledger
is
committed
to
creating
safe
and
welcoming
community
for
all
for
more
information.
Please
visit
our
hypological
conduct,
so
my
pleasure
to
you
to
have
you
all
here
is
everything
this
time.
C
A
C
C
So
you
can
mute
people
yeah
right
thanks.
It
was
quite
nice
singing
anyway.
So,
let's
start
I
have
a
couple
of
slides
were
prepared
for
you
and
then
I
will
have
a
slight
kind
of
a
multimedia
show.
Today.
I
will
show
you
and
practice
also
the
things
that
I'm
I'm
working
with,
and
hopefully
there
are
some
value
for
you
as
well.
C
So
the
header
for
the
session
today
is,
do
we
understand
our
data
and
the
key
question
today
is
why,
like
you
see
there,
we
start
asking
why,
when
we
are
three
years
old
and
even
the
pop
bands
are
asking
that,
but
finally
we
as
a
business
people,
I.t
people,
technical
people,
blockchain
people.
We
also
are
really
interested
of
the
question.
Why
and-
and
you
will
understand
why
why
this
is
a
free
question
today?
C
Finding
many
many
items
in
the
nordic
countries
where
we
are
delivering
the
good
things
in
in
digital
way,
and
I
have
been
working
in
sap
for
13
years
and
now
last
three
years
as
a
business
developer,
looking
at
the
future,
both
from
my
our
own
banking
perspective,
but
also
from
the
our
customers
perspective,
I'm
serving
mostly
large
corporations
and
financial
institutions.
But
I
have
some
background
as
well
for
the
private
customer
and
sme
point
of
view.
C
C
I
will
present
you
another
community
that
we
have
been
running
for
three
years
or
four
years
actually
already
standardized
trust
as
then.
Some
practical
cases
how
the
knowledge
graphs
actually
can
improve
our
understanding
of
our
data
and
then
a
summary
as
well,
and
you
will
get
this
presentation
in
a
pdf
format,
so
the
presentation
is
is
filled
with
hyperlinks
with
interesting,
hopefully
interesting
links
of
data
where
you
can
dive
in
in
a
deeper
way
into
the
items
that
I'm
really
scratching
the
surface
today.
So
I
have
a
tight
agenda.
C
So
the
point
here
is
that
the
organizations
that
are
following
must
share
data
mantra.
Instead
of
don't
share
data
are
making
better
business
overall.
So
it's
really
critical
that
we
are
now
moving
into
digital
world
platforms,
ecosystems
that
are
based
on
information
sharing
and
if
you
are
not
able
to
do
that,
then
then
you
are
not
really
well
participating
in
that
kind
of
ecosystems
and
platforms.
C
C
What
we
are
dealing
with
is
only
what
it's
a
extract
of
the
real
data
real
world
by
some
kind
of
metrics
that
we
have
been
defining
ourselves
via
standards
or
market
practices.
Do
we
measure
kilos
or
or
pounds?
That's
up
to
different
metrics
that
we
are
using,
but
it's
not
telling
that
much.
It's
only
a
extraction
of
the
real
real
world,
then,
when
we
start
moving
from
what
to
who?
C
Where
and
when,
then
we
are
combining
the
data
together
so
that,
for
example,
in
my
case,
I
can
show
you
that
there
is
a
bank
account
with
some
data
and
there
is
a
closing
date,
balance
on
the
2019
date
for
5
000
euros,
even
even
on
the
credit
side.
It
now
has
an
informational
meaning,
but
then
to
make
that
even
more
meaningful,
answering
the
question.
How,
then
we
are
talking
about
the
semantics?
We
have
to
be
able
to
compose
that
information
into
the
new
level,
meaning
that
we
have
a
understandable
set
of
information
available.
C
So
now
I
can
start
making
conclusions
that
how
this
is
possible
that
my
my
bank
account
is
on
5000
euros,
credit
side
and
finally,
the
the
last
thing
that
we
we
humans
are
good
are
exactly
asking
the
question:
why
why
this
is
important
information?
