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Automating Web Service Discovery_ Customization_ and Semantic


									A Bottom-Up Approach to
 Automating Web Service
Discovery, Customization,
and Semantic Translation

 Dan Mandell and Sheila McIlraith
    Knowledge Systems Lab
      Stanford University
         ESSW 2003
 Bottom-Up  approach
 Motivating example
 BPEL4WS and automated Web service
 The Semantic Discovery Service (SDS)
  and automated Web service discovery,
  customization, and semantic translation
 Summary: contributions, future directions
     A Bottom-Up Approach
 Web services long-term goal: seamless
  interoperation between programs and devices
 Industry provides standards, computing
  infrastructure, and recently choreography
  models akin to work in process modeling
 These include WSCI, BPML, XLANG, WSFL,
 Still far from seamless interoperation
     A Bottom-Up Approach
 In parallel, Semantic Web community has
  developed languages and computing machinery
  for authoring and reasoning about unambiguous,
  machine interpretable Web content
 Efforts are based on AI technology, and include
 Though powerful, these efforts remain largely
  disconnected from industrial standards and
         A Bottom-Up Approach
   We argue that:
       Web Services must embrace representation and
        reasoning ideas from Semantic Web community
       Must also recognize evolutionary influence of industry
        standards and machinery on Semantic Web services
   From this viewpoint, we build on BPEL4WS
       A leading process modeling framework
       Co-authored by IBM, Microsoft, BEA, SAP, Siebel
       Merges ideas from XLANG and WSFL
   Integrate Semantic Web technology to enable
    automated service discovery, customization, and
    semantic translation
          A Motivating Example
 Consider integrating services to provide a loan
  finding service:
 Possible scenario:
       User sends loan request to loan finding service
       Loan finder distributes work among 2 partners
         • Credit Assessor Service
               Consumes user’s personal info
               Produces a credit report
         • Loan Lender Service
               Consumes a credit report and a loan request
               Produces a rejection or a loan offer and its terms
       Loan finder invokes credit assessor for a credit report,
        passes report to lender service, receives result and
        returns it to the user
        A Motivating Example

   Possible scenario:
           A Motivating Example
 Questions:
     How are the service partners
       •   Selected?
       •   Ordered?
       •   Invoked?
       •   Integrated?
      BPEL4WS - Automated
        Service Execution
    A BPEL4WS document
      • Provides notation for describing WS interactions as
        business processes, following in tradition of
        workflow modeling
      • Integrates services by treating them as partners
        that fill roles in a process model
      • Directs workflow using traditional control
        constructs: if, then, else, while-loop
    Communication level params (e.g. service
     partner bindings) are described in
     accompanying WSDL docs
      BPEL4WS - Automated
        Service Execution
    Engine released by IBM alongside BPEL4WS
    Implements subset of features defined in
    Consumes a BPEL4WS doc along with
     accompanying WSDL docs defining service
     partner bindings to physical ports
    Establishes a single endpoint for accessing
     BPEL4WS process as a Web service
      BPEL4WS - Automated
        Service Execution
 BPEL4WS      and the loan example
    A service provider writes a BPEL4WS doc
     describing the loan finding process model -- a
     program that orchestrates interaction of the
     service partners
    BPEL4WS allows service partners to be
     unbound to physical ports until runtime through
     dynamic assignment of Service References
    Current implementation of BPWS4J does not
     implement Service Reference assignment, so
     author selects service partners at design time
       BPEL4WS - Automated
         Service Execution
 Critical   analysis of BPEL4WS automation:
     Limitations in BPWS4J
      • Service provider assigns partners a priori
      • System cannot customize partner selection for each
        user. Suboptimal partners may be selected because
            Service provider may lack full list of potential partners at
             design time
            Difficult to find single solution that generalizes for all users
      • Loan finder example: user may wish to use in-state
        lender to benefit from in-state tax incentives
      • If service provider defines lending partner prior to
        receiving user’s request, the preference is ignored
       BPEL4WS - Automated
         Service Execution
 Critical   analysis of BPEL4WS automation:
     Limitations in BPWS4J
      • Manually discovering, selecting and integrating the
        service partners means significant responsibilty and
        maintenance time demands for the service provider
       BPEL4WS - Automated
         Service Execution
 Critical   analysis of BPEL4WS automation:
     Limitations in BPEL4WS
      • Relies on expressivity of XML / XML Schema
      • Interface-oriented: insufficient for automating many
      • E.g., credit assessor for an ex-UK resident provides
        UKCreditReports, while lending service comsumes
        USCreditReports. Even if differ only in
        representation of dates, failing to recognize their
        semantic compatibility leaves a potentially
        successful integration unrealized
      • Need service-oriented descriptions of service form
        and function in an well-defined ontology language
  Automated, Customized,
 Service Discovery with SDS
   alleviate shortcomings in BPEL4WS /
 To
 BPWS4J, introduce a Semantic Discovery
 Service (SDS) to enable
     automated service discovery
     automated service customization
     automated semantic translation
 Use Semantic Web technologies to enable
 description of services in computer
 interpretable format and discovery of
 services with desirable properties
  Automated, Customized,
 Service Discovery with SDS
 Supporting    technologies
     DAML-S: A well-defined ontology based on
      DAML+OIL, used to describe services
     DAML Query Language (DQL): Language and
      protocol used for querying repositories of
      DAML-S service profiles. DQL server
      interfaces with automated reasoner operating
      over knowledge base (KB) of DAML-S profiles
     Java Theorem Prover (JTP): Hybrid reasoning
      system based on FOL model elimination.
      Use as DQL server’s automated reasoner
  Automated, Customized,
 Service Discovery with SDS
 Form   and function of the SDS
     Sits between a BPWS4J process and
      potential service partners
     Locates appropriate partners, acts as
      dynamic proxy between them and BPWS4J
  Automated, Customized,
 Service Discovery with SDS
 The SDS is portable between BPWS4J
 actions and processes because it is:
     Agnostic as to the content of the service
      descriptions and invocation messages it
     Stateless, with no knowledge of prior
      interactions or service-specific properties
 TheSDS enables automated service
 customization and semantic translation
     Automated, Customized,
    Service Discovery with SDS
       Automated service customization
        When SDS receives invocation request from
         BPWS4J, discovers a service partner meeting
         user and functional constraints as follows
         1. DAML-S functional and user-supplied restrictions are wrapped
            into a DQL query and sent to the DQL server
         2. Server invokes JTP reasoner to compute set of matching
            DAML-S profiles in the KB
         3. SDS selects partner from DQL answer bundles and invokes it
            with the request parameters
         4. Partner executes, responds to SDS, forwarded to BPWS4J
         5. BPWS4J recovers flow control, continues executing process,
            invokes SDS when customized Web service invocation needed
 Automated, Customized,
Service Discovery with SDS

 Interaction flow between BPWS4J, SDS, DQL
     server, and discovered service partners
  Automated, Customized,
 Service Discovery with SDS
 Automated     semantic translation
     In the Web services context, semantic
      translation means redefining well-defined data
      types in terms of their relationships to each
      other via translational axioms
     Enables integration of service partners
      operating on messages that differ syntactically
      but are semantically translatable
  Automated, Customized,
 Service Discovery with SDS
 Automated     semantic translation
     SDS provides automated semantic translation
      for Web service discovery
     Uses a back-chaining algorithm to find
      sequence of service invocations, or service
      chain, which consumes the input supplied by
      BPWS4J and produces the output desired by
     Uses translational axioms encoded as Web
      services to integrate partner inputs and outputs
   Automated, Customized,
  Service Discovery with SDS
 SDS   and the loan example
    Recall ex-UK resident seeking a loan from
     an in-state lender
    BPWS4J could not satisfy request given
     the constraints
     • Credit assessor produces UKCreditReport,
       lender consumes USCreditReport
     • UKCreditReport represents dates as
       MM/DD/YYYY, US version uses
  Automated, Customized,
 Service Discovery with SDS
 SDS   and the loan example
    With SDS, the request is satisfiable
     • Automated service customization: include DAML-S
       restriction that lender partner be physically located in
       the user’s state in request message
     • Automated semantic translation: back-chaining
       algorithm inserts a DateTranslator translational
           DateTranslator translates between UKCreditReport and
           Forms service chain (Assessor -> DateTranslator ->
            Lender) which can successfully complete request
 Seamless    interoperability is critical for
  Web services to provide an infrastructure
  for ubiquitous computing
 Towards this goal, the bottom-up
  approach brings Semantic Web
  technology to industrial standards and
  computing machinery
 Byintegrating the SDS with BPEL4WS,
 the industrial system gained the following
     Automatic, runtime binding of service partners
     Selection between multiple service partners
      based on user-defined constraints
     Integration of service partners with
      syntactically distinct but semantically
      translatable service descriptions
   To work towards seamless interoperation, it is
    critical that:
      Web service providers publish descriptions of

       Web service form and function in a well-
       defined ontology language like DAML-S
      Web service interoperation frameworks

       embed semantic technology into their
       systems and specificaitons that is capable of
       reasoning about such descriptions

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