The Financial Industry Business
Ontology
Explanatory Material
Mike Bennett, EDM Council
August 20 2012
Confidential
1
Overview
• Definition of an ontology
• Overview of classification theory
• Transformation from a taxonomy to an
ontology.
• The Financial Industry Business Ontology
(FIBO)
• From business semantics to an operational
ontology
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Data Governance
• A Bank is in essence an IT Company
– Software manufacturing
– Data production, consumption,
– Information supply chain
• So how do we manage the business
view of data?
– Language interface business to IT
– Conceptual model
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Managing Semantics
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Conceptual Model for Data
Conceptual Model (Semantics)
Realise
Logical Model (Design)
Implement
Physical Model (Implementation specific)
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Conceptual Model for Data
Business
Conceptual Model (Semantics)
The Language
Interface
Logical Model (Design)
Technology
Physical Model (Implementation specific)
FIBO bridges the “Language gap” between business and
technology
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Development Lifecycle for Data
Level
(from Zachman)
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Data
Function
0
Scope
(contextual)
Things relevant
to the business
Set of business
processes
1
Business Model
(conceptual)
Semantic Model
Functional
Requirements
(Use Case)
2
System Model
(logical)
Logical Data
Model
Logical Design
3
Technology Model Physical Data
(physical)
Model
4
Detailed
Representation
Data definition
Copyright © 2010 EDM Council Inc.
Physical Design
Program
7
Development Lifecycle for Data
Level
(from Zachman)
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Data
Function
0
Scope
(contextual)
Things relevant
to the business
Set of business
processes
1
Business Model
(conceptual)
Semantic Model
Functional
Requirements
(Use Case)
2
System Model
(logical)
Logical Data
Model
Logical Design
3
Technology Model Physical Data
(physical)
Model
4
Detailed
Representation
Data definition
Copyright © 2010 EDM Council Inc.
Physical Design
Program
8
Conceptual Model Requirements
• Must be owned and validated by
business
– Manage the “Language interface” between
tech and business subject matter experts
– Everything should be in English
• No techie terms and casing like
“objectProperty”
– Everything should be reviewable
• Spreadsheets
• dialect-free diagrams
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Industry Standards Experience
• Business knowledge gained during reviews is either
– Lost
– Buried in meeting minutes
– Kept in uncontrolled spreadsheets in a variety of structures
• Data Dictionaries try to link business definitions to
data elements
– but data elements are reused across business meanings
and usage contexts (good design again)
• Good design is weak semantics
• Industry conclusion
– “We need a semantics standard”
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Ontology
• “A formal specification of a
conceptualization”
• But
– What formalization?
– What conceptualization?
– That defines what sort of ontology
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Some Terms
• Taxonomy
– A structured classification scheme
• Linnaeus Taxonomy of Species
• Taxonomy of Financial Instruments
• Ontology
– Adds formal properties to a taxonomy
– Describes real world things
• Vocabulary or Lexicon
– Deals with the words for things
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Taxonomy
• Taxonomy:
– system that can be used to group, arrange, and
describe items according to meaningful principles,
and which provides users with an overview of the
domain being organized
• Lambe (2009)
• A taxonomy uses a classification scheme to
arrange the items in the domain of discourse
• A Taxonomy forms the basis for any ontology
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From Taxonomy to Ontology
• Ontology: the study of what is
• Ontologies (plural): the real world
universe as it is referred to in a
computer application
– Informal: every application has an
ontology, whether it’s documented or not
– Formal: uses formal logic in some notation
• Semantic Web
– Uses a formalism which can be reasoned
over
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Model Theory and Semiotics
• For any model we may ask:
– What is that to which the model elements
correspond?
– What is the formal grounding of the
symbols in the model
• For an ontology:
– The things to which the model elements
refer are real things in the domain of
discourse
– The grounding is formal logic
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Possible classes of Thing
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Example “Thing”: Equity
• Real world definition of Equity:
"An equity is a financial instrument setting
out a number of terms which define rights
and benefits to the holder in relation to
their holding a portion of the equity within
the issuing company".
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What is an Equity?
Or to put it another way…
Financial
Instrument
Equity
Is a kind of
Equity
security
In relation to
Instrument
Terms
Has rights defined in
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23 June 2010
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What is an Equity?