While
this
is
information,
this
information
is
meaningful
or
knowledge
point
of
view,
and
then
we
are
answering
the
question
why
we
can
make
decisions
out
of
that,
we
can
start
predicting
things
like.
C
C
C
So
we
had,
we
have
started
this
internet
evolution
with
web
0.1
of
1.0,
which
was
actually
only
reading
the
web
pages
that
are
available
there.
So
it
was
only
output
from
different
https
or
http
sites
that
you
could
evaluate
what
kind
of
data
there
is
on
each
and
every
home
site.
Then
we
moved
into
the
social
web,
where
we
could
also
show
our
fingers
up
and
down
participating
into
different
discussions
and
also
giving
content
into
different
home
sites
and
and
the
different
data
storages
that
were
available
there.
C
So
it
was
the
next
step
for
for
making
the
web
on
the
next
level.
2.0,
and
now
we
are
talking
about
this
3.0
web,
which
is
actually
started
2016
and
the
key
person
there,
which
is
now
tim
berners-lee
having
a
sir
as
a
as
a
ranking
for
him.
It
doesn't
it
wasn't
there
yet
in
1996,
but
now
that
it
is
so
team.
C
Bernice
lee
has
said
that
the
vision
already
the
web
3.0
vision
in
1999
that
we
are
moving
into
linked
web,
so
that
the
the
web
is
also
executing
some
stuff
by
itself
and
the
home
sites.
Web
pages
humans
included,
can
be
operating
that
by
themselves,
and
that
means
that
we
have
a
semi
available,
which
is
combining
the
approach
that
we
human
beings
are
doing
together
with
the
machines,
and
that
is
really
the
important
thing
that
we
are
able
to
to
do
now.
Having
the
web
semantics
available.
C
But,
finally,
the
knowledge
crash.
What
is
the
meaning
of
that
that
started?
2012
and-
and
this
is
part
of
the
wgc
semantic
web
vision.
So
the
idea
here
is
like
it's
there
in
the
picture
that
we
can
have
whatever
database
blockchain,
whatever
home-based
structure
or
whatever.
We.
We
define
simple
definitions
of
simple
things,
like
cities
being
a
place
and
we
can
make
a
person
available
and
then
we
have
a
date.
C
Alice
is
also
a
person.
Pilgrim
appeal
has
visited,
eiffel
eiffel
tower,
eiffel
tower
is
a
place
and
louvre
is
a
museum
and
it's
located
in
paris,
and
we
can
make
quite
complicated
and
easily
understandable
statements
out
of
these
instances
of
data
and
information,
and
that
makes
that
possible
both
as
humans
and
machines
to
understand
and
that's
really
critical.
C
What
kind
of
links
are
there
between
these
nodes
in
the
in
the
knowledge
graph?
So
again
saying
this?
Finally,
that
we
started
from
the
flat
files
and
we
have
been
moving
into
relational
data
models,
different
kind
of
databases
that
are
there,
then
the
xml.
The
revolution
study
that
we
have
schemas
that
are
able
to
deliver
validated
data
between
different
endpoints
and
still
there.
We
were
using
a
lot
of
ftp
or
sftp
to
move
the
data
from
point
a
to
point
b,
but
then
2004.
C
The
definition
of
the
semantic
web
started
by
w3c
and
2013.
The
knowledge
graphs
were
created
based
on
that
semantic
web
languages
and
and,
of
course,
again
starting
from
the
big
text.
So
google
is
using
this
technique
and
they
have
their
own
knowledge
graph
implementation
by
themselves,
which
is
practically
openly
available
via
apis.
So
if
you
are
interested
of
that,
you
can
look
that
into
or
from
the
google
developer
site
you
can
make
any
of
your
requests
or
or
queries
that
you
are
doing
in
in
the
google
pages.
C
This
kind
of
stuff,
when
we
have
a
knowledge
graph
available
and
the
semantics
are
available
for
the
data
wherever
that
is
in
whatever
technology
stored,
then
the
combination
of
the
data
can
be
done
and
then
we
can
start
utilizing
artificial
intelligence
for
analyzing.
The
data
like
google
is
doing.
C
So
all
the
data
will
be
moving
structured
data
instead
of
old,
empty
messages
that
were
a
little
bit
more
unstructured,
actually
quite
a
lot
of
more
unstructured,
so
how
this
is
evolving
in
the
financial
world.
Overall,
with
the
semantics,
there
is
already
edm
council
enterprise
data
management
council
that
is
working
on
this,
and
they
have
created
this
financial
industry
business
ontology
fibo.
If
you
want
to
call
it
like
that-
and
fibo
is
available
there
for
you.
C
So
you
can
go
into
fibo
viewer
in
the
internet
and
start
browsing
there's
the
stuff
that
is
available
there.
It's
not
100
covering
all
the
final
services
information,
but
many
of
the
items
are
there
available
like
business
entities,
which
is
really
interesting
to
look
into
that.
You
can
drive
a
deep
dive
already
into
that
stuff.
From
from
your
own
point
of
view,
so
the
hyperlinks
are
working
quite
well,
so
you
can
explore
afterwards
after
this
presentation,
also
by
yourself
all
these
resources
available
in
the
presentation.
C
We
had
a
booth
camp
where
we
had
people
coming
in
from
different
perspectives
from
corporations,
vendors
banks
and
we
had
a
discussion
and
we
created
white
paper
which
is
available
there
on
the
standardizedtrust.com,
which
you
can
download,
is
still
really
valid
paper.
We
found
out
that
there
are
really
some
pain
points
that
we
have
to
address
2017.
C
We
talked
about
standards
and
actually
semantics
already
there,
because
in
that
time
europe
eu
level
e-invoice
semantic
model
was
just
coming
up.
It
was
in
the
discussion
to
be
a
regulation
which
is
it
now
already,
so
we
were
copying
that
semantic
model
approach
from
there
and
then,
of
course,
making
standardized
approach
available
for
for
the
team.
So
we
have
now
about
300
plus
members
in
linkedin
group,
which
we
use
mostly
for
the
market
intel.
C
So
we
can
jump
into
the
standardized
home
base
homepage
and
I
can
show
you
some
basic
facts
from
from
this
point
of
view.
We
have
working
groups
here
and
nowadays
we
work
within
this
working
group
number
two
and
the
latest
stuff
that
is
available
there
is
is
in
one
drive.
We
do
everything
openly,
so
you
do
not
have
to
pay
anything.
You
just
commit
yourself
into
the
team
and
suddenly
you
are
able
to
look
into
the
semantic
model
draft
as
we
are
working
here.
C
So
we
have
a
a
data
set
that
is
describing
the
undertaking
with
which
we
have
defining
all
the
necessary
fields
that
we
need
for
making
the
undertaking
available,
and
it's
quite
longish
description
and
at
the
same
time
we
also
make
a
comments
available.
How
for
example,
icc
rules
like
urdg
can
be
applied
into
each
and
every
point
that
is
there.
We
have
also
used
the
code
lists
available
so
that,
if
you
want
to
see,
for
example,
different
undertaking
parties
that
are
there,
they
have
been
also
added
into
the
lists.
C
So
you
can
make
this
as
a
really
living
document,
and
you
can
use
that
also
available
for
any
kind
of
use
case
mapping.
So
you
can
have
the
code
list
available
if
you
want
to
you,
make
a
use
case
of
rental
guarantee,
counter
guarantees
whatever
and
all
these
code
lists
are
coming
from
the
standardized
trust
home
page.
We
have
a
resource
site
here,
so
we
have
all
the
currency
court
lists
that
are
in
the
excel
sheet
dynamically
linked
from
this
home
page.
So
we
have
links
available
here.
C
So
we
have
tried
to
make
this
as
modern
as
possible
and
easily
amendment
amendments
available
so
that
we
can
agree
what
kind
of
stuff
we
are
delivering
easily
available
for
anyone
who
is
available
for
this
setup
so
and
also
in
the
onedrive.
I
can
show
you
just
wait
a
second.
I
go
with
the
right
page
here.
We
also
now
started
lately
a
json
description
as
well,
so
we
have
made
a
from
the
excel
seed.
