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Semantic Web Enabled Web Services: State-of-Art and Industrial Challenges

Industrial Ontologies Group. Semantic Web Enabled Web Services: State-of-Art and Industrial Challenges. Vagan Terziyan, Oleksandr Kononenko “Industrial Ontologies” Group http://www.cs.jyu.fi/ai/OntoGroup/index.htm.

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Semantic Web Enabled Web Services: State-of-Art and Industrial Challenges

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  1. Industrial Ontologies Group Semantic Web Enabled Web Services:State-of-Art and Industrial Challenges Vagan Terziyan, Oleksandr Kononenko “Industrial Ontologies” Group http://www.cs.jyu.fi/ai/OntoGroup/index.htm Int. Conference on Web Services Europe (ICWS-Europe’03), Erfurt, Germany, Sept. 23-25, 2003 These slides are available from: http://www.cs.jyu.fi/ai/ICWS-2003.ppt

  2. Industrial Ontologies Group • We develop Semantic Web solutions for industry • Our research contacts with: Metso, Tietoenator, Sonera, Nokia, … • Location: • University of Jyväskylä, Finland; • National University of Radioelectronics, Ukraine • Developed Concepts: • OntoServ.Net: • Semantic Web-based large-scale automated industrial service integration framework for asset management (case of smart-devices maintenance is under development) • GUN (Global Understanding eNvironment): • Approach for resource integration built using combination of Semantic Web, Web Services and Agent technologies • OntoShell: • Agent-based representative of informational entities in semantic-enabled environment (OntoServ.Net) • OntoAdapter: • Connector-software that adapts native service interface to OntoServ.Net find more details at www.cs.jyu.fi/ai/OntoGroup/

  3. SWWS – Web Services with semantics represented explicitly via ontology-based descriptions Intelligent agents will use semantic web services, discovering composing them accordingly their goals New types of service consumers: user agents, devices, AI agents Intelligent dynamic service integration Reasoning about service capabilities requires more advanced service description framework than existing technology has Web Services and Semantics The promise is that Web Service Technology in conjunction with Semantic Web Technology (“Semantic Web Services”) will make service integration dynamically possible for all types and sizes of environments compared to the “traditional” technologies

  4. Semantic Web support for IT “The Semantic Web is a vision: the idea of having data on the Web defined and linked in a way that it can be used by machines not just for display purposes, but for automation, integration and reuse of data across various applications” http://www.w3.org/sw/ The Semantic Web is an initiative with the goal of extending the current Web and facilitating Web automation, universally accessible web resources, and the 'Web of Trust', providing a universally accessible platform that allows data to be shared and processed by automated tools as well as by people.

  5. SWWS main challenges (Dieter Fensel) “Next-generation Web” E-commerce, EAI • Service description • Service discovery • Service mediation Web ServicesUDDI, WSDL, SOAP Intelligent Web Services Dynamic Static Interoperability, knowledge management Web TechnologyHTTP, URI Semantic WebXML, RDF(S), OWL Human-oriented dataMachine-processable data

  6. UDDI needs semantics! Domain ontologies • Service semantics • Service interface semantics • Message semantics • and more.. • Service model • Constraints • Composition rules E-Market E A I DAML-S Industrial Services Business Processes DAML-S is an upper-ontology for service description. Development of common domain ontologies will provide basis for semantic-enabled service descriptions. Will be there a Semantic UDDI?

  7. Service description • Description models in: WSDL, UDDI, E-Speak, ebXML, RosettaNet BPEL4WS, WSCI, BPML • Existing technology: • No explicitly defined semantics in service descriptions • None of existing model proposes something more than basic ontology definition • Keyword-based search is not enough • Semantic Web for Web Services: • Standards via ontological definition • DAML-S (upper ontology of services) • Reuses WSDL adding semantics-binding elements • Provides ontological description of service model • Adds semantic-bindings to service profile

  8. Where are changes? Agents can ‘understand’ what, when and how to useservices • BPEL4WS, WSCI, BPML Service Flow Orchestration,Choreography, Composition Common and domain ontologies • DAML-S: • Service Model • Service Profile • Service Grounding (WSDL) • UDDI Discovery Description Still to be implemented Semantic match Collaborative service-agents Ontology-based standards • WSDL • SOAP and extensions: • Transactions • Security • Routing, etc. Messaging Ontologies instead of language standards • RDF Messaging • HTTP, FTP,email, etc. Networking

  9. Descriptiveness of DAML-S • DAML-S is ontology for service description based on Resource Description Framework and DAML+OIL ontology language • DAML-S • ServiceProfile properties for automatic discovery (offered functionality, preconditions, inputs, outputs and effects of service invocation) • ServiceModelprocess model for automated integration and invocation • ServiceGroundingcommunication-level details (WSDL)

  10. Maintenance Service Network Agents acting as service components in the Maintenance Service Network have ability to learn during work improving services’ performance. OntoServ.Net: “Semantic Web Enabled Network of Maintenance Services for Smart Devices”, Industrial Ontologies Group, March 2003, Smart-devices are becoming users of provided maintenance services.

