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The Model-Driven Semantic WebEmerging Technologies & Implementation Strategies
Elisa KendallSandpiper Software
September 8, 2005
2Copyright ©2005 Sandpiper Software, Inc.
Model Driven Architecture® (MDA®)
Insulates business applications from technology evolution, for
– Increased portability and platform independence– Cross-platform interoperability– Domain-relevant specificity
Consists of standards and best practices across a range of software engineering disciplines
– The Unified Modeling Language (UML®)– The Meta-Object Facility (MOF™)– The Common Warehouse Metamodel (CWM™)
MOF defines the metadata architecture for MDA
– 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
3Copyright ©2005 Sandpiper Software, Inc.
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 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
Model 1
Model 2
Metamodel A
Transformation Model
Metamodel B
language used
language used
transformation
source language
target language
4Copyright ©2005 Sandpiper Software, Inc.
The Semantic Web
"The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation."
-- Tim Berners-Lee
“the wedding cake”“the bus”
5Copyright ©2005 Sandpiper Software, Inc.
Level Setting
An ontology specifies a rich description of the 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.
6Copyright ©2005 Sandpiper Software, Inc.
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.
7Copyright ©2005 Sandpiper Software, Inc.
Semantic Web Evolution
Draft specifications for RDF/S & OWL became formal W3C Recommendations in February 2004
Increasingly attention is on applications and deployment strategies, moving from research to early adoption
Research from the DAML community and W3C is now focused on– Methodology & best practices – representing value spaces,
complex relations, engineering methods, applications with richly specified ontologies
– Query and rule languages– Tools and development resources
• Parsers and Validators• Authoring Tools for ontologies and mark-up• Ontologies, knowledge bases, and libraries
– Interaction with SOAP/WSDL to support Semantic Web Services (OWL-S, SWRL)
8Copyright ©2005 Sandpiper Software, Inc.
Guiding Principles
Historically, knowledge representation and reasoning systems have operated under closed world assumptions
Uncertainty is magnified under open-world, “wild, wild web” conditions, making reasoning more difficult
Semantic web languages are designed to support less certainty, provide “better” search results, informed answers to questions, not absolutes
Based on XML, they can assist businesses in leveraging mark-up, content, and data – To augment business intelligence/analysis and knowledge mining – To support knowledge sharing and collaboration, augment
enterprise information integration – Enrich web services and other applications – Support policy-based applications and ensure compliance with
policy
at a lower cost with higher potential ROI than traditional computing methods
9Copyright ©2005 Sandpiper Software, Inc.
Cost of Knowledge Capture Most tools are oriented towards taxonomy or limited ontology
formation vs. knowledge base development, terminology reconciliation, or alignment
They require significant knowledge of formal logic and domain analysis from an ontological perspective
Few are graphical and/or standards based
Vulcan estimates the cost of encoding 50 pages of basic high school chemistry textbook knowledge at $10,000 per page*
Tools to assist subject matter experts (SMEs) in encoding knowledge, including increasing automation in developing the starting points for ontology and KB development are essential
Combining MOF® and MDA® technologies with KR dramatically reduces cost, increases likelihood of success, increases availability to a much broader community of potential users
* See Vulcan, Inc. – Project Halo, at http://www.projecthalo.com/
10Copyright ©2005 Sandpiper Software, Inc.
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
11Copyright ©2005 Sandpiper Software, Inc.
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– 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
12Copyright ©2005 Sandpiper Software, Inc.
Metadata Management Scenarios
13Copyright ©2005 Sandpiper Software, Inc.
Classifying Ontologies
Level of Complexity
Level of
Expre
ssiv
ity
Simple Taxonomy
Glossary
Topic Map
Concept Map
Hierarchical Taxonomy
Entity – Relationship Model
Database Schema
OO Software Model
KR System
XML Schema
Classification techniques are as diverse
as conceptual models; and generally
include understanding
Methodology
Target Usage
Level of Expressivity
Level of Complexity
Reliability / Level of Authoritativeness
Relevance
Amount of Automation
Metrics Captured and/or Available
14Copyright ©2005 Sandpiper Software, Inc.
Model Dynamics
Model centric perspectives characterize the ontologies themselves and are concerned with their structure, formalism and dynamics.
Perspective
Level ofAuthoritativeness
Source of Structure
Degree of Formality
Model Dynamics
Instance Dynamics
One Extreme
Least authoritative, broader shallowly defined ontologies
Passive (Transcendent) - Structure originates outside the system
Informal or primarily taxonomic
Read-only, ontologies are static
Read-only, resource instances are static
Other Extreme
Most authoritative, narrower, more deeply defined ontologies
Active (Immanent) - Structure emerges from data or behavior
Formal, having rigorously defined types, relations, and theories or axioms
Volatile, ontologies are fluid and changing
Volatile, resource instances change continuously
15Copyright ©2005 Sandpiper Software, Inc.
Application Characteristics
Application centric perspectives are concerned with how applications use and manipulate ontologies.
Perspective
Control/Degree
of Manageability
ApplicationChangeability
Coupling
Integration Focus
Lifecycle Usage
One Extreme
Externally focused, public(little or no control)
Static (with periodic updates)
Loosely-coupled
Information integration
Design Time
Other Extreme
Internally focused, private(full control)
Dynamic
Tightly-coupled
Application integration
Run Time
16Copyright ©2005 Sandpiper Software, Inc.
Ontologies have well-defined, formal semantics:– To support reasoning– To represent shared semantics for intelligent agents or semantic
web services– To represent declarative policies (with legal implications, such as
regulatory policies)
Elements frequently cross meta-levels or apply at multiple levels (e.g., act as a class and as an individual at the same time)
Reuse of complex relationships and axioms is critical to successful development:– Relations are first class elements– Associations in UML2 are insufficient to meet this need
Individuals may be specified independently and may have properties that are not properties of the classes of which they are members (e.g., owl:sameAs, owl:differentFrom)
Knowledge Representation vs. UML
17Copyright ©2005 Sandpiper Software, Inc.
Forward & reverse engineering of source material and ontologies
Support ontologies expressed in existing description logics (e.g., OWL DL) and a limited set of higher order languages (e.g., OWL Full, Common Logic)
UML Profiles vs. Metamodels– Both are required due to structural and semantic distinctions
between KR languages and UML– Metamodels precisely represent the abstract syntax– Profiles facilitate use of UML notation and “code” generation
Extending the UML2 metamodel vs. new, distinct metamodels– Extension would introduce unnecessary complexity, unintended
semantics
Should there be a core ODM metamodel that the others extend?– No obvious commonalities– Goal was to be true to the abstract syntax and formal semantics of
the selected KR languages – without unnecessary complexity
Design Rationale
18Copyright ©2005 Sandpiper Software, Inc.
Towards a Model Driven Semantic Web – Ontology Definition Metamodel Six EMOF platform independent metamodels,
(PIMs), five normative Mappings (MOF QVT Relations Language
planned) UML2 Profiles
– RDFS & OWL– TM
Collateral– XMI– Java APIs– Proof-of-concepts
Conformance– RDFS & OWL– All else optional
TM<<metamodel>>
DL<<metamodel>>
ER<<metamodel>>
SCL<<metamodel>>
RDFS<<metamodel>>
OWL<<metamodel>>
Ontology Definition Metamodel
Completed/Included Mapping Planned Mapping
UML<<metamodel>>
(nonnormative)
CL<<metamodel>>
19Copyright ©2005 Sandpiper Software, Inc.
Subclassing vs. Mapping– OWL metamodel depends on RDFS metamodels– All others are related through mapping (non-normative)
Naming– Namespaces are defined at the package level in UML & MOF– Namespaces are global in RDFS/OWL, CL, & TM
Associations– Relations and Properties are “first class entities” in RDFS/OWL & CL– AssociationEnds must be defined in UML (requires model library)– Inheritance of features, attributes (slots), axioms, other relevant
production rules on associations is poorly supported in UML2, not at all previously (requires use of UML2 properties, association classes)
Packaging– Discussions underway to resolve RDF/S packaging structure– RDF Schema & RDF Syntax, or possibly 3 packages
OCL is insufficiently rich to support rules, axioms
Impedance Mismatches & Issues
20Copyright ©2005 Sandpiper Software, Inc.
Provide standard UML notation for each of the languages
RDFS/OWL was highest priority based on RFP
Topic Maps was high priority based on user community input
What about ER and CL?– ER has an existing graphical notation, though no “standard”
notation – a profile will likely be done under a broader data modeling standardization effort (forthcoming – CWM2)
– CL was originally included for constraint/rule representation; profile requested due to its utility for BSBR and interoperability with other ISO efforts; will follow through an RFC/RFP process
Essentially a one-to-one mapping from concrete meta-model element to stereotype
Abstract meta-classes contribute to base classes for stereotypes
ODM Profiles
21Copyright ©2005 Sandpiper Software, Inc.
OWL Full was selected as the core ODM metamodel to limit NxN mapping requirements
Final specification will include – Two-way mappings from UML2, TM, & ER to RDFS/OWL– One-way mapping from RDFS/OWL to CL– Reverse (lossy) mapping from CL to RDFS/OWL may be
done through RFP/RFC– Two-way mapping from UML2 to CL (lossy) may be done
through RFP/RFC
Current mapping representations include tables, abstract syntax, an interim QVT notation (i.e., inconsistent)
Plans include migration to emerging MOF Query / View / Transformation (QVT) Relations Language
ODM Mappings
22Copyright ©2005 Sandpiper Software, Inc.
Bridging KR and MDA
23Copyright ©2005 Sandpiper Software, Inc.
Technology Architecture
24Copyright ©2005 Sandpiper Software, Inc.
