This document summarizes a presentation about the benefits of using semantic standards and technologies to make reference data more meaningful. It discusses how semantic models can extend industry standards to meet enterprise needs, and how integrating metadata and reference data through these models can achieve data harmonization. The overall approach taken is to leverage standards as much as possible through semantic representations of models, metadata, and reference data.

1. ©
TopQuadrant,
Inc.
2015
Making Reference Data More
Meaningful: Benefits of a Seman8c
Standards-­‐based Approach
Sco? Henninger PhD,
TopQuadrant, Inc.
Seman8cs in Financial & Business Systems at EDW
Organized
by
the
Enterprise
Data
Management
Council
April 1, 2015

2. Overview
v SemanGc
technology
can
easily
extend
the
standards
to
meet
enterprise-­‐specific
requirements
• enterprise
models
extending
industry
models
(FIBO,
etc.)
v Data
harmonizaGon
achieved
through
integraGon
of
metadata
and
reference
data
• enterprise
models
define
common
data
aQributes
and
relaGonships
• reference
data
define
common
values
v Overall
theme:
standards
can
get
you
a
long
ways
• semanGc
technology:
data
integraGon
and
common
representaGon
of
metadata
• reference
data:
standard
code
lists
• all
defined
in
a
common
and
standard
data
representaGon
©
TopQuadrant,
Inc.
2015
2

3. TopQuadrant
Company
• Our Mission:
Empower people
—by making enterprise information meaningful
• Our Foundation:
TopQuadrant was founded in 2001 and continues a strong
commitment to standards-based approaches to data
semantics
• Our Evolution:
Tools/Platform
Company
(2006)
Business Solution
Company
(2010 - Today)
Services
Company
(2002)

4. Emergence
of
SemanGc
Technologies
in
the
Financial
Industry
©
TopQuadrant,
Inc.
2015
4
SemanGc
Technology
Approach
• RelaGonships
between
data
is
a
first-­‐
order
representaGon,
not
an
indirect
key
• Data
integraGon
is
a
first-­‐order
representaGon:
IRIs
+
triples
• Metadata
and
data
represented
in
same
representaGon
• Human
friendly,
yet
machine-­‐
readable
IndustryModels
EnterpriseModels
Referencedata
• Efficient
access
to
integrated
enterprise
data
• Shared
meaning
of
data
• Data
harmonizaGon
• Regulatory
compliance
• …
Industry
Challenges
Data
Governance
support
• Common,
standard,
representaGon
• Data
harmonizaGon
• SemanGc
definiGons
Metadata

5. SemanGc-­‐Based
Data
Governance
v Ontologies
• Industry
models
(FIBO,
etc.)
• Enterprise
models
(organizaGonal
extensions
of
Industry
models)
• Business
unit
models
(extends
enterprise)
v Metadata
• Structural
(design
and
specificaGon
of
data
structures)
• AdministraGve
(data
governance,
stewardship,
product
classificaGons,
etc.)
• DescripGve
(defining
individual
data,
workflows,
processes)
• Provenance
(statement
reificaGon)
• metadata
standards
(ISO
11179/XMDR)
v Reference
data
• provides
context
in
which
data
is
used
(code
lists,
etc.)
©
TopQuadrant,
Inc.
2015
5

6. Enterprise
Ontologies
v Enterprise
Ontology
• collecGon
of
terms
and
definiGons
relevant
to
the
enterprise
• basis
of
shared
understanding
by
business
and
IT
• reusable
self-­‐contained
units
represenGng
business
concepts
and
enGGes
v Why
SemanGc
Technology
ontologies?
• doesn’t
have
to
be
• …but
must
be
uniquely
idenGfied
(URIs)
• …must
represent
data
relaGonships
• also
machine
interpretable
–
can
be
queried,
serviceable,
etc.
• having
the
model
and
the
metadata
in
the
same
representaGon
helps
©
TopQuadrant,
Inc.
2015
6

7. Semantic Middleware
ERP
Industry
Ontology
Models
Enterprise
Ontology
Models
PLM
CRM
Data
Warehouse
Translation
Models
SemanGc
ApplicaGon
Interaction Logic
Application Logic
Semantic Interface
WS
WS
WS
Web Services
WS
WS
WS
Adaptor
Data on the Web
Unstructured Data
(e.g. documents)
Adaptor Adaptor Adaptor Adaptor Adaptor
People
and
soiware
interact
through
the
semanGc
business
layer
with
a
uniform
interface
to
data
SemanGc
Hub
abstracts
mulGple
type
of
data
into
a
single
interface,
defines
standard
vocabularies,
formal
models
and
relaGonships
between
data
sources
Data
are
mapped
to
the
semanGc
layer
to
provide
integrated
views,
queries
and
other
services
Query Services
Result Processor
Semantic Cache
Rules Engine
Triple Store
Web Services Controller
Mapper
Acquirer
Seman8c Ecosystem
©
TopQuadrant,
Inc.
2015