  11. Semantic-enabled web services in OntoServ.Net • We add semantic-enabled descriptions of services to facilitate: • automated discovery and use of services by smart-devices; • automated integration of services; • communication between heterogeneous services. Service Platform Set of “service components” Maintenance Platform Set of “service components”

  12. Interoperability Ontology B: Research Ontology C: Services Ontology A: Documents A:Report V. Terziyan Instance-of A:Author Semantic Web 3.1: analysis A:Location A:Subject A:name \\AgServ\vagan\InBCT_1.doc Common (shared) ontology System 2 System 1 A commitment to a common ontology is a guarantee of a consistency and thus possibility of data (and knowledge) sharing

  13. Service discovery • DAML-S service profiles • Supporting domain ontologies • Semantic match procedure Ontology of service description RequestedService profile: - service of class “Text Search Service” (subclass-of “Search Service”) - “Data Source” is “PDF File” Input data: 1: “URL Location” of “Data Source” 2: “Search String” Required result: 1: “Occurrence position” of “Search String” Service profile Class: “PDF Search Service” (subclass-of “Text Search Service”) Input: 1: “Search String” 2: “Case-sensitive Flag” 3: “URL Location” Output: 1: “Page Number” 2: “Occurrence position” Semantic match Common Ontologies … … Data Source … … URL String … Search String

  14. Service discovery in OntoServ.Net Maintenance Centers and Maintenance Platforms • Peer-to-peer network of platforms for maintenance services • No centralized service registration • Peer-to-peer semantic search based on service profiles • Profile includes history of “service use efficiency”

  15. Services as Agents • Service (an agent) is a self-interested, autonomous, active, mobile(!!!) entity • If Service = Agent, than Service is mobile • Mobile code is carried by agent • Agent-shell for web services • Agent-shell as service adapter • Main strategies: • Service composition via collaboration between agent- services • Service composition by “Service Manager” accordingly to specific goals of service platform • Mobility factors: • Security • Bandwidth • Time and other constraints

  16. Semantic adapters • OntoServ.Net resources: • Services • Device • Human • Data repository + Semantic adapter = OntoServ.Net Service OntoServ.Net service OntoServ.Net service Service profile and configuration Semantic-basedcommunication via standard protocols Specific communication methods (semantic queries, ontologically described data) Resource Application Human, smart-device, application, service, algorithm… Semantic adapter • In OntoServ.Net common “language” is used between adapters allows mapping into and from internal service-specific protocols. • Implementation of generic semantic-adapter software is non-trivial task, but adapters for restricted class of services (for device data access, data retrieval from DB, alarm system notifications) are less challenging.

  17. Service composition in OntoServ.Net • System is composed accordingly to Task Ontology • New services are requested from the network when needed • Service’s diagnostic “experience” is concerned Diagnostic Services Maintenance ManagerService Task Ontology Platform Smart-devices

  18. Ontology support for OntoServ.Net User Agents Maintenance activities Diagnostics Diagnostic services • Common intermediate language: • Unambiguous agreed vocabulary and semantics • - Service taxonomy • - Maintenance domain Data access • Sharable diagnostic knowledge representation • System configuration • Semantic adapter configuration Data access services

  19. OntoServ.Net Challenges • New group of Web service users – smart industrial devices. • Semantic Web enabled services • Internal (embedded) and external (Web-based) service platforms. • “Mobile Service Component” concept supposes that any service component can move, be executed and learn at any platform from the Service Network, including service requestor side. • Semantic Peer-to-Peer concept for service network management assumes ontology-based decentralized service network management.

  20. Conclusion • Traditional web service technology is able to address some of problems today. However, in combination with Semantic Web Web Services have the potential to address these needs much better • Semantic Web it is a new context within which one should rethink and re-interpret his existing businesses, resources, services, technologies, processes, environments, products etc. to raise them to totally new level of performance… • The OntoServ.Net concept of Distributed Maintenance Network can be a good pilot case to implement the benefits of Semantic Web and Web Services integrated framework. ------------------------------------------ Contact:Vagan Terziyanvagan@it.jyu.fi http://www.cs.jyu.fi/ai/vagan

  21. Acknowledgements Agora Center (University of Jyvaskyla): Agora Center includes a network of good-quality research groups from various disciplines. These groups have numerous international contacts in their own research fields. Agora Center also coordinates and administrates research and development projects that are done in cooperation with different units of university, business life, public sector and other actors. The mutual vision is to develop future's knowledge society from the human point of view. http://www.jyu.fi/agora-center/indexEng.html InBCT Project (2000-2004): Innovations in Business, Communication and Technology http://www.jyu.fi/agora-center/inbct.html

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