1. Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Chapter 6: Modeling and Representation
Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005
© Singh & Huhns

2. Highlights of this Chapter
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Highlights of this Chapter
Integration versus Interoperation
Common Ontologies
Knowledge Representations
Relationships
Hierarchies
Modeling Fundamentals
Unified Modeling Language (UML)
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

3. Integration versus Interoperation
Tight coupling
Loose coupling
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

4. Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Modeling and Composing Services Emphasis on the Conceptual Model or Schema
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

5. Ontology
A specification of a conceptualization or a set of knowledge terms for a particular domain, including
The vocabulary: concepts and relationships
The semantic interconnections: relationships among concepts and relationships
Some simple rules of inference and logic
Some representation languages for ontologies:
Unified Modeling Language (UML) Class Diagrams
Resource Description Framework Language Schema (RDFS)
Web Ontology Language (OWL)
Some ontology editors: Protégé, Webonto, OilEd
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

6. Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Common Ontologies
A shared representation is essential to successful communication and interoperation
For humans: physical, biological, and social world
For computational agents: common ontology (terms used in communication)
Representative efforts are
Cyc (and Opencyc)
WordNet (Princeton); LDOCE; OED
Several upper-level ontologies, including by IEEE
Mostly stable concepts such as space, time, person, which can be used within various domains
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

7. Ontologies and Articulation Axioms
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Ontologies and Articulation Axioms
Mapping by hand, but with tool support
Developing a common ontology:
All at once (top down)
Incrementally via consensus (bottom up)
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

8. Dimensions of Abstraction: 1
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Dimensions of Abstraction: 1
Descriptions of services that have a bearing on interoperation
Constraints that we must discover, represent, and reason about
Data
Domain specifications
Value ranges, e.g., Price >= 0
Allow or disallow null values
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

9. Dimensions of Abstraction: 2
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Dimensions of Abstraction: 2
Structure
Specializations and generalizations of domain concepts
Taxonomic representations and relationships such as in schemas and views, e.g., securities are stocks
Semantics of data
Some stock price databases consider daily averages; others closing prices
Value maps, e.g., S&P A+ rating corresponds to Moody’s A rating
Integrity constraints
Each stock must have a unique SEC identifier
Cardinality constraints
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

10. Dimensions of Abstraction: 3
Process
Procedures, i.e., how to process information, e.g., how to decide what stock to recommend
Flow, e.g., where to forward requests or results
Temporal constraints, e.g., report tax data every quarter
Preferences for accessing and updating information
Dealing with data replication (recency or accuracy)
Updating views
Contingency strategies, e.g., whether to ignore, redo, or compensate
Contingency procedures, i.e., how to compensate transactions
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

11. Dimensions of Abstraction: 4
Service-Oriented Computing: Semantics, Processes, Agents
August 2004
Dimensions of Abstraction: 4
Policy
Privileges, i.e., who has rights to what service
E.g., owners can access all of their accounts, except blind trusts
Authentication, i.e., how to establish identity
E.g., passwords, retinal scans, or smart cards
Bookkeeping
E.g., logging all accesses
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns
© Singh & Huhns

12. Value Maps: 1
A value map relates the values expressed by different services
Key properties
Totality or coverage
Order preservation or monotonicity
Consistent inversion or triple negation
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

13. Value Maps: 2
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

14. Knowledge Representation
Expressive power
Procedural (how) versus declarative (what)
Declarative pros: enables standardization, optimization, improved productivity of developers
Declarative cons: nontrivial to achieve and causes short-term loss of performance
Trade-offs shifted by Web to favor declarative modeling
Because of heterogeneity
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

15. Frames versus Descriptions
Frame-based approaches are intuitive
Like O-O
Rely on names of classes and properties to indicate meaning
Description logics provide a computationally rigorous means to represent meaning; difficult for people
Managing this trade-off is a major challenge for Knowledge Representation
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

16. Exercise: Which Conceptualization is Most Expressive and Flexible?
awg22SolidBlueWire(ID5)
blueWire(ID5, AWG22, Solid)
solidWire(ID5, AWG22, Blue)
wire(ID5, AWG22, Solid, Blue)
wire(ID5)^size(ID5, AWG22)^type(ID5, solid)^color(ID5, Blue)
Think of a database in which you store such facts
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

17. Mappings among Ontologies
Term-to-term (one-to-one), e.g.,
hookupWireO1  wireO2
Many-to-one, e.g.,
solidWireO1(x, size, color) Ɩ strandedWireO1(x, size, color)  wireO2(x, size, color, (Stranded | Solid))
Many-to-many, e.g.,
solidBlueWireO1(x, size) Ɩ
solidRedWireO1(x, size) Ɩ
strandedBlueWireO1(x, size) Ɩ
strandedRedWireO1(x, size) 
solidWireO2(x, size, (Red | Blue)) Ɩ
strandedWireO2(x, size, (Red | Blue))
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

18. Unified Modeling Language (UML) for Ontologies
Class diagrams without members
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

19. Comparison of Modeling Languages
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

20. Chapter 6 Summary Shared models are essential for interoperation
Based on shared ontologies or conceptualizations
Good models must accommodate several important considerations
Modeling requires several subtle considerations
Declarative representations facilitate reasoning about and managing models
Formalization enables ensuring correctness of models and using them for interoperation
Chapter 6
Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns