The Ontology Definition Metamodel
An MDA-based Framework for Semantic
Interoperability
Elisa Kendall
Sandpiper Software
March 21, 2006
Model Driven Architecture® (MDA®)
 Insulates business applications from technology
evolution, for
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Increased portability and platform independence
Cross-platform interoperability
Domain-relevant specificity
 Consists of standards and best practices across a
range of software engineering disciplines
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The Unified Modeling Language (UML®)
The Meta-Object Facility (MOF™)
The Common Warehouse Metamodel (CWM™)
 MOF defines the metadata architecture for MDA
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Database schema, UML and ER models, business and
manufacturing process models, business rules, API
definitions, configuration and deployment
descriptors, etc.
Supports automation of physical management and
integration of enterprise metadata
MOF models of metadata are called metamodels
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MOF-Based Metadata Management
 MOF tools use metamodels to generate code
that manages metadata, as XML documents,
CORBA objects, Java objects
 Generated code includes access mechanisms,
APIs to
– Read and manipulate
– Serialize/transform
– Abstract the details based on access
patterns
Model 1
Metamodel A
source language
Transformation Model
 Related standards:
– XML Metadata Interchange (XMI®)
– CORBA Metadata Interface (CMI)
– Java Metadata Interface (JMI)
 Metamodels are defined for
– Relational and hierarchical database
modeling
– Online analytical processing (OLAP)
– Business process definition, business
rules specification
– XML, UML, and CORBA IDL
language used
transformation
target language
Model 2
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language used
Metamodel B
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Production Rules RFP
Ontology Definition Metamodel
Semantics for Business Vocabularies
& Rules
OMG Standards & Zachman Framework
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MDA from the KR Perspective
 EII solutions rely on strict adherence to agreements based on
common information models that take weeks or months to build
 Modifications to the interchange agreements are costly and time
consuming
 Today, the analysis and reasoning required to align multiple
parties’ information models has to be done by people
 Machines display only syntactic information models and informal
text describing the semantics of the models
 Without formal semantics, machines cannot aid the alignment
process
 Translations from each party’s syntactic format to the agreed-upon
common format have to be hand-coded by programmers
 MOF® and MDA® provide the basis for automating the syntactic
transformations
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MOF and KR Together
 MOF technology streamlines the mechanics of managing models as XML
documents, Java objects, CORBA objects
 Knowledge Representation supports reasoning about resources
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Supports semantic alignment among differing vocabularies and
nomenclatures
Enables consistency checking and model validation, business rule analysis
Allows us to ask questions over multiple resources that we could not answer
previously
Enables policy-driven applications to leverage existing knowledge and
policies to solve business problems
• Detect inconsistent financial transactions
• Support business policy enforcement
• Facilitate next generation network management and security applications
while integrating with existing RDBMS and OLAP data stores
 MOF provides no help with reasoning
 KR is not focused on the mechanics of managing models or metadata
 Complementary technologies – despite some overlap
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Metadata Management Scenarios
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Level Setting
An ontology specifies a rich description of the
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Terminology, concepts, nomenclature
Properties explicitly defining concepts
Relations among concepts (hierarchical and lattice)
Rules distinguishing concepts, refining definitions and relations
(constraints, restrictions, regular expressions)
relevant to a particular domain or area of interest.
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Ontology-Based Technologies
 Ontologies provide a common vocabulary and definition of rules for
use by independently developed resources, processes, services
 Agreements among companies, organizations sharing common services
can be made with regard to their usage and the meaning of relevant
concepts can be expressed unambiguously
 By composing component ontologies, mapping ontologies to one
another and mediating terminology among participating resources and
services, independently developed systems, agents and services can
work together to share information and processes consistently,
accurately, and completely.
 Ontologies also facilitate conversations among agents to collect,
process, fuse, and exchange information.
 Improve search accuracy by enabling contextual search using concept
definitions and relations among them instead of/in addition to
statistical relevance of keywords.
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Classifying Ontologies
Classification techniques are as diverse
as conceptual models; and generally
include understanding
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Methodology
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Target Usage
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Level of Expressivity
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Level of Complexity
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Reliability / Level of Authoritativeness
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Relevance
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Amount of Automation
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Metrics Captured and/or Available
KR System
OO Software Model
Level of Expressivity
Entity – Relationship
Model
Concept Map
Topic Map
Database Schema
XML Schema
Hierarchical Taxonomy
Simple Taxonomy
Glossary
Level of Complexity
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MDSW Representation Framework
Description Logics
 W3C Resource Description
Framework (RDF)
 W3C Web Ontology
Language (OWL)
First-Order / Higher Order Logic
 ISO Common Logic (ISO FCD
24707)
MOF/UML
Topic-based Categorization
 ISO Topic Maps (ISO 13250-2)
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Ontology Definition Metamodel
 Five EMOF platform independent metamodels (PIMs),
four normative
 Mappings (MOF QVT)
 UML2 Profiles
– RDFS & OWL
– TM
<<metamodel>>
CL
(from org.omg.odm)
<<metamodel>>
DL
(from org.omg.odm)
<<metamodel>>
RDF
(from org.omg.odm)
(non-normative)
<<metamodel>>
TM
(from org.omg.odm)
 Collateral
– XMI
– Java APIs
– Proof-of-concepts
<<metamodel>>
RDFS
(from RDF)
<<merge>>
<<metamodel>>
RDFBase
(from RDF)
 Conformance
– RDFS & OWL
– Multiple Options
– TM, CL Optional
– Informative Mappings
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<<metamodel>>
RDFWeb
(from RDF)
<<merge>>
<<merge>>
<<merge>>
<<metamodel>>
OWL
(from org.omg.odm)
<<metamodel>>
OWLBase
(from OWL)
<<merge>>
<<metamodel>>
OWLDL
(from OWL)
<<merge>>
<<metamodel>>
OWLFull
(from OWL)
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ODM Status
 Several revision cycles on the specification
 Informative discussions of Usage Scenarios, differences between
UML & OWL
 Platform Independent (Normative) Metamodels (PIMs) include
– RDF & OWL – abstract syntax, constraints for OWL DL & OWL
Full, several compliance options
– ISO Common Logic (CL)
– ISO Topic Maps (TM)
 Informative Models
– DL Core – high-level, relatively unconstrained Description
Logics based metamodel (non-normative, informational)
– Identifier (keys) model extension to UML for ER
 Latest revised submission posted 11/14 to the OMG web site
(http://www.omg.org/docs/ad/05-09-08.pdf)
 Update to include minor metamodel changes, QVT mappings,
revised profile for St. Louis OMG Meeting (4/23/06)
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Bridging KR and MDA
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Relationship to Other OMG Standards
Mapping via W3C RIF
BMI Semantics for Business Vocabularies
& Rules (SBVR)
BMI Production Rule Representation (PRR)
Formal Grounding (CL)
Vocabulary in ODM
Rules in PRR
Ontology Definition Metamodel
ODM extensions planned
∞ Mapping from CL to RDF/S & OWL
∞ Support for Semantic Web Services Language, with bindings to WSDL & SOAP
∞ Mappings for W3C Rule Interchange Format (RIF) (i.e. vocab/ontology  rules)
∞ Mappings for Emerging OMG Information Management Metamodel (CWM2)
∞ New requirements from SOA ABSIG anticipated
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Relationship to ISO Standards
 CL Metamodel is included in ISO FCD 24707
 High degree of synergy between ODM and Topic Maps ISO FCD
13250-2 working group
 All ODM metamodels are referenced and used in ISO FCD 19763
(MMF – Metamodel Framework, Model Registry specification)
 All ODM metamodels inform latest modifications proposed in ISO
draft 11179 Metadata Registration specification
 ODM team is working with DoD XMDR team to promote
interoperability among ODM, 19763, 11179 efforts
 Current work in OMG (IMM) to develop a metamodel for ISO
Express will include mappings to ODM
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Complementary Concerns
Ontology-based Registries for
Semantic Interoperability
Information Resource (e.g. GILS, 19763, IW)
& Terminology Registries (e.g. 11179, SKOS,
WordNet, Thesauri)
Semantic Process Registry
(e.g. ISO PSL, BPEL)
Semantic Service Registry
(e.g. OWL-S, SWSF, WSMO)
 Semantically grounded information &
terminology registries, integrated /
mapped to other MOF models & MOFbased applications provide basis for
information interoperability
 Semantics for process representation
support automated process choreography,
composition, interoperability across
business segments
 Semantic service registries provide rich
descriptions of capabilities
(ServiceProfile), implementation
(ServiceModel), access & interoperability
(ServiceGrounding) to support service
discovery, invocation, composition
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Business Integration Summary
 Semantic Web Services standards are converging
 OMG RFP forthcoming for extensions to ODM to support W3C
Semantic Web Services, ISO EXPRESS, eventually W3C RIF
 OMG BMI DTF Semantics for Business Vocabularies & Rules (SBVR) is
logically grounded in Common Logic / ODM CL Metamodel
 Planned mapping to forthcoming Production Rule Representation
(PRR) specification
 Planned mappings to structured, semi-structured resources via IMM
 Leverage mapping from UML for BPEL to ODM extensions (e.g., to
the PSL component of SWSF)
 Strategy:
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Link business process models through MOF environment
Generate OWL for the linkage
Use linkage as basis for mediating business process semantics
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A Framework for
Next Generation Interoperability
 MOF’s model management facilities and KR capabilities for
machine interpretable semantics and reasoning are
separate, complementary concerns
 The ability of reasoners to find discrepancies in invariant
rules, preconditions, and post conditions, can add scalability
to MDA’s use of Design-by-Contract (DBC)
 UML profiles can serve as graphical notations for Semantic
Web languages, dramatically increasing ease of use
 The combination of MDA and SW technologies promises to
– Address the missing link in business process automation
– Enable true information interoperability and continuity
– Support next generation policy-based applications development
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The Model-Driven Semantic Web
 Knowledge acquisition, developing the semantics is the
bottleneck
 Leveraging existing assets breaks that bottleneck
 Correlation through reasoning provides the utility
– Multi-dimensional, cross organizational tailored semantic views
– “Virtual” repository approach enables elimination of
redundancy
– Reasoning supports quality initiatives through inconsistency
discovery, model and content validation
 MDA and MOF coupled with semantic technologies are the
key
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Ontologies for Web Services
 Ontologies provide a common vocabulary and definition of rules
for use by independently developed services
 Companies and organizations sharing common services can
declaratively specify the behaviors, policies and agreements
relevant to their usage
 Through ontology composition, mapping and vocabulary
brokering for participating resources and services,
independently developed services can share information and
processes consistently, accurately, and completely
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OWL-S: Enabling Infrastructure for Web Services
 Emerging work based on research from the DARPA/DAML
program in DAML-S (2000/2001 – SRI, Stanford, CMU)
 OWL-S – an ontology that sits at the application level, above
WSDL, and describes what is being exchanged and why, not
just the how
 OWL-S enables
– discovery – of services that meet particular requirements and
adhere to specified constraints
– invocation – and execution by agents or other services
– interoperation – through specification of the appropriate
vocabularies (semantics) and message parameter translation as
required based on service specifications
– composition – automated service composition and interoperation
to provide new services
– verification – of service properties
– execution monitoring – tracking of execution of complex services
and transactions
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OWL-S Structure
 Two essential types of knowledge about services
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The what, its capabilities and parameters, through a ServiceProfile,
which can answer questions such as what does the service require of
agents and provide for them
The how, through a ServiceModel that describes the workflow and
possible execution paths
 Service profiles are used to request or advertise services with
discovery services and capabilities registries, including
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Descriptions of services and providers
Functional behavior
Functional attributes
 Service models describe the operation of a web service through a
process model of the control and data flow structure of the service
 OWL-S complements WSDL by providing an abstract or application
level description lacking in WSDL
 Current specifications available at http://www.daml.org/services/
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Semantic Web Services Framework
 Emerged from work in services composition
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Requiring more expressivity than was available in OWL
First order logic approach
Based on significant work in logic programming, government funded policy
work
 Considered the smorgasbord of relevant standards
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Web Services Description Language (WSDL) – for specifying input & output
message, invocation (W3C)
Business Process Execution Language for Web Services (BPEL4WS) – addresses
specification of workflows of basic services (OASIS)
Choreography Description Language (WS-Choreography) – supports a more
global view information exchange from a transaction perspective (W3C)
UDDI provides a standard approach for service registration, discovery, and
advertizing
 Integrates notions from prior initiatives, builds on DAML-S, OWL-S, WSMO
 Provides rich semantics for greater automation of service discovery,
selection and invocation, content transformation, composition,
monitoring & recovery, verification
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Semantic Web Services Framework
SWSL & SWSO
 Semantic Web Services Language (SWSL)
– SWSL-FOL – first order language for ontology representation,
builds on CL
– SWSL-Rules – logic programming to enable ontology use in
reasoning and execution environments
 Semantic Web Services Ontology (SWSO)
– Conceptual model, complete axiomatization expressed in
SWSL-FOL
– Called FLOWS – First-Order Logic Ontology for Web Services
– Includes model theoretic semantics
– Ontology translated to SWSL-Rules is slightly more constrained,
– Called ROWS – Rules Ontology for Web Services
 W3C Note (proposal for recommendation made recently),
additional references available at
– http://www.w3.org/Submission/SWSF/
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Current Status
 Several candidate standards recently submitted to
W3C (OWL-S, SWSF, WSMO, WSDL-S)
 Workshop on creating a Semantic Web Services
working group held Spring 2005
 Draft charter for working group currently under
development
 Process is likely to move forward in early 2006, 2
year preliminary timeline to complete standards
work
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Opportunity for OMG
 Potential for extensions to ODM to support
– OWL-S, building on the RDF & OWL metamodels
– SWSF, building on the CL metamodel, with mappings to
OWL-S
– Mappings to standardize bindings to WSDL, SOAP
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