C
A
json
schema
that
I
can
show
you
here,
so
we
can
make
that
available
for
the
ones
that
are
technically
interested
of
how
how
this
common
model,
voluntary
and
and
freely
available
openly
available.
Whoever
can
be
applied
into
what
kind
of
platform
vendor
system
or
or
application
of
of
different
guarantees.
You
would
like
to
implement
with
that
and,
of
course,
we
have
been
now
exercising
as
well
how
that
would
look
like
in
a
json
payload,
so
there's
a
short
example
of
that.
C
What
kind
of
rental
guarantee
could
be
described
in
json
payload
so
that
whatever
machines
can
understand
and
read
it
in
the
in
the
purposes
of
using
that
we
will
not
go
into
in
this
team
into
any
kind
of
application,
digital
security
solutions
or
whatever
we
focus
on
the
practical
side
of
the
the
guaranteed
descriptions
and
and
start
and
continue
on
that
we
will
gradually
move
now
from
the
guarantees
also
to
the
documentary
credits.
But
due
to
our
small
team,
it
will
take
some
time
to
finalize
the
the
current
descriptions
available.
C
So
that
was
the
community
story
there
and,
of
course,
if
you
are
interested
to
join
standardized
trust,
just
inform
yourselves
into
linkedin
community.
First
of
all,
I
will
approve
you
easily
there
to
be
members
and
then,
if
you
will
be
able
and
interested
of
joining
the
actual
working
group
being
active
on
guaranty
or
documentary
credit,
semantic
model
descriptions,
please
inform
me
and-
and
I
will
be
able
to
put
you
available
into
the
team.
C
Then
another
practical
case,
I'm
just
looking
to
my
my
clock
that
I'm
still
in
the
timetable.
Yes,
we
made
a
proof
of
concept
together
with
one
of
our
customers,
verzilla
in
finland,
versus
a
a
manufacturer
of
different
digital
and
physical
goods
for
marine
technology,
for
example,
and
they
also
delivering
power
plants
all
over
the
world
and
they
have
a
multitude
of
digital
services
as
well
available.
C
Scb
is,
is
the
bank
that
I'm
presenting
here,
and
we
were
the
final
sponsor
of
this
proof
of
concept
that
we
wanted
to
test
in
the
secure
corporate
data
sharing
and
and
then
we
used
the
platform
of
citra,
which
is
finnish
innovation
fund
and
the
eihan
testbed.
That
I
will
talk
about
a
little
bit
later.
C
Instead
of
sharing
documents
like
we
use
usually
do
we
have
to
do
still
in
the
letter
of
credit
when,
when
the
advising
bank
is
delivering
the
requirements
of
the
letter
of
credit
to
the
exporter,
export
a
response
by
the
documents,
and
now
we
exchanged
everything
there
into
data
sets,
and
there
are
press
releases
and
case
studies
in
details
available
for
that.
But
I
will
show
you
now
a
short
video
just
wait.
C
C
C
C
C
Yes,
so
that
was
the
case
in
the
short
video
and
let's
go
back
into
the
presentation
here.
The
key
idea,
like
you
saw
in
the
video,
is
that
we
used
open
standards
even
in
the
data
if
it
was
if
it
was
available
and
and
the
security
side
open
id,
logins
and
and
all
that
stuff
available,
and
we
even
had
a
possibility
to
go
into
further
in
in
cell
strawberry
and
identities.
C
I
will
talk
about
those
as
well,
but
we
did
this
in
a
mock-up
way
so
that
we
didn't
need
to
go
into
that
verifiable
credentials
way
of
sharing
the
the
contents
in
this
case.
But
the
key
element
here
was
that
we
were
able
to
to
run
this
case
in
the
citra
iran
testbed,
and
I
will
show
you
here.
Some
technological
features
of
that
ehan
testbed,
which
was
the
basement
for
sharing
the
the
data
and
and
the
key
element
here
is
the
data
is
not
shared
on
the
platform.
C
As
such,
it
was
really
critical
from
the
customer
side
to
say
that
none
of
this
business
critical
information
will
be
shared
on
the
day
on
the
actual
platform,
but
it
can
be
shared
only
by
a
data
owner
into
the
data
user
consumer
by
this
consensus
that
they
were
giving
to
this.
