A Logical Framework for Web Service Discovery

A Logical Framework for Web Service Discovery

The Third International Semantic Web Conference Hiroshima, Japan, 08-11-2004

Michael Kifer1, Rubén Lara2, Axel Polleres2, Chang Zhao1,

Uwe Keller2, Holger Lausen2, and Dieter Fensel2

[email protected]

1Department of Computer Science University at Stony Brook, New Department of Computer Science University at Stony Brook, New York, USAYork, USA

2Digital Enterprise Research Institute, Innsbruck, Austria, and Digital Enterprise Research Institute, Innsbruck, Austria, and Galway, IrelandGalway, Ireland

08-11-2004 Rubén [email protected]

2

Overview

1. Introduction

2. Proof obligations and formalization

3. Realization

4. Semantics of rule reification

5. Conclusions & future work


3

Automatic discovery

• Current Web Services have to be selected and hard-wired at design time– No dynamic reconfiguration of services

• Semantics can enable the automatic location of Web Services providing particular functionality


4

WSMO & WSML

Objectives that a client may have when consulting a Web Service

Provide the formally specified terminology used by all other components

Semantic description of Web Services: - Capability - Interfaces

Connectors between components to bypass heterogeneity

F-Logic + Transaction Logic


5

The problem

• Matching capabilities of existing Web Services against the goal described by the requester

– Consideration of the functionality of the Web Service

– Distinction between discovery and contracting

– Example implementation using


6

Overview

1. Introduction


3. Realization




7

Goals, capabilities & mediators

• Goal describes (in terms of domain ontologies) the desired state of:– Information space– State of the world

• Web Service capabilities describe (in terms of domain ontologies):– What the service expects to provide its functionality– What is guaranteed to hold after execution

• wgMediators link Web Services and goals, resolving heterogeneity– Resolve possible terminology differences


8

Logics and scalability issues

• Logic can be used to formalize goals, capabilities and proof obligations– Scalable framework must rely on a relatively small

number of logicians

Customer:

- no training in KR

-pre-defined discovery queries

-goal ontology

Service Provider:

- modest requirements

-Capabilities written to relatively simple ontologies

-Relatively simple types of rules

Mediation Provider:

- Bulk of logical expertise

-Link ontologies, not customers and providers


9

Proof obligations (I)

• Set of imported ontologies O

• Goal G

• Service capability C (Ceff and Cpre)

• wgMediator wg– takes a goal G and constructs input Inwg(G) suitable for services

mediated– Converts the goal into a postcondition Postwg(G) expressed in terms of

the service ontology– Mediation can be complex:

• Goals can be expressed in a very high level syntax• Service capabilities can be rather simple


10

Proof obligations (II)

• Service discovery– Given a goal G, can the service execute in a way

such that G can be achieved?

• Service contracting– Given an actual input to a specific service, does this

input lead to the results expected by the requester?


11

Proof obligations (III)

• Proof obligations before– Deal with a particular service– Different services have different effects

• Use of transaction logic

• is the sequence operator• is the hypothetical operator


12

Overview

1. Introduction


3. Realization




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Realization

• Use of :– Support for F-Logic, HiLog, Transaction Logic and

rule reification

• Geographic ontology


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Realization (II)

• Goal ontology:

• Service1:Conditions over the input

Input is a search -> provide itinerary

wgMediator used


15

Realization (III)

• Service 3:

• Goals:

Uses goal ontologyRegion!


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Realization (IV)

• Mediator: Takes the goal and constructs input to the service

Takes the result and checks it according to the format specified in the goal


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Realization

• Discovery

Construct input

Generate effects

Assume effects

Check goal

Remove effects


18

Overview

1. Introduction


3. Realization




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Semantics of rule reification

• Model theory for F-Logic extended with rule reification defined

• Reified F-Logic avoids paradoxes through two restrictions:– No negation is allowed in the rule head, and– Reification of negation of any fact or any rule is not

permitted


20

Overview

1. Introduction


3. Realization




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Conclusions

• Logical framework and realization for: – dynamic discovery of Web Services– verification of contractual statements

• Scalable framework in terms of human resources by exploiting mediators

• The framework captures the relation between inputs and effects, thus providing more accurate descriptions and discovery

• Easily extendable to include invocation


22

Future work

• In progress– Alignment with WSML– Integration with other types of web service discovery– Further investigation on border between ggMediation

and wgMediation– Complete knowledge goals in the absence of sufficient

domain knowledge– Implementation of WSMO discovery engine

• Planned– Integration with composition


23

Conclusions

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A Logical Framework for Web Service Discovery