Using OWL to
define the classes
of real things in the
world, and the
facts about those
things
Modeled in
TopBraid Composer
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23 June 2010
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Financial Semantics in OWL
• Pizza approach
– “Everything is a Thing”
• What about common terms?
– accounting terms for equity, debt,
cashflow
– Places, time concepts
– Legal terms (securities are
contracts)
• Better partitioning needed
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The Semantic Web
• Web Ontology Language
– Based on Subject-Verb-Object “Triples”
– Widely used
• Protégé tool
• Experiment: Ingest a logical data model
into OWL
– Result: a logical data model in OWL
• Syntax is not semantics!
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Making it Meaningful
• Putting something into RDF/OWL does not
make it meaningful
– Only you can do that
• So, what is a meaningful model
– 1. Formal relationship between model and subject
matter:
• “Everything is a Thing”
– 2. Formal notation grounded in common logic
– 3. Abstraction of kinds of thing into their simplest
possible building blocks
• Contracts, Parties, Legal Entities etc.
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Theory of Meaning – in English
• The model consists of:
– Things
• A Thing is a set theory construct
• Arranged in a hierarchy called a “Taxonomy”
– Like taxonomy of species
– Facts
• Simple facts (names, dates etc.)
– e.g. “Issue Date” is a date
• Relationship Facts (relate one thing to another thing)
– e.g. “Share confers Voting Rights”
– Things so referenced are also in taxonomic hierarchies
– Other set theory concepts
• Disjoints, Unions
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Theory of Meaning – in English
• Taxonomy: Like Taxonomy of Species
– Animal v Plant
– Vertebrate v invertebrate
– Mammals, fish etc.
• Each thing is defined by what facts distinguish it
• For each new thing:
– What sort of thing is it?
– What facts distinguish it from other things?
– If an animal has a backbone, it belongs to a set of all things that are a vertebrate
– If the animal has hair, is born alive, feeds its babies with milk and has a four
chambered heart, it belongs to the set of vertebrates that are a mammal
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Applying Meaning to Financial Semantics
• Everything is a Thing
– What kind of Thing?
– What distinguishes it from other things?
• What kind of Thing?
– Share is a Security is a Transferable Contract … is
a Contract
• What properties?
– Share gives the holder some Equity
– Share confers on the holder some Voting Rights
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Where does this lead?
• Taxonomy of kinds of contract
• Taxonomy of kinds of Rights
– Rights, Obligations are similar and reciprocal
concepts
– Note that these don’t necessarily correspond to
data
• Semantics of accounting concepts
– Equity, Debt in relation to assets, liabilities
– Cashflows etc.
• Semantics of countries, math, legal etc.
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Global Terms
• Rationale:
– Everything is a specialization of some more general term
• Legal, accounting, events, transaction semantics
– Facts about instruments are stated in terms of other things
• Countries, formulae etc.
• Want to derive from and align with the best ontologies for these
area
• Disposed under a common framework
• FIBO models are extensively partitioned
• Shared Semantics:
– Align with standard ontologies where these exist
– Leverage OMG standards e.g. Date Time Vocabulary
• Work with academia and standards (ongoing)
– Transaction Semantics: REA, XBRL-GL
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Financial Industry Business Ontology
User Commitments
Original
BIAN XBRL Content
Boxes & Lines
SME Reviews
Industry
Standards
XLS
ISO 20022
FpML
MDDL
FIBO
Archetypes
Theory of meaning
UML
Tools
Sub-set for
readability
SemWeb OWL
constructs
RDF/OWL
ODM
ODM v1.1
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What we wanted
• Business meanings
• In business language
• For business people
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What we wanted
• Business meanings
– Not data dictionary
• In business language
– Not a design
• For business people
– No funny symbols and things
– No language to learn
– Just the facts
– Boxes and lines – something like this…
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Sample Screenshot
Thing
“Is A”
relations
Relationship Fact
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Example: Credit Default Swap (CDS)
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Spreadsheet
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Sample screenshot 2:
Different types of Thing
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The EDM Council
So what is FIBO
• FIBO has these distinct aspects:
– The Business Ontology
– Presentation for Business Readability
• Released in discrete ontologies by subject area
