1. Semantic Web Processes: Semantics to exploit Web Services on a global scale IBM TJ Watson 10 July, 2003 Amit Sheth METEOR-SMETEOR-S Project Large Scale Distributed Information Systems (LSDIS) Lab The University of Georgia, Athens GA Special Thanks: Kaarthik Sivashanmugam © METEOR-S Team, UGA, 2003

2. LSDIS Introduction Slide 1 of 3: Move from Syntax to Semantics in Information System Semantic Web, some DL-II projects, Semagix SCORE, Applied Semantics VideoAnywhereInfoQuiltOBSERVER Generation III (information brokering)1997... Semantics and Ontology-driven Information Systems InfoSleuth, KMed, DL-I projects Infoscopes, HERMES, SIMS, Garlic,TSIMMIS,Harvest, RUFUS,... Generation II (mediators)1990s VisualHarnessInfoHarness Metadata MermaidDDTS Multibase, MRDSM, ADDS, IISS, Omnibase,... Generation I (federated DB/ multidatabases)1980s Data

3. Paradigm shift over time: Syntax -> Semantics Increasing sophistication in applying semantics  Relevant Information (Semantic Search & Browsing)  Semantic Information Interoperability and Integration  Semantic Correlation, Mining, Analysis, Early Warning

4. Ontology Content Sources Semi- Structured CA Content Agents Structured Unstructured Documents Reports XML/Feeds Websites Email Databases CA Knowledge Sources KA KS KA KS Knowledge Agents KS Metabase Semantic Enhancement Server Entity Extraction, Enhanced Metadata, Automatic Classification Semantic Query Server Ontology and Metabase Main Memory Index Metadata adapter Existing Applications ECM EIP CRM Semagix Freedom Architecture (a platform for building ontology-driven information system)

5. Web ProcessesWorkflows Distributed Workflows GlobalEnterpriseInter-Enterprise B2BE-Services Globalization of Processes Processes driving the Networked Economy

6. LSDIS Introduction Slide 2 of 3: Enterprise Integration (Workflow Processes) DAML-S, projects at IBM METEOR-S Global Processes 2001- Semantic Web Processes (e-services, dynamic trading processes) Exotica, ADEPT, MOBILE, … Advanced Workflow 1995-2000 METEOR-2 Distributed workflows and e-Commerce METEOR-1 Early Workflow Mgmt 1990-1994 Centralized workflows

7. LSDIS Slide 3 of 3: Unique Attributes and Approach Extensive industry collaborations/partnerships (Boeing, MCC, Telcordia, CHREF, NIST, MCG, …) Commercial products from technology licensing and spin-offs: ADEPT/X Harness, METEOR EAppS and Semagix Freedom Research with well understood requirements/objectives (near or long term), focus on Enterprise Software, not just tools Real impact, not just papers

8. Processes driving the Networked Economy “Companies distributed over space, time, and capability will have to come together to deliver products and solutions in global marketplace. Processes are already becoming chief differentiating and the competitive force in the networked economy. Processes are becoming an organic part of doing business.” * From Sheth, Aalst et al, “Processes driving the Networked Economy” 1999

9. Architectures for Web Processes* Stages of architectural evolution Process Portal –one stop for e-services, p2p interactions between buyer and sellers –E-Gov, industry automation, Life Science Process Vortex –Interactions between buyer and seller through a third party marketmaker, predefined processes, shared ontology Dynamically Trading Processes * From Sheth, Aalst et al, “Processes driving the Networked Economy” 1999