So
practically
all
that
architecture.
C
What
on
the
ehan
testbed
is
available
as
well
here
on
the
homepages,
so
you
can
also
dive
in
into
these
links
and
look
into
how
the
actual
testbed
is
working.
So
we
do
productized
apis,
meaning
standard
apis
that
will
that
are
registered
on
the
platform.
And
then
you
can
link
corporations
and
end
users
into
those
apis
and
they
limit
who
can
use
their
apis
for
different
purposes
and
the
data
products
that
are
there
are
based
on
the
the
actual
standards
as
well,
so
practically
everything
available
again
in
the
github.
C
I
will
show
you
here
the
standards
that
are
available
avail
already,
and
we
go
into
the
invoice
data
that
I
can
show
to
you
in
in
a
json
format.
This
is
not
a
any
standard
invoice
payload,
but
we
used
in
the
in
the
test.
All
the
standards
that
were
available
there,
I
can
even
show
the
ldjs
and
ld
documentation
of
this,
which
is
not
available
there
yet
on
the
internet,
but
the
the
json
ld.
The
link
data
description
is
describing
actually
the
data
elements
from
which
standard
they
are
taken
off.
C
So
we
use
the
idiom
counsel
we
used.
We
used
iso
202
and
different
other
standards
to
make
the
the
fields
available
on
any
standard
survey
on
standards
that
are
there
already
without
creating
any
any
news
stuff
that
was
needed
there.
Of
course,
we
also
wanted
to
share,
for
example,
ingo
terms,
and-
and
that
was
something
that
was
not
available
in
any
standard
yet,
but
to
create
something.
C
C
C
I
even
copied
some
facts
that
were
composed
by
the
participants
and
digital
leaving
colleagues
into
this
kind
of
analytic
analysis
of
how
these
different
platforms,
like
the
big
tech
platform,
sky
ix
and
ehan
testbed
how
they
can
compare
p,
compares
with
each
other.
So,
like
I
said
the
high
hand
test
that
is
ready
for
testing.
It
has
been
already
used
for
multitude
of
test
cases,
and
and
now,
of
course
also
there
will
be
new
cases
available
as
well,
because
it
has
been
quite
successful
in
this
proof
of
concept
working.
C
Finally,
other
enablers
that
we
will
need
in
this
digitalization
of
the
trade,
finance
and
businesses.
Overall,
I
remember
the
two
weeks
ago.
The
same
team
here
was
discussing
about
mletr,
which
is
coming
from
the
united
nations
commission
on
international
trade
law,
and
there
has
been
now
really
good
developments
from
this
2017
when
the
mletr
was
released.
Bahrain,
global
market
and
singapore
has
been
adapting
that
or
starting
to
adapt.
This
into
legal
framework
and
uk
is
now
setting
their
own
goal
for
year.
C
2020
20,
22
and
g7
just
in
in
last
month,
agreed
that
yes,
this
will
be
the
way
forward
on
these
big
countries
that
are
also
a
dominant
in
the
in
the
global
trade,
and
this
is
really
critical
for
the
development
overall
and
utilization
of
trade
finance,
and
then
we
will
need
this
trust.
So
this
is
linked
into
web
3.0
semantics.
There
is
really
important
part
and
block
called
trust
that
we
have
to
solve
that
wasn't
solved
in
the
early
days
of
development
of
internet
and
again,
wgc
is
doing
good
work
there.
C
So,
finally,
we
have
a
summary.
I
have
used
most
of
my
time,
but
I
wanted
to
conclude
in
the
end
like
a
wish
list
and
and
the
building
blocks.
First,
with
the
wishlist.
What
kind
of
companies
we
will
need
to
make
business
utilization
happen
in
practice?
It
might
be
trade
finance
digitalization.
It
can
be
whatever
other
digitalization,
but
we
need
to
have
a
common
legal
framework
so
that
we
have
a
capability
to
exchange,
not
documents
papers,
but
we
can
exchange
data
sets
instead
and
mletr
is
really
good
basement.
C
We
should
be
able
to
to
share
the
data
in
a
secure
way
with
digital
consents,
and
then
it
again
should
be
openly
available
as
a
governance
rulebook,
so
that
we
can
agree
with
the
data
sharing
network
participants
by
all
of
them.
How
we
will
do
that
until
there
will
be
maybe
some
regulation
or
law
available,
but
before
that
we
have
to
make
a
contractual
agreement,
how
to
make
the
data
sharing
happen,
because
it's
needed,
like
you
remember
from
the
beginning
of
the
presentation,
the
organizations
that
are
sharing
data
participating
in
in
data
sharing
platforms.
C
C
No
fees
included,
no
partnerships,
no
vip
memberships,
like
we
are
doing
in
the
standardized
trust
we
should
be
sharing
our
knowledge
and
expertise,
like
many
developers
nowadays
are
doing
via
kit
help
an
an
internet.
Overall.
If
you
have
a
question
regarding
changing
or
json,
ld
or
semantics
you,
you
will
find
an
answer
by
a
multitude
of
communities
using
that
and
then
I
finally
made
a
conclusion
with
the
building
blocks.
In
my
very
last
slide.
Like
lego
bricks,
we
have
uni
unigital,
mletr
trust
over
internet
protocol,
legal
entity
identifier.
C
You
can
look
into
that
verifiable
credential
proof
of
concept
that
they
did
with
the
evernim,
using
this
sovereign
foundation
and
and
blockchain
technology
there.
It's
really
fantastic
what
they
did,
and
this
will
be
the
way
of
identifying
organizations
globally
instead
of
using
national
level
identifiers.
C
Then
we
need
the
semantics
and
knowledge
graphs
to
to
fine-tune
our
data
into
level
that
can
be
used
in
artificial
intelligence.
We
need
the
secure
corporate
data
sharing
and
then
we
will
need
these
rulebooks
in
in
especially
in
in
trade
finance.
Uniform
rules,
like
icc,
has
been
always
doing
and
then
their
transformation
to
digital
world
as
well,
and
then
the
dsi
digital
trade
standard
initiative
led
by
oswald
kyler,
who
is
also
have
been
talking
to
you
here.
C
That's
really
critical
initiative
that
makes
these
standards
available
for
anyone
who
is
willing
to
develop
something
on
on
those
shipping.
The
pill
of
ladings
is
really
critical
or
for
various
cargo.
Is
it's
really
critical
for
the
trade
finance
system,
follow-ups
and
dcsa,
the
digital
container
and
shipment
association
shipping
association?
C
They
have
started
a
really
good
work
as
well,
starting
this
kind
of
standardization
and
fibo
I
was
talking
about,
and
then
we
have
bayern
network
as
well,
who
has
done
already
70
kpis
available
for
creating
infrastructures
for
for
banking
services
or
finance
services
available
by
any
kind
of
payment,
service
provider
or
bank
or
financial
institutions.
Overall.
So,
as
a
banker
or
developer
for
banks,
I
would
pref
really
recommend
to
look
into
fibo
and
buy
it
together,
and
then
we
need
collaboration
like
we
are
doing
today.
We
have
to
share
our
knowledge.
C
We
have
to
share
our
skills
and
put
them
available
on
the
same
table
and
and
start
discussing
how
to
make
these
building
blocks
available,
some
of
them
already
there.
Some
of
them
will
be
there
and
then
to
put
them
available
when
we
have
all
the
legal
framework
market
practices
uniform
rules
equipped
with
the
digital
digital
needs,
then
we
are
also
already
ready
with
the
different
different
platform
system
and
process
applications
they're
available
and
now
I
will
stop
and
leave
some
room
for
the
discussion
as
well.
B
A
I
would
like
to
to
make
a
question
taking
as
a
reference
to
slide,
which
show
which
you
showed
on
having
a
pyramid
and
showing
essentially
different
data
analysis,
perspective
or
perception
from
the
market,
and
I
would
ask
you
to
ask
in,
according
to
your
opinion,
which
kind
of
I
would
say,
level
understanding
the
trade
market.
Different
trade
market
participants
are
actually
having
to
understand
their
own
data
and
how,
as
a
community,
we
could
help
the
trade
finance
market
to
elevate
that
understanding
and
reach
the
maximum.