ODM Status
Several revision cycles on the specification to date
Informative discussions of usage scenarios, differences between UML & OWL
Platform Independent Metamodels (PIMs) include– Resource Description Framework and Web Ontology
Language (covers abstract syntax, common concrete syntactic elements from both)
– Common Logic (CL), based on draft ISO CD 24707– Topic Maps (TM), based on draft ISO FCD 13250-2
specification– ER – based on de facto industry standards– DL Core – high-level, relatively unconstrained Description
Logics based metamodel (non-normative, informational)
Revised submission (next iteration) will be posted by 11/14/05 to the OMG web site
Presentation on 8/22 revision planned for OMG Atlanta meeting (September 12-16 – see http://www.omg.org/docs/ad/05-08-01.pdf)
Plans for recommendation / vote for adoption December meeting
25Copyright ©2005 Sandpiper Software, Inc.
Implementation Strategies
Native OWL Tool UML Tool with ODM Plug-In
Ontology Analysis & Validation
Java Theorem Prover(JTP)
Hybrid Reasoning System
Use Reasoning to Find Inconsistencies
Validate Logic, Policies
MOF RepositoryTools
XMI Representation Enables Use in Eclipse/EMF, MOF-Based Tools
Link ODM Models (conceptual / semantic) To logical (ERWIN, Rose) and physical models (ERWIN, Rose,
Power Designer)
MOF/ODM –OWL Bridge
Use UML to Refine Linkage Ontologies
Use Links / Mappings to Find & Eliminate Redundancies
thru Reasoning
Use Links / Mappings For Query Planning, Business
Intelligence
RDFS/OWL
26Copyright ©2005 Sandpiper Software, Inc.
Related OMG Standards Work
Business Semantics for Business Rules – Emerging standard, Semantics for Business Vocabularies &
Rules (SBVR) – Depends on the ODM CL Metamodel for logical grounding
Production Rules Representation– Emerging standard, preliminary presentation in Atlanta 9/12– Discussions in progress to relate PRR to CL
CL will provide the logical foundation for all OMG ontology and rules related standards
Mappings between ODM & SBVR, ODM & PRR, ODM & EXPRESS are planned
Relationship to emerging W3C standards for rules, semantic web services will depend on how the standards evolve
Plan in Ontology PSIG is to extend or build on ODM to support both rules and semantic web services vocabularies, potentially other vocabularies as they are developed
27Copyright ©2005 Sandpiper Software, Inc.
OMG Standards & Zachman Framework
Pro
du
cti
on
Ru
les
RF
P
Se
ma
nti
cs
fo
r B
us
ine
ss
Vo
ca
bu
lari
es
& R
ule
s
Ontology Definition Metamodel
28Copyright ©2005 Sandpiper Software, Inc.
Related ISO Metadata Standards
ISO/IEC 11179 – Metadata Registries– Part 2: Classification for Administered Items– Part 3: Registry Metamodel & Basic Attributes
ISO/IEC 19763 – Framework for Metamodel Interoperability– Part 3: Metamodel Framework for Ontology Registration
(depends on ODM Metamodels, ISO 11179 classification)– Part 4: Metamodel Framework for Mapping (depends on
MOF QVT specification)
XMDR Program – Extended Metadata Registration– OWL ontologies for ISO 11179 Part 3, related MMF
elements– discussions bridging the standards are underway– Liaison meeting (ODM, ISO, XMDR) planned for 9/22-23
in Toronto prior to ISO WG meeting
29Copyright ©2005 Sandpiper Software, Inc.
Business Integration
Semantic Web Services standards are converging (OWL-S and SWSL)
OMG RFP forthcoming for extensions to ODM to support Semantic Web Services, EXPRESS, eventually SWRL (when a rule language is selected/formalized)
Business Semantics for Business Rules joint revised submission, called “Semantics for Business Vocabularies & Rules (SBVR)” is logically grounded in Common Logic / ODM CL Metamodel
Potential mapping to forthcoming Production Rule specification
Leverage mapping from UML for BPEL to ODM extensions
Strategy:– Link business process models through MOF environment– Generate OWL for the linkage– Use linkage as basis for mediating business process semantics
30Copyright ©2005 Sandpiper Software, Inc.
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
31Copyright ©2005 Sandpiper Software, Inc.
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 Web technologies are the key
32Copyright ©2005 Sandpiper Software, Inc.
Questions / Discussion
33Copyright ©2005 Sandpiper Software, Inc.
John Sowa’s Top-Level Categories
34Copyright ©2005 Sandpiper Software, Inc.
Physical Quantities & Dimensions
35Copyright ©2005 Sandpiper Software, Inc.
Constant Quantities & Units
36Copyright ©2005 Sandpiper Software, Inc.
Standard International Units
37Copyright ©2005 Sandpiper Software, Inc.
Example Measurement Class Definition
38Copyright ©2005 Sandpiper Software, Inc.
Example Corrosion Rate Definition