Chapter 6:Modeling and Representation

Service-Oriented Computing: Semantics, Processes, Agents– Munindar P. Singh and Michael N. Huhns, Wiley, 2005

Chapter 6 2Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Highlights of this Chapter

Integration versus Interoperation Common Ontologies Knowledge Representations Relationships Hierarchies Modeling Fundamentals Unified Modeling Language (UML)

Chapter 6 3Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Integration versus Interoperation

Application

Transform

Application Application Application Application

Integration EDI XML Portal + Workflow Solution

APIsolution

Standard DataFormat

XML-Based DataExchange Format

Application Application Application Application Application

Distributed application: XML +Web services + workflow

TransformationTransformation

Transform Transform Transform Transform

Transform Transform Transform Transform Transform

Tight coupling Loose coupling

Chapter 6 4Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Modeling and Composing Services

RequirementsAnalysis

ConceptualSchema

BackgroundKnowledge

Universe ofDiscourse

Universe ofDiscourse

RequirementsAnalysis

CO

MP

RE

HE

ND

ConceptualSchema

ServiceInterface

ServiceInterface

DesignService

Implementation

DesignService

Implementation

MA

P

INT

ER

OP

ER

AT

E

Chapter 6 5Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Dimensions of Abstraction: 1

Information resources are associated with abstractions over different dimensions, which capture knowledge that is relevant for interoperation. These may be thought of as constraints that must be discovered and represented

Data Domain specifications Value ranges, e.g., Price >= 0 Allow/disallow null values

Chapter 6 6Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Dimensions of Abstraction: 2

Structure Taxonomic representations and relationships

such as in schemas and views, e.g., securities are stocks

Specializations and generalizations of domain concepts, e.g., stocks are a kind of liquid asset

Value maps, e.g., S&P A+ rating corresponds to Moody’s A rating

Semantic data properties, sufficient to characterize the value maps, e.g., some stock price databases consider daily averages; others closing prices

Cardinality constraints Integrity constraints, e.g., each stock must

have a unique SEC identifier

Chapter 6 7Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Dimensions of Abstraction: 3

Process Procedures, i.e., how to process information,

e.g., how to decide what stock to recommend Preferences for accesses and updates in case

of data replication (based on recency or accuracy of data)

Preferences to capture view update semantics Contingency strategies, e.g., whether to

ignore, redo, or compensate Contingency procedures, i.e., how to

compensate transactions Flow, e.g., where to forward requests or results Temporal constraints, e.g., report tax data

every quarter

Chapter 6 8Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

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Dimensions of Abstraction: 4

Policy Security, i.e., who has rights to access or

update what information? (e.g., customers can access all of their accounts, except blind trusts)

Authentication, i.e., a sufficient test to establish identity (e.g., passwords, retinal scans, or smart cards)

Bookkeeping (e.g., logging all accesses)

Chapter 6 9Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

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Value Maps: 1

A value map relates the values expressed by different services

Key properties Totality Order preservation Consistent inversion

Chapter 6 10Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Value Maps: 2

A++

Aaa

A.M. Best Moody’s

A+

Aa1

A

Aa2

A-

Aa3

B++

A1

B+

A2

B

A3

B-

Baa1

C++

Baa2

C+

Baa3

C

Ba1

C-

Ba2

D

Ba3

E

B1

F

B2

B3

Caa

Ca

C

A++

Aaa

A.M. Best Moody’s

A+

Aa1

A

Aa2

A-

Aa3

B++

A1

B+

A2

B

A3

B-

Baa1

C++

Baa2

C+

Baa3

C

Ba1

C-

Ba2

D

Ba3

E

B1

F

B2

B3

Caa

Ca

C

(a) A consistent value map (b) A value map that violates consistent inversion

Chapter 6 11Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

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: Uniform Modeling Language (UML) Resource Description Framework Language

Schema (RDFS) Web Ontology Language (OWL)

Some ontology editors: Protégé, Webonto, OilEd

Chapter 6 12Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

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 13Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Ontologies and Articulation Axioms

SeatingArrangement

Airplane

TransportationDevice

nonNegativeInteger

seats

nonNegativeInteger

range

numpassengers

Airliner

Flight

Airport

to from

equipment

CommercialTransportation

Device

PublicTransportation

Device

Itinerary

LocationClass ofService

classto Leg

from

uses

1*

Boeing777

JumboJet

CommonOntology

Travel Agent Service

User’s Agent

Mapping byhand, butwith toolsupport

Developing acommon ontology:• All at once• Incrementally viaconsensus

Chapter 6 14Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

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

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Frames versus Descriptions

Frame-based approaches are like object-oriented representations: Intuitive but 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 16Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

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)

Chapter 6 17Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

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Mappings among Ontologies Term-to-term (one-to-one), e.g.,

hookupWireO1 => wireO2

Many-to-one, e.g.,solidWireO1(x, size, color) ^ strandedWireO1(x, size, color)

=> wireO2(x, size, color, (Stranded|Solid))

Many-to-many, e.g.,solidBlueWireO1(x, size) ^

solidRedWireO1(x, size) ^

strandedBlueWireO1(x, size) ^

strandedRedWireO1(x, size)

=>solidWireO2(x, size, (Red|Blue)) ^

strandedWireO2(x, size, (Red|Blue))

Chapter 6 18Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

Unified Modeling Language (UML) for Ontologies(Class Diagrams)

PurchaseOrder ShippingDetail

BillingDetailItemDetail

Seller Buyer Account

Organization Person

1 *

1*

1*

1* 1 *1 *

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Comparison of Modeling Languages

Chapter 6 20Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and

Michael Huhns

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