C
Good
good
question,
and-
and
it's
quite
funny
also
an
experience
from
our
proof
of
concept
that
when
the
corporations
are
sharing
and
we
share
the
data
between
each
other
in
trade,
finance
which
is
based
on
paper
papers
and
pdfs,
can
be
shared
without
any
concerns,
or,
let's
say,
major
conscious,
but
when
that
document,
for
example,
invoice
it's
not
on
the
paper,
but
we
compose
that
into
structured
data
set.
Suddenly
we
start
discussing
and
being
concerned
about,
is
this
relevant?
C
How
can
I
secure
that,
when
I
share
this
inbox
data
with
you
that
you
use
it
only
for
this
specific
purpose?
So,
yes,
we
start
to
understand
the
value
of
the
data
when
we
move
from
paper,
which
is
actually
a
printout
of
these
facts,
or
partly
also
information,
because
it's
a
set
of
data
already
composed
who
were
when
so
practically
we
are,
we
are.
We
are
still
in
this
area,
data
and
information
area
on
on
many
stakeholders
in
the
in
the
trade,
finance
and
even
global
trade.
C
Like
I
said,
the
the
shipping
data
is
also
there
available.
I
I
remember
dcsa
presentation
saying
that,
unfortunately,
95
of
the
documentation
in
in
the
shipping
and
logistics
is
still
on
paper,
even
though
a
good
work
has
been
done
for
standardizing
that
as
well.
But
that's
coming
from
that
that
you,
you
cannot
refer
that
into
data
sets
in
in
possible
disputes
in
any
court.
So
we
have.
We
have
a
way
to
go
to
make
semantics
work
so
that
we
can
understand
how
the
knowledge,
part
and
final
revision
part
of
the
data.
B
C
B
B
C
Finally,
when
we
are
moving
into
mlatr
type
of
implementation
in
the
legal
framework
that
will
again
enable
us
to
do
new
work
like
if
international
trade
and
for
failing
association
and
bafta
are
doing
now,
they
are.
They
are
promoting
this
digital
and
negotiable
negotiable
instrument
initiatives
also
pushing
legal
framework
to
move
forward
so
that
electronic
bill
of
ladings
can
be
used
for
automated
triggering
for
the
electronic
payment
undertaking,
so
that
automation
comes
along
and-
and
we
have
to
apply
these
into
the
uniform
rules
as
well.
C
From
the
payments
domain,
experience
of
iso
202
implementation
that
exactly
that
happened,
because
the
standard
alone
is
not
good
enough.
We
have
to
agree
by
the
market
stakeholders
how
we
use
the
standard,
so
we
have
to
agree
there's
information
and
knowledge
level
so
that
we
have
a
common
market
practice.
How
to
do
that
and
semantics
really
could
work
a
good
tool
for
doing
that.
C
So
this
is
really
critical
that
we
agree
on
on
the
market
practices
as
well,
because
that
is
the
only
way
to
avoid
fragmentation
it.
It
was
starting
to
happen
in
iso
202
use
cases
as
well.
In
the
early
days,
2005
2006
before
the
separatists
started
to
use
that
as
well.
So
we
agreed
to
make
a
market
practice
group
as
well
available
to
include
banks
and
vendors
and
end
users,
corporations
together
to
agree
on
those
rules
and
that
we
have
to
do
as
a
cooperative
work
together
in
the
trade
finance
domain
as
well.
B
B
C
I
forgot
to
show
you
a
one
picture,
which
is
a
value
network
that
we
did
in
the
virtual
proof
of
concept.
So
I
can
show
you
here.
This
was
a
collaboration
by
excellent
group
by
digital
living
international.
They
actually
build
up
from
the
two
proof
of
concept
cases:
the
lc
cases
that
we
used
in
proof,
of
course,
the
value
network.
So
this
is
describing
a
one
single
letter
of
credit,
all
these
things
in
one
letter
of
credit
documentation.
C
So
so
practically
we
have
four
layers.
We
have
banking
and
finance.
Like
you
said,
the
banks
are
there.
Then
we
have
a
business
side,
buyer
and
seller,
requiring
an
agreement
making
all
that
invoices
available
and
all
other
related
documentation,
logistics,
layer
who
is
delivering
the
goods
from
the
seller
to
the
buyer
and
then
the
manufacturing
part
which
is
producing
the
goods
that
are
delivered.
We
actually
tested
even
really
mini
scale.
C
C
So
this
is
this,
makes
the
stakeholder
value
network
visualized,
meaning
that
then,
of
course,
you
can
also
realize
that
it's
not
only
buyer
seller,
sellers
bank
and
buyers
bank
that
are
involved
in
this
global
trade.
It's
only
the
trade
finance
part
when
we
add
the
logistics
shipping,
where
we
added
the
manufacturing
park,
all
the
suppliers,
all
the
customer
side,
as
well
as
as
buyers.
C
We
actually
do-
and
I
do
that
on
my
big
day
basis,
making
the
automation
on
triggers
happening
on
on
smart
contracts
on
how
to
make
the
payments
flow
automatically,
if
all
the
terms
and
conditions
of
the
contracts
are
met
and
so
on,
and
we
have
to
break
the
layer
between
business
and
logic
side
so
that
we
have
a
capability
of
of
connecting
these
value
network
players
and
nodes
closer
to
each
other
and
automate
these
relations
between
each
other
by
standardization
and
being
and
making
that
happen
in
a
secure
way.
That
doesn't
have
to
be
compromised.
C
A
All
right
mark
here,
but
I
think,
isn't
that
one
of
the
biggest
challenges
that
we
have-
I
mean
it's
interesting
you
have
this
slide
here-
is
dated
to
new
oil.
I
got
an
interesting.
You
know
quote
during
the
week
from
margaret
investigator,
where
she
said:
data
is
not
oil,
it's
a
renewable
source
that
needs
to
be
pulled
shared
and
reused,
and
we
need
to
make
sure
that
we
make.
A
C
And
I
just
noticed,
I
didn't
share
the
screen
that
I
was
talking
to
you
just
before
you
you
coming
in
so
here
is
the
value
network
visualization
by
by
one
single
lc
and
and
then
having
this
banking
layer,
business,
layer
losses,
manufacturing
layer
and,
finally,
the
the
knowledge
graph
of
one
single
llc
showing
the
complexity
of
the
stakeholder
stakeholders
here.
So
this
is
the
power
of
knowledge
graph.
C
B
C
Any
other
comments
black
said.
I
will
share
the
presentation
to
you,
so
you
can
deep
dive
into
those
links
and
look
into
more
details
on
really
practical
level.
What
is
possible
to
do
already,
and,
of
course,
in
the
proof
of
concept,
we
will
try
to
now
make
a
experiment
viable
in
in
business-wise
commercially,
looking
into
possibility
to
fit
some
funding
and
the
participants
to
make
that
happen
in
a
larger
scale,
so
that
we
can
start
making
that
data
sharing
available
according
to
any
any
available
rules
already
so
that
we
can
start
exercising
practice.
A
A
A
Maybe
there
is
one
topic
we
didn't
discuss
here,
which
is
very
practical,
but
maybe
important
as
well
into
the
process
overall,
which
I
think
is
education
and-
and
I
mean
not
just
in
terms
of
content,
which
is
related
to
data,
but
more
from
practical
perspective.
How
bring
this
information
this
knowledge
to
the
people
to
different
people
which
have
different
different
different
resources,
different
education
as
well
different
languages.
C
Best
way
of
learning
is
is
doing
that
by
practice.
That
was
already
done
said
by
by
ancient
greek
philosopher
ferraris,
but
we
we
tend
not
to
have
time
for
upskill
ourselves,
because
we
are
too
busy
with
the
existing
processes.
So
that's
why
being
part
of
monetary
communities
and
the
upskilling
ourselves
by
by
practicing
it's
not
that
common
nowadays,
because
we
are
too
busy
and
that's
really
a
big
pity
that
we
we
do
not
have
time
for
adapting
this
new
new
technologies,
new
ways
of
working
and
doing
things
together.