– FIBO for Business Entities is currently under
submission
– Securities, Loans, Derivatives to follow
– Corporate Actions, Transactions later
• Leverage other OMG standards and shared semantics
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From Business to Operational Ontology
• Uses for FIBO
• Semantic Technology applications
• Conceptual versus Operational
Ontologies
• Transforming from one to the other
• Use of metadata
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FIBO Application
Conventional Tech
MDR
Repository
Semantic Web
FIBO
XLS
OWL
Model
Semantic Data Model
Reasoners
Logical Data Model
Mapping
Linked Data
Semantic Query
Physical Data Model
Model Driven Development
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FIBO Application
• As a common reference point
– Mapping, integration
– Replaces ad hoc spreadsheets with a formal project
deliverable
– Extend locally for concepts within the firm
• Model Driven Development
– Position as “Business conceptual model”
– Manage the “language interface” between Business
and IT
• Semantic Technology applications
– Implemented across conventional data stores
– New application infrastructures (Triple stores)
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FIBO Semantic Technology Applications
• Model one get one free
– Full and formal representation of the business
facts as a common language across the enterprise
– Rendition of this in Semantic Web format (OWL)
opens the way to semantic technology
applications
• Formal reasoning across subject matter
• Automatic classification of product types
• Querying across subject matter
• Business Conceptual ontology (FIBO)
transformed into “Operational Ontology”
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Conceptual and Operational Ontology
• Conceptual Ontology
– Includes concepts like rights, obligations
• Meaning is grounded in law
– Does not care if it is decidable or how long it takes to reason
over it
• Operational Ontology
– Must conform with the stated technical constraints
• Reasoning
• Decidability
– Combines
• ontology (classes) with
• “individuals” (instance data in triple store format)
• How to get from one to the other?
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How to get from one to the other
• Select a single classification facet
• Collapse the taxonomy above the domain
• Ignore terms which do not correspond to data
– Rights and obligations
– Policies, strategies, goals
• Identify those terms which correspond to instance
data
– For most rights and obligations, some data signature is likely
to be present
• Use property chaining in the conceptual ontology to
relate several more abstract but meaningful
properties, with one concrete and data-focused
property which can be processed.
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Ontology Metadata
• Standard metadata for definitions,
notes, provenance etc.
• Additional metadata for mapping,
regulatory cross reference etc.
• Available in OWL versions of FIBO
– Annotation Properties: not reasoned over
– Object Properties: seen by reasoner
– Both are visible to semantic querying
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Provisional Roadmap
2012
2013
Q1
FIBO-Foundations
Global Terms and modeling
framework
FIBO Business Entity
Domain ontology
Q2
Beyond
Q3
Industry
review
OMG
finalization
Final
Industry
review
OMG
finalization
Final
FIBO Securities
Domain ontology
FIBO Derivatives
Domain ontology
Q4
Industry
review
OMG
finalization
Final
Industry
review
OMG
finalization
Final
FIBO Loans
Domain ontology
Industry
review
OMG
finalization
Final
FIBO Market Data, CAE, Portfolio, Payments
Other Domain
ontologies
FIBO Market
Data, CAE,
Risk/Reporting
Other Domain
ontologies
FIBO Market
Data, CAE,
Risk/Reporting
Other Domain
ontologies
FIBO Market
Data, CAE,
Risk/Reporting
Other Domain ontologies
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Co
pyri
ght
©
201
0
ED
M
Deliverables
Adaptive: Webaccessible FIBO
presentation
FIBO Business Conceptual
Ontology (BCO)
FIBO OMG Specifications
FIBO Foundations
FIBO for Business Entities
Etc.
Operational Ontology
(main business use case – common
reference and querying across multiple
data sources)
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Operationa
l Ontology
Operation
al
Ontology
Main Take-away Points
• An ontology extends a taxonomy which is organized according
to some classification principles
• An ontology is not another sort of data model
– It does not replace or displace messaging standards,
database schemes or anything else
– Common semantics is about the business view of what’s in
data
– Enables mature approach to technology management
• Putting it in a SemWeb tool doesn’t make it meaningful
– You do
• Two ways to leverage FIBO
– Common semantics
– Semantic Technology applications
• Regulators and the industry are paying attention!
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Contact
• Mike Bennett
– [email protected]
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