8. Metadata
v Data
defining
the
semanGcs
of
data
• the
field
is
‘AU’,
but
how
can
that
be
interpreted?
• criGcal
for
supporGng
reporGng,
analyGcs,
Data
Governance
v Varies
across
contexts
• what
is
metadata
for
one
could
be
data
for
another
v Objec8ve:
Add
semanGc
meaning
to
data
©
TopQuadrant,
Inc.
2015
8

9. RepresenGng
Metadata
in
RDF
©
TopQuadrant,
Inc.
2015
9
typed
relaGonship
RelaGonship
metadata:
aQribute
and
relaGonships
• represented
as
RDF
triples
–
directly
in
the
model
• green
boxes
are
literals,
the
rest
are
objects
(resources)
idenGfied
by
URIs
cc:AU
f:Contract_1
:hasGoverningJurisdicGon
idenGfies
the
jurisdicGon
governing
the
contract,
as
agreed
by
all
parGes.
In
a
wriQen
contract
this
is
generally
idenGfied,
for
example,
as
Governing
Law,
namely
the
jurisdicGon
in
which
any
disputes
arising
from
the
contract
are
to
be
resolved.
dc:definiGon
As
modeled,
this
relaGonship
combines
two
slightly
different
senses
in
which
a
JurisdicGon
may
be
named
in
some
Contract:
the
jurisdicGon
under
whose
laws
the
contract
is
deemed
to
be
in
force,
and
the
jurisdicGon
under
which
the
parGes
agree
to
submit
in
the
event
of
any
dispute
resoluGon.
Scope
Note:
One
thing
to
tease
out
is
whether
"Dispute
ResoluGon"
and
other
forms
of
"Governing
Law"
are
one
and
the
same
thing
or
not.
Dispute
ResoluGon
is
uncontroversial,
the
quesGon
is
whether
there
are
other
implicaGons
to
Governing
Law
or
if
it's
the
same
thing.
For
instance
I
may
undertake
to
behave
as
though
I
were
responsible
to
a
parGcular
authority
i.e.
a
parGcular
set
of
statutes..
:isGovernedBy
rdfs:subPropertyOf
f:Party_1
:hasPartyInRole
has
governing
jurisdicGon
governing
jusisdicGon

10. Metadata
Case
Study
v Large
financial
company
• registry
of
data
tables
to
manage
• structural,
administraGve,
descripGve,
provenance
metadata
captured
in
spreadsheets
• use
semanGc
technology
to
merge
metadata
into
an
authoritaGve
portal
• query
the
physical
source
daily
for
excepGon
reports
• build
reports
with
SPARQL
©
TopQuadrant,
Inc.
2015
10

11. What
is
Reference
Data?
©
TopQuadrant,
Inc.
2015
11
Adds
value
to
other
business
informaGon
by:
• Meaningfully categorizing other data within enterprise applica6ons and databases.
• Rela6ng data in applica6ons to external informa6on that is rela6vely sta6c
• Sharing common meaning across the whole organiza6on and extended value-­‐net
Special
data
that
provides
a
meaningful
informaGonal
context
about
the
wider
world
in
which
the
enterprise
funcGons.
Examples:
country
codes,
currency
codes,
and
industry
codes,
etc.

12. Reference
Data
and
Data
HarmonizaGon
v Data
harmonizaGon
empowered
by
reference
data
©
TopQuadrant,
Inc.
2015
12
PO
Box
Postal
Address
Street
Address
id
Corporate
Address
Country
Name
Business
Unit
1
…
…
…
id
TransacGon
Source
Country
Business
Unit
2
Regulatory
EnGty
…
…
…
id
Corporate
JusisdicGons
Country
How to define Country?
A
country
name?
That
will
be
correct
most
of
the
Gme
• country
names
change
• misspellings,
data
entry
errors
• …

13. Reference
Data
and
Data
HarmonizaGon
v Reference
data
defines
standard
codes
©
TopQuadrant,
Inc.
2015
13
PO
Box
Postal
Address
Street
Address
id
Corporate
Address
Business
Unit
1
…
…
…
id
TransacGon
Source
Business
Unit
2
Regulatory
EnGty
…
…
…
id
Corporate
JurisdicGons
Country
Code
Country
Code
Country
Code
Country
Name
Start
Date
End
Date
Reference
Data
Country
Code
Example: AU is country code for “Australia”
• All
data
guaranteed
to
be
referring
to
the
same
enGty
• can
get
official
name(s)
from
the
reference
data
• ISO,
United
NaGons
are
most
common
sources
for
country
codes
• crosswalks
between
codes
are
common

14. Reference
Data
and
Metadata
Management
v Reference
data
is
a
good
place
to
start
a
Metadata
Management
iniGaGve
• standard
definiGons
exist
• create
policies
to
use
these
or
provide
crosswalks
• data
structures
are
not
complex
• strong
value
proposiGon
©
TopQuadrant,
Inc.
2015
14
Metadata
Reference
Data
TransacGon
Structure
Data
Enterprise
Structure
Data
TransacGon
AcGvity
Data
TransacGon
Audit
Data
Increasing:
• Volume of Data
• Popula8on Later in Time
• Shorter Life Span
Increasing:
• Per Value Data Quality Importance
• Seman8c Content
Reproduced with permission from Malcolm Chisholm

15. IntegraGng
Enterprise
Ontologies
and
Reference
Data
©
TopQuadrant,
Inc.
2015
15
Defines
“primary
key”
for
class
all
instances
named
via
a
URI
paQern,
e.g.:
hQp://www.omg.org/spec/EDMC-­‐FIBO/FND/AccounGng/Currency-­‐
Represented
as
a
URI,
using
class
paQern
subset
in
support
of
reference
data
Enterprise
Ontology
instances
of
Currency
Code
Reference
Data

16. TopBraid
Reference
Data
Manager™
(TopBraid
RDM)
makes
it
easy
to
bring
consistency
and
accuracy
to
reference
data
management
and
use.
Reference
Data
Management
©
2015
TopQuadrant
Inc
Slide
16
A collabora8ve web-­‐based
solu8on for governing and
provisioning reference data in the
enterprise:
• AuthoritaGve
Source
for
reference
data
• Governance
• Provisioning
• Enrichment
• Change
management,
audit
trails
throughout
• Data
consistency
constraints
• Comprehensive
metadata

17. Making
Reference
Data
Meaningful
©
2015
TopQuadrant
Inc
Slide
17
TopBraid
RDM
enables
more
meaningful
and
effecGve
use
of
reference
data
by
capturing
and
managing
seman&c metadata
about reference data
and also about
reference datasets

18. DescripGve
Metadata
©
TopQuadrant,
Inc.
2015
18
Metadata
about
the
reference
dataset
Metadata
for
individual
codes

19. Provenance
Metadata
©
TopQuadrant,
Inc.
2015
19
Provenance metadata
iden6fies:
• Where
the
data
comes
from
• How
it’s
obtained

20. AdministraGve
Metadata
©
TopQuadrant,
Inc.
2015
20
• Responsible
• Authorized
• Consulted
• Informed
Capture of
governance and
authority

21. © TopQuadrant, Inc. 2014
Customer
Onboarding
CRM
FRONT OFFICE
Compliance
MIDDLE OFFICE
Trading
Systems
FRONT OFFICE
BACK OFFICE
DWH
ReporGng
Web
Web
TopBraid
RDM
Reference
Data
and
Enterprise
Systems
Centralized reference data provided
…

22. Key
Concepts
for
Defining
Data
SemanGcs
v Enterprise
ontology
• comprised
of
a
set
of
industry
ontologies,
reference
data,
etc.
v Reference
datasets
• use
enterprise
ontology
to
ensure
consistency
across
the
enterprise
• consistent
URIs
meeGng
organizaGonal
or
industry
standards
• crosswalks
for
integraGng
inconsistent
data
v DefiniGonal
metadata
• define
semanGcs
of
aQribute
and
relaGonship
types
• searchable
data
about
datasets,
individual
codes
v AdministraGve
metadata
• data
governance
and
stewardship
(RACI)
v Flexible
data
provisioning
• applicaGons
“import”
full
or
subsets
of
data
based
on
search
criteria
• publish-­‐subscribe
or
publish-­‐alert
models
• record
where
reference
data
is
used
across
the
enterprise
©
TopQuadrant,
Inc.
2015
22

23. Data
SemanGcs
and
Standards
v A
lot
can
be
accomplished
with
a
few
standards
• Reference
data
as
a
well-­‐defined
jump-­‐start
to
Metadata
Management
iniGaGves
v Reference
data
and
metadata
in
support
of
data
harmonizaGon
• define
common
data
aQributes
and
relaGonships
v SemanGc
technology
support
key
data
semanGcs
concepts
• unique
idenGfiers
–
within
and
outside
of
the
organizaGon
• standards-­‐based
§ no
custom
vendor
encodings
§ reduces
vendor
lock-­‐in
©
TopQuadrant,
Inc.
2015
23

24. v Model
driven
flexibility
for
present
and
future
needs
v Empowers
data
stewardship
–
easy
maintenance
–
minimal
IT
involvement
v User
friendly
web-­‐based
UI
v Metadata
capabiliGes
v Easy
customizaGon
v Governance
For more informa8on:
rdm-­‐info@topquadrant.com
©
2015
TopQuadrant
Inc
Slide
24
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More?
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