1

Explicit Semantics for Business Ontology

- an interim work report fromthe Ontolog Forum

http://ontolog.cim3.net

Adam PeaseArticulate Softwareadampease@earthlink.nethttp://www.ontologyportal.org/http://home.earthlink.net/~adampease/professional/

Peter YimCIM Engineering, Inc.peter.yim@cim3.comhttp://www.cim3.com/

Presented at the “Semantics Harmonization” Panel Session of the EIDX Conference

Dec. 1, 2004 – Menlo Park, CA, USAby

v 1.00

2

Presentation Contents

• Ontolog Forum• Ontology• Suggested Upper Merged Ontology• Core Component Type

representation effort

3

Ontolog Forum (started May 2002)

• Ontolog is an open forum to:– Discuss practical issues and strategies associated with the

development of both formal and informal ontologies used in business– Identify ontological engineering approaches that might be applied to

the UBL effort (and by extension, to the broader domain of eBusiness standardization efforts)

• Virtual team collaboration with open source tools– About 100 member from 12 countries - Industry, Government, and

Academia, geographically distributed• Among ontolog’s activities: Collaboration on business ontology -

Component projects to encode a business ontology in formal logic• Acknowledgement: group participation that produced what we are presenting

here - Patrick Cassidy (Micra), Kurt Conrad (SagebrushGroup), Peter Denno (NIST), Robert Garigue (BMO), Nenad Ivezic (NIST), Holger Knublauch (Stanford-Protégé), Monica Martin (Sun), Bill McCarthy (MSU), Tim McGrath (UBL-LCSC), Garret Minakawa (Oracle), Brand Niemann (EPA), Bo Newman (KMForum), Leo Obrst (MITRE), Adam Pease (Articulate), Sue Probert (UN/CEFACT-TBG17), Steve Ray (NIST), Bob Smith (TallTreeLabs), Alan Stitzer (UN/CEFACT-CCTS), Susan Turnbull (GSA), Evan Wallace (NIST) & Peter Yim (CIM3)

4

Ontolog: CCT-Representation project

• Goal: To influence the adoption of ontology in eBusiness standards

• Mission– Ontologize ebXML Core Component Types ("CCT") – engage CCT community – produce a reference CCT ontology – report on findings and recommendations for

submission to UN/CEFACT CCTS (and possibly the Harmonization) working group(s).

• Deliverables: – a reference ontology of approved ebXML Core

Component Types ("CCTONT") – a report on findings and recommendations regarding

the current CCT specifications

5

Presentation Contents

• Ontolog Forum• Ontology• Suggested Upper Merged Ontology• Core Component Type

representation effort

6

Pursuit of Rigor in Data Standards

Old-style (most common) standards specifications: (ISO 14258, Requirements for enterprise-reference architectures and methodologies)“3.6.1.1 Time representation If an individual element of the enterprise system has to be traced then

properties of time need to be modeled to describe short-term changes. If the property time is introduced in terms of duration, it provides the base to do further analyses (e.g., process time). There are two kinds of behavior description relative to time: static and dynamic.”

Data-model standards (ISO 10303-41, Product Description and Support)ENTITY product_context SUBTYPE OF (application_context_element); discipline_type : label;END_ENTITY;

Semantic-model standards (IEEE P1600.1 - SUMO, ISO 18629-11, PSL Core)(forall (?t1 ?t2 ?t3) (=> (and (before ?t1 ?t2) (before ?t2 ?t3)) (before ?t1 ?t3))) Thanks to Steve Ray, NIST

7

Imagine...your view of the web

CV

name

education

work

private

Joe Smith

BS Case Western Reserve,1982MS UC Davis, 1984

1985-1990 ACME Software,programmer

Married, 2 children

8

...and the Computer's View

name

CV

education

work

private

9

But wait, we've got XML -

<job name=”Joe Smith” title=”Programmer”>

10

But wait, we've got XML -

<job name=”Joe Smith” title=”Programmer”>

<x83 m92=”|||||||||” title=”..............”>

11

But wait, we've got Taxonomies -

Person

Mammal

JoeSmith

12

But wait, we've got Taxonomies -

o4839

x931

i3729

13

Wait, we've got semantics -

Person

Mammal

JoeSmith

instance

subclass

implies

Mammal

JoeSmith

instance

14

Wait, we've got semantics -

Person

Mammal

JoeSmith

instance

subclass

implies

Mammal

JoeSmith

instance

u8475

x9834

p3489

r53

r22

implies

x9834

p3489

r53

15

Semantics Helps a Machine Appear Smart

• A “smart” machine should be able to make the same inferences we do

• (let's not debate the AI philosophy about whether it would actually be smart)

16

Definitions

• An ontology is a shared conceptualization of a domain

• An ontology is a set of definitions in a formal language for terms describing the world

17

Language Formality & Expressiveness

Formality

Expressiveness

Human Language OWL+RuleML, KIF

weak semanticsweak semantics

strong semanticsstrong semantics

Is Disjoint Subclass of with transitivity property

Modal Logic

Logical Theory

Thesaurus

Has Narrower Meaning Than

Taxonomy

Is Sub-Classification of

Conceptual Model

Is Subclass of

DB Schemas, XML Schema

UML

First Order Logic

RelationalModel, XML

ER

Extended ER

Description LogicDAML+OIL, OWL

RDF/S

XTM

Syntactic Interoperability

Structural Interoperability

Semantic Interoperability

Thanks to Leo Obrst, MITRE

18

Content Formality and Size

Formality

WordNet

Cyc

SUMO

DOLCE

Lexicons Formal Ontology

Taxonomy

Size

SUMO+domain

UMLSYahoo!

