Confidential 111 The Financial Industry Business Ontology Explanatory Material Mike Bennett, EDM Council August 20 2012

Confidential111

The Financial Industry Business Ontology

Explanatory Material

Mike Bennett, EDM Council

August 20 2012

ConfidentialConfidential

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

ConfidentialConfidential 3Copyright © 2010 EDM Council Inc.

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


Managing Semantics


Conceptual Model for Data

Conceptual Model (Semantics)

Logical Model (Design)

Physical Model (Implementation specific)

Realise

Implement


Conceptual Model for Data

Conceptual Model (Semantics)

Logical Model (Design)

Physical Model (Implementation specific)

The Language Interface

Business

Technology

FIBO bridges the “Language gap” between business and technology


Development Lifecycle for Data

Level (from Zachman)

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)

Physical Data Model

Physical Design

4 Detailed Representation

Data definition Program


Development Lifecycle for Data

Level (from Zachman)

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)

Physical Data Model

Physical Design

4 Detailed Representation

Data definition Program


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


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”


Ontology

• “A formal specification of a conceptualization”

• But– What formalization?– What conceptualization?

– That defines what sort of ontology

11Copyright © 2010 EDM Council Inc.


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



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



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



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


ConfidentialConfidential 23 June 2010 16

Possible classes of Thing


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".


What is an Equity?

Or to put it another way…

Equity

Equity security

Instrument Terms

Financial Instrument

Is a kind of

Has rights defined in

In relation to


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


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


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!


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.


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


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


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



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.



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


Financial Industry Business Ontology

FIBO

IndustryStandards XLS

Boxes & LinesUser CommitmentsOriginal Content

ISO 20022

FpML

XBRL

SemWeb OWL constructs ODM

UML Tools

MDDL

Sub-set for readability

Theory of meaning

SME Reviews

ODM v1.1

Archetypes

RDF/OWL

BIAN


What we wanted

• Business meanings

• In business language

• For business people


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…


Sample Screenshot

Thing

“Is A” relations

Relationship Fact


Example: Credit Default Swap (CDS)


Spreadsheet

ConfidentialConfidential The EDM Council Semantics Repository

Sample screenshot 2: Different types of Thing


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


From Business to Operational Ontology

• Uses for FIBO

• Semantic Technology applications

• Conceptual versus Operational Ontologies

• Transforming from one to the other

• Use of metadata



FIBO Application

FIBOConventional Tech Semantic Web

Repository

Semantic Data Model

Logical Data Model

Physical Data Model

MDR XLS

Mapping

Model Driven Development

OWL Model

Reasoners

Linked Data

Semantic Query


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)


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”


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?



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.



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



Provisional Roadmap

43

Copyright

© 201

0 ED

M Co

uncil

Inc.

FIBO Market Data, CAE, Risk/ReportingOther Domain ontologies






2012 2013 Beyond

FIBO-FoundationsGlobal Terms and modeling

framework

FIBO-FoundationsGlobal Terms and modeling

framework

FIBO Business EntityDomain ontology

FIBO Business EntityDomain ontology

FIBO SecuritiesDomain ontology

FIBO SecuritiesDomain ontology

FIBO DerivativesDomain ontology

FIBO DerivativesDomain ontology

FIBO LoansDomain ontology

FIBO LoansDomain ontology

FIBO Market Data, CAE, Portfolio, PaymentsOther Domain ontologies

FIBO Market Data, CAE, Portfolio, PaymentsOther Domain ontologies

Industry review

Industry review

Industry review

Industry review

Industry review

OMG finalization

OMG finalization

OMG finalization

OMG finalization

OMG finalization

FinalFinal

FinalFinal

FinalFinal

FinalFinal

FinalFinal

Q1 Q2 Q3 Q4


Deliverables

44

FIBO Business Conceptual Ontology (BCO)

Adaptive: Web-accessible FIBO

presentation

FIBO OMG Specifications

FIBO FoundationsFIBO for Business Entities

Etc.

Operational Ontology(main business use case – common

reference and querying across multiple data sources)

Operational Ontology

Operational

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!


Contact

• Mike Bennett– [email protected]


Documents

Confidential 111 The Financial Industry Business Ontology Explanatory Material Mike Bennett, EDM Council August 20 2012