Designing Semantic Web Process: The WSDLS Approach

1
Designing Semantic Web Process The WSDL-S
Approach

• Presented by
• Ke Li
• LSDIS Lab, University of Georgia
• (Under the Direction of John A. Miller)

2
Acknowledgment

• Dr. John A. Miller
• Dr. Amit P. Sheth
• Dr. Eileen T. Kraemer
• Kunal Verma
• Doug, Zixin
• Meena, Cary, Scott

3
Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

4
Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

5
Introduction

• Web Service
• Concept
• Web Services is self-contained modular business
  applications that have open, internet-oriented
  and standards-based interface.
• Web Service Standards
• SOAP (Simple Object Access Protocol)
• WSDL (Web Service Description Language)
• UDDI (Universal Description, Discovery and
  Integration)
• WS-BPEL (Web Service Business Process Execution
  Language)

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Introduction

• Web Process
• Combine individual services to achieve a more
  complex goal
• Advantage
• enables modular design
• Implements the control and data flow between
  services
• For example, Service A, B and C.
• B is dependent on As output message.
• A and C can be invoked at the same time

7
Introduction

• Semantic Web Service
• Adding semantics to Web service standards
• Bring meaning to the services
• Removes ambiguity in the description of Web
  service elements.
• Enables automation of tasks like discovery,
  invocation, composition

8
Introduction

• WSDL-S Based Tool Suite for Designing Semantic
  Web Process
• Radiant Web Service Semantic Annotation and
  Semantic Publish
• Lumina Semantic Web Service Discovery
• Saros Web Services Composition

9
Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

10
Background

• Problems with current Web Service publishing,
  discovery and composition
• No unified WSDL to UDDI mapping structure
• Syntactic search mechanism for service discovery

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Background

• Mapping Structure from WSDL to UDDI

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Background

• Modified Mapping Structure from WSDL-S to UDDI

13
Background

• Four Semantic Web Service Standard Proposals
  (Brief Overview)
• OWL-S
• WSMO (Web Service Modeling Ontology)
• SWSO (Semantic Web Service Ontology)
• WSDL-S

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Background (OWL-S and WSMO)

• OWL-S
• WSMO

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Background (WSDL-S)

• WSDL-S
• Built on existing Web Service standard - WSDL
• Enables semantic annotation of Web Services by
  using extensibility elements and attributes
• Annotation on message types
• modelReference, and schemaMapping
• Annotation on operation
• modelReference, category, precondition and effect
• Uses external domain models to provide the
  semantics

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Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

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The METEOR-S Semantic Discovery Tool - Lumina

• Motivation
• Support semantic discovery (WSDL-S approach)
• Enable semi-automatic design of Web Processes
  (using Saros)
• Supply a unified discovery style to discover from
  different Universal Business Registries

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The METEOR-S Semantic Discovery Tool - Lumina

• Setting Environment
• Web Server Tomcat 5.0.30
• UDDI Registry Implementation JUDDI 0.9
• Registry Database MySQL-4.1.12-win32
• JDK 1.5
• Model Dependency
• METEOR-S Discovery API
• WSDLS4J
• UDDI4J

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The METEOR-S Semantic Discovery Tool - Lumina

• Discovery Modes UDDI structure based discovery
• General UDDI Discovery (Basic UDDI Discovery
  Panel)
• Unified search style for all the UBRs
• Provide discovery of Business Entity, Business
  Service and Technical Model
• Business Entity Business Name, Discovery URL,
  Categories, TModel Keys
• Business Service Service Name, Categories,
  Business Key, TModel Keys
• TModel TModel Name

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The METEOR-S Semantic Discovery Tool Lumina
UDDI Structure Based Discovery
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The METEOR-S Semantic Discovery Tool Lumina
UDDI Structure Based Discovery
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The METEOR-S Semantic Discovery Tool - Lumina

• Discovery Modes WSDL-S based Semantic Discovery
• WSDL-S Discovery (WSDL-S Discovery Panel
  Semantic Template View)
• Input to the discovery module
• Ontology URL
• Operation functional concepts, semantic inputs
  and semantic outputs
• Input modes
• Typed in by the user
• Dragged and dropped from the Ontology Navigator
  in Radiant
• Output from the discovery module
• Service information (service name, WSDL location)
  
• Service provider information (link to the
  business entity)
• Detailed discovered operation information
  (operation name, input / output variables,
  ontological concepts about these parameters,
  input / output types, portType)

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The METEOR-S Semantic Discovery Tool Lumina
Semantic Discovery Panel Partner Service Viewer
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The METEOR-S Semantic Discovery Tool Lumina
Semantic Template View
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The METEOR-S Semantic Discovery Tool - Lumina

• Discovery Modes WSDL based Syntactic discovery
• WSDL Discovery (WSDL Discovery Panel)
• Input to discovery module
• Exact operation name, input and output variables
• Same as WSDL-S Discovery except the semantic
  information

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The METEOR-S Semantic Discovery Tool Lumina
METEOR-S Discovery Class Diagram
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The METEOR-S Semantic Discovery Tool - Lumina

• Architecture of Lumina
• Adopts Eclipse Plugin Techniques
• Action Lumina start button in tool bar
• Editor UDDI Editor (Basic UDDI Discovery, WSDL-S
  Discovery and WSDL Discovery)
• View (Semantic Template Viewer and Partner
  Service Viewer)
• Perspective Lumina Perspective

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The METEOR-S Semantic Discovery Tool Lumina

• Model
• Class diagram

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The METEOR-S Semantic Discovery Tool Lumina

• View
• Class diagram

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Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

31
Design Semantic Web Process Using WSDL-S

• Semantic Annotation and Publish Radiant
• WSDL-S to UDDI Mapping Structure

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Design Semantic Web Process Using WSDL-S WSDL-S
to UDDI Mapping Structure
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Design Semantic Web Process Using WSDL-S
Annotating a Web service using Radiant
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Design Semantic Web Process Using WSDL-S

• Semantic Discovery Lumina
• WSDL-S Discovery Panel (UDDI Editor) and Partner
  Service Viewer
• Store the candidate partner services to partner
  service viewer (convenient)
• Semantic Template Viewer
• Save the semantic template to files
• Load a exist semantic file
• Enable discovery of multiple operations
• Dependence
• Economic
• Efficient

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Design Semantic Web Process Using WSDL-S WSDL-S
Discovery Panel
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Design Semantic Web Process Using WSDL-S
Semantic Template View
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Design Semantic Web Process Using WSDL-S

• Semantic Web Process Design - Saros
• Dynamic partner selection using the Semantic
  Templates that describe virtual partners
• Two phase design
• Generate new semantic template(s) or load the
  exist semantic template(s) using Semantic
  Template Viewer (Lumina)
• Discover the partner services using the semantic
  templates and bind the discovered services to the
  process

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Design Semantic Web Process Using WSDL-S

• Semantic Web Process Design - Saros

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Design Semantic Web Process Using WSDL-S Saros
Design Panel
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Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

41
Sample Use Case

• Sample Scenario
• Goal investment strategy for buying stock
• Input stock ticker, possible investment amount
• Output value analysis for proceeding with the
  investment

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Sample Use Case

• Analyze the business requirement and build a UML
  diagram

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Sample Use Case

• Fill in the process skeleton

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Sample Use Case

• 3. Fill in the nested constructs / structured
  activities

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Sample Use Case

• 4. Identify partners
• Binding the real partners using concrete service
  information
• Binding the virtual partners filling a semantic
  template
• Discovery based on
• Operation
• Input and output

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Sample Use Case Search for investment service
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Sample Use Case Search for the other two services
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Sample Use Case Add virtual partner
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Sample Use Case

• Analyze the business requirement and build a UML
  diagram
• 2. Fill in the process skeleton
• 3. Fill in the nested constructs / structured
  activities
• 4. Identify partners
• Binding real partners
• Binding virtual partners

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Sample Use Case

• 5. Add namespace, variables
• 6. Link partners to invoke, receive and
  reply
• 7. Add the supplementary elements and fill in
  details
• 8. Generate BPEL process
• BPEL file
• WSDL file of the Process

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Sample Use Case Complete BPEL Process part I
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Sample Use Case Complete BPEL Process part II
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Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

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Evaluation

• Efficient and effective service discovery
• Comparative UBRs
• XMethods and Microsoft UBR
• Search scenario
• Stock Quote
• Comparative formulas
• Precision
• Recall

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Evaluation

• Precision of Stock Quote Web Services Discovery
  Result on the Regular UBRs

• Recall of Stock Quote Web Services Discovery
  Result on XMethods
• 9/13 69

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Evaluation

• The Stock Quote services in the enhanced UDDI
  registry

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Evaluation

• Precision of Lumina Discovery Result Using
  StockQuote Ontological Concepts

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Evaluation

• Recall of Lumina Discovery Result Using
  StockQuote Ontological Concepts

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Evaluation

• 2. Accurate discovery of specific operations
• Service level discovery and operation level
  discovery
• Operation level discovery operation functional
  concept, semantic inputs, semantic outputs
• Discovery of Multiple operations within one
  partner service

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Evaluation

• Web Services Based on the Currency Ontology

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Evaluation

• Web Services annotated with a part of the Travel
  Ontology describing the Weather domain

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Evaluation

• 3. Semi-automatic BPEL process design
• Supply the detailed information of the service
  and operations these information are useful to
  design the process.

63
Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

64
Related Work

• Two categories of Web Services Composition
• Workflow composition
• Static workflow composition
• EFlow (Casati, Ilnicki, et al. 2000)
• Dynamic workflow composition
• PPM (Polymorphic Process Model) (Schuster,
  Georgakopoulos, et al. 2000)
• AI Planning
• Golog Logic Programming Language
• Planning Domain Definition Language (PDDL)
  action value
• Rule-based plan generation SWORD (Ponnekanti
  and Fox, 2002)
• Hierarchical Task Network (HTN) SHOP2 (Wu,
  Sirin, et al. 2003)

65
Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

66
Conclusion

• By using Semantics to annotate the Web Services,
  we provide the efficient, effective and accurate
  services discovery. It enables the automatic and
  dynamic Web Process Design.
• WSDL-S supplies a easy way to add semantics to
  the Web Services.

67
Outline

• Introduction
• Background
• The METEOR-S Semantic Discovery Tool Lumina
• Design Semantic Web Process Using WSDL-S
• Sample Use Case
• Evaluation
• Related Work
• Conclusion
• Future Work

68
Future Work

• Organize Saros to run in the same workspace as
  Lumina, and supply the Drag and Drop
  functionality to further ease the work of the
  process developer
• Develop a constraint analyzer to extend our
  WSDL-S based tool suite.
• Adopt data mapping techniques to implement Web
  Process composition automatically.
• Extend the discovery, composition by using
  preconditions and effects to achieve a more
  accurate result.
• Develop a process monitor to trace the process at
  execution time.

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Demo
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Questions
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Thank you