19

Many Ways to Use Ontology• As an information engineering tool

– Create a database schema– Map the schema to an upper ontology– Use the ontology as a set of reminders for

additional information that should be included• As more formal comments

– Define an ontology that is used to create a DB or OO system

– Use a theorem prover at design time to check for inconsistencies

• For taxonomic reasoning– Do limited run-time inference in Prolog, a

description logic, or even Java• For first order logical inference

– Full-blown use of all the axioms at run time

20

Validation (2004-11-23 Tool Screenshot)

Thanks to Peter Denno, NIST

21

CCTONT – Protégé version

Thanks to Pat Cassidy, MICRA

22

Upper Ontology

• An attempt to capture the most general and reusable terms and definitions

23

Ontology vs Language and Knowledge

Ontology

- Expandable- language independent- machine understandable

Language

- understood by humans- ambiguous

Knowledge

- changes rapidly- may be local to an entity

24

Presentation Contents

• Ontolog Forum• Ontology• Suggested Upper Merged

Ontology• Core Component Type

representation effort

25

Suggested Upper Merged Ontology

● 1000 terms, 4000 axioms, 750 rules● Mapped by hand to all of WordNet 1.6

– then ported to 2.0● A “starter document” in the IEEE SUO group● Associated domain ontologies totalling 20,000

terms and 60,000 axioms● Free

– SUMO is owned by IEEE but basically public domain– Domain ontologies are released under GNU

26

SUMO (continued)

• Formally defined, not dependent on a particular implementation

• Open source toolset for browsing and inference– https://sourceforge.net/projects/sigmakee/

• Many uses of SUMO (independent of the SUMO authors and funders)– http://www.ontologyportal.org/Pubs.html

27

WordNet

● Lexical database● 100,000 word senses – synsets● Created by George Miller's group at Princeton

● Free● De facto standard in the linguistics world

28

SUMO Structure

Structural Ontology

Base Ontology

Set/Class Theory Numeric Temporal Mereotopology

Graph Measure Processes Objects

Qualities

29

SUMO+Domain OntologyStructuralOntology

BaseOntology

Set/ClassTheory Numeric Temporal Mereotopology

Graph Measure Processes Objects

Qualities

SUMO

Mid-Level

Military

Geography

Elements

Terrorist Attack Types

Communications

People

TransnationalIssues Financial

Ontology

TerroristEconomy

NAICS TerroristAttacks

…

FranceAfghanistan

UnitedStates

DistributedComputing

BiologicalViruses

WMD

ECommerceServices

Government

Transportation

WorldAirports

Total Terms Total Axioms Total Rules 20399 67108 2500

30

Presentation Contents

• Ontolog Forum• Ontology• Suggested Upper Merged Ontology• Core Component Type

representation effort

31

ebXML Core Component Types

• Map each concept to the SUMO and its domain ontologies– 10 Core Components mapped– 43 Supplemental Components mapped– 7 terms needed to extend SUMO

• Ref. CCT-Representation Project– see: http://ontolog.cim3.net/cgi-bin/wiki.pl?CctRepresentation

32

CCT-Rep Project – Worksheet and Ontology

33

CCT-Rep Project – example: defining URI

34

CCT-Rep Project– CCT-to-SUMO Mapping

35

Issues

• Clarifying code vs. identifier– An issue of purpose not of content?– Requiring a formalization of each in logic

results in clear and unambiguous definition• Clarifying implementation vs

implementation independent semantics

36

Conclusion: Business Case• Standards development is hard work

– Most standards bodies work harder than they have to• Standards-setting bodies are susceptible to ontological gaps

– Gaps hamper progress and threaten both the expressiveness and semantic stability of the resulting specifications

• Ontologically-formalized standards should be easier to adopt – They provide numerous migration, integration, and interoperability

advantages• This approach will yield the greatest benefits when it incorporates

– conceptual modeling – ontological engineering – use of a standardized upper ontology

• An ontological engineering approach will identify knowledge gaps – which will need to be addressed, but should improve the flow of knowledge

both within the standards committee and to downstream communities• Businesses and other communities can be expected to enjoy standards

that are more stable, easier and less expensive to develop, and provide more rapid returns on investments

Source: KurtConrad-BoNewman-BobSmith