10. BIG Challenge #1 from Enterprise to Global Scope: Scalability A CD N1N2F E B8 A1 A4 A1 A2 A4 B3 A1 A4 A6 A2 A5 Before (Enterprise,Inter-enterprise workflows) Discovery/Matchmaking should be accurate and scalable to the number of services available in Web A CD N1N2 F E A4 A1 A4 A1 A4 A1 A2 A1 B3 A1 B3 A1 A2 A1 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 A1 B3 A1 B3 A1 A4 A1 A2 A1 B3 A1 A4 A2 A1 B3 A1 A4 A1 A2 B3 A1 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 A1 A4 A1 A4 A1 A2 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 A1 A4 A1 A4 A1 A4 A1 A2 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 B3 A1 A4 A1 A2 A1 A4 A1 A4 A1 A4 A1 A2 A1 A4 A1 A2 A1 A4 A1 B3 A1 B3 A1 A4 A1 A2 A1 B3 A1 A4 A1 A2 A1 A2 A1 A4 A2 A4 A2 A1 B3 A1 A4 A1 A2 A1 Now Semantics of the services Semantics of the activity (Data, Functional, Execution, QoS)

11. BIG Challenges Scalability from Enterprises to the Web (Global) –Machine understandable description to support discovery, composition, etc. Dynamic nature of business interactions –Dynamic discovery, service selection, composition,.. Handle heterogeneity and autonomy –Syntactic, semantic and pragmatic –Complex rules/regulations related to B2B and e- commerce interactions

12. METEOR-S @ LSDIS Lab Proposition: Semantics is the most important enabler. METEOR-S exploits Workflow, Semantic Web, Web Services, and Simulation technologies to meet these challenges in practical standards based framework. –Adding semantics to different layers of Web services conceptual stack –Applying Semantics in all steps of process lifecycle –Using ontologies to provide underpinning for information sharing and semantic interoperability

13. Relating SWP with the Semantic Web Gen. Purpose, Broad Based Scope of Agreement Task/ App Domain Industry Common Sense Degree of Agreement Informal Semi-Formal Formal Agreement About Data/ Info. Function Execution Qos Other dimensions: how agreements are reached, … Current Semantic Web Focus Semantic Web Processes Lots of Useful Semantic Technology (interoperability, Integration)

14. Semantics for Web Services Data/Information Semantics –What: Formal definition of data in input and output messages of a web service –Why: for discovery and interoperability –How: by annotating input/output data of web services using ontologies Functional/Operational Semantics –Formally representing capabilities of web service –for discovery and composition of Web Services –by annotating operations of Web Services as well as provide preconditions and effects; also annotating TPA/SLA – all using ontology(-ies) Execution Semantics –Formally representing the execution or flow of a services in a process or operations in a service –for analysis (verification), validation (simulation) and execution (exception handling) of the process models –using State Machines, Petri nets, activity diagrams etc. QoS Semantics (possibly part of above types) –Formally describing operational metrics of a web service/process: cost, time, reliability,.. –To select the most suitable service to carry out an activity in a process –using QoS model [Cardoso and Sheth, 2002] for web services (part of TPA/SLA model?)

15. Data / Information Semantics Development / Description / Annotation WSDL, WSEL DAML-S Meteor-S (WSDL Annotation) Publication / Discovery UDDI WSIL, DAML-S METEOR-S (P2P model of registries) Composition (Choreography?) BPEL, BPML, WSCI, WSCL, DAML-S, METEOR-S (SCET,SPTB) Execution (Orchestration?) BPWS4J, Commercial BPEL Execution Engines, Intalio n3, HP eFlow Semantics for Web Process Life-Cycle

16. Data / Information Semantics Publication / Discovery WSDL, WSEL DAML-S Meteor-S (WSDL Annotation) UDDI WSIL, DAML-S METEOR-S (P2P model of registries) BPWS4J, Commercial BPEL Execution Engines, Intalio n3, HP eFlow Development / Description / Annotation Composition (Choreography?) Execution (Orchestration?) BPEL, BPML, WSCI, WSCL, DAML-S, METEOR-S (SCET,SPTB) Semantics for Web Service Life-Cycle

17. Functional / Operational Semantics Publication / Discovery WSDL, WSEL DAML-S Meteor-S (WSDL Annotation) UDDI WSIL, DAML-S METEOR-S (P2P model of registries) BPWS4J, Commercial BPEL Execution Engines, Intalio n3, HP eFlow Development / Description / Annotation Composition (Choreography?) Execution (Orchestration?) BPEL, BPML, WSCI, WSCL, DAML-S, METEOR-S (SCET,SPTB) Semantics for Web Service Life-Cycle

18. QoS Semantics Publication / Discovery WSDL, WSEL DAML-S Meteor-S (WSDL Annotation) UDDI WSIL, DAML-S METEOR-S (P2P model of registries) BPWS4J, Commercial BPEL Execution Engines, Intalio n3, HP eFlow Development / Description / Annotation Composition (Choreography?) Execution (Orchestration?) BPEL, BPML, WSCI, WSCL, DAML-S, METEOR-S (SCET,SPTB) Semantics for Web Service Life-Cycle

19. Execution Semantics Publication / Discovery WSDL, WSEL DAML-S Meteor-S (WSDL Annotation) UDDI WSIL, DAML-S METEOR-S (P2P model of registries) BPWS4J, Commercial BPEL Execution Engines, Intalio n3, HP eFlow Development / Description / Annotation Composition (Choreography?) Execution (Orchestration?) BPEL, BPML, WSCI, WSCL, DAML-S, METEOR-S (SCET,SPTB) Semantics for Web Service Life-Cycle

20. Publication / Discovery WSDL, WSEL DAML-S Meteor-S (WSDL Annotation) UDDI WSIL, DAML-S METEOR-S (P2P model of registries) BPWS4J, Commercial BPEL Execution Engines, Intalio n3, HP eFlow Semantics Required for Web Processes Execution Semantics QoS Semantics Functional / Operational Semantics Data / Information Semantics Development / Description / Annotation Composition (Choreography?) Execution (Orchestration?) BPEL, BPML, WSCI, WSCL, DAML-S, METEOR-S (SCET, SPTB) Semantics for Web Service Life-Cycle

21. Semantics at Different Layers of Web Service Conceptual Stack 1 Publication Discovery Description Messaging Network Flow Description Layer: Why: Reason about the functionality of the services and the semantics of the I/O data How: Using Ontologies to semantically annotate WSDL constructs (conforming to extensibility allowed in WSDL specification version 1.2) to sufficiently explicate the semantics of the –data types used in the service description, and –functionality of the service Semantics Types: Data, Functional and QoS Present scenario: WSDL descriptions are mainly syntactic (provides operational information and not functional information) Semantic matchmaking is not possible 1 [Kreger]

22. How to Annotate ? Map Web service’s input/output data as well as functional description using relevant data and function/operation ontologies, respectively How ? –Borrow from schema matching –Semantic disambiguation between terms in XML messages represented in WSDL and concepts in ontology

23. Semantic Annotation IOParametersMatch (w,o) = LingusticMatch (w,o) + StructureMatch (w,o) + ContextMatch (w,o) LingusticMatch (w,o) => –NameMatch with stemming –Description Match –SynonymsMatch –HypernymRelation (w is a kind of o) : prevailing_speed is a type of speed of a wind i.e. windSpeed –HyponymRelation (o is a kind of w) –Acronyms : Sea Level Pressure has acronym SLP StructureMatch (w,o) => –subTree(w) == subTree(o) ContextMatch –Name of the parent concept provides some insight to the context of the term Patil, Oundhakar, Sheth, SAWS Techincal Report

24. Semantic Annotation: Data Semantics WindEvent windSpeed WeatherEvent windDirection PressureEvent AltimeterSettingwindGustSpeed SeaLevelPressure PressureChangeEvent Class Property Patil, Oundhakar, Sheth, SAWS Techincal Report Ontology : weather-ont.daml WSDL : GlobalWeather.wsdl 0.756 0.69 0.9 0.5 0.8 0.23 1.0

25. Semantic Annotation: Functional Semantics Patil, Oundhakar, Sheth, SAWS Techincal Report WeatherFunctions getWeather getStation getWind getPressure getTemperature getStationByZip getStationByCountry A Sample Functional Ontology WSDL Operations

26. Publication Discovery Description Messaging Network Flow Publication and Discovery Layers: Why: Enable scalable, efficient and dynamic publication and discovery (machine processability / automation) How: Use of ontology to categorize registries based on domains and characterize them by maintaining the 1. properties of each registry 2. relationships between the registries Capturing the WSDL annotations in UDDI so others can use for discovery Semantics Types: Data, Functional and QoS Present scenario: Suitable for simple searches ( like services offered by a provider, services that implement an interface, services that have a common technical fingerprint etc.) Categories are too broad Automated service discovery (based on functionality) and selecting the best suited service is not possible Semantics at Different Layers of Web Service Conceptual Stack 1

27. Publication Discovery Description Messaging Network Flow Flow Layer: Why: Design (composition), analysis (verification), validation (simulation) and execution (exception handling) of the process models To employ mediator architectures for automated composition, control flow and data flow based on requirements How: Using –Functionality/preconditions/effects of the participating services –Knowledge of conversation patterns supported by the service –Formal mathematical models like process algebra, concurrency formalisms like State Machines, Petri nets etc. –Simulation techniques Semantics Types: Data, Functional, QoS and Execution Present Scenario: Composition of Web services is static. Dynamic service discovery, run-time binding, analysis and simulation are not supported directly Semantics at Different Layers of Web Service Conceptual Stack 1

28. Semantics in WS stack and METEOR-S Components Publication Discovery Description Messaging Network Flow MWSDI: Scalable Infrastructure of Registries for Semantic publication and discovery of Web Services MWSDI: Semantic Annotation of WSDL (WSDL-S) MWSCF: Semantic Web Process Composition Framework

29. METEOR-S components for Semantic Web Services METEOR-S Discovery Infrastructure (MWSDI) –Semantic Annotation and Discovery of Web Services 1 –Semantic Peer-to-Peer network of Web Services Registries 2 METEOR-S Composer (MWSCF) –Service Composition and Execution Tool 3 –Semantics Process Template Builder and Process Generator 4 –QoS Management Specify, compute, monitor and control QoS (SWR algorithm) 5 Orchestrator (Under development) –Analysis and Simulation 6, Execution, Monitoring 6 1 [Sivashanmugam et al.-1], 2 [Verma et al.], 3 [Chandrasekaran et al.], 4 [Sivashanmugam et al.-2], 5 [Cardoso et al.], 6 [Silver et al.]

30. METEOR-S Web Service Discovery Infrastructure (MWSDI)  uses Functional, Data semantics for service discovery  uses QoS semantics for service selection

31. Search retrieves lot of services (irrelevant results included) Which service to select ? How to select? UBR Registry is universal and provides non-semantic search Keyword match, taxonomy The problem in discovery..

32. Registries are categorized Select relevant registries (semantic filtering) Select best matched service Domain Registry Registry is domain specific and supports semantic search Ontology Scalable Solution..

33. Search for services to book air ticket (using categories)* unspsc-org: unspsc:3-1 –Travel, Food, Lodging and Entertainment Services Travel facilitation –Travel agents »Travel agencies Services: 3 records found. –AirFares Returns air fares from netviagens.com travel agent –Hotel reservations Reservations for hotels in Asia, Australia and New Zealand –Your Vacation Specialists Web enabled vacation information Providers: 2 records found. * Search carried out in one of the Universal Business Registries

34. Search for services to book air ticket (using keywords)* air ticket –1 record with name air tickets booking airticket, ticketbooking, airtravel, air travel, travel agent, airticketbooking, air ticket booking, travel agency, travelagency –0 records were returned travelagent –1 record with name travelagent test 4 services: BookFlight, cancelFlightBooking etc. Descriptions say that both these services are “XML based Web services” No URL for WSDL Travel –15 records. Purpose/functionality understood from descriptions 2 services : TravelBooks 4 services : TravelInformation 2 services : Reservation and cancallation of travel tickets 1 service : Emergency Services for travellers 1 service : Travel documentation and itinerary 5 services : Description is ambiguous/not present * Search carried out in one of the Universal Business Registries

35. Use of ontologies enables shared understanding between the service provider and service requestor Semantic Publication and Discovery Extract details from WSDL file Annotate the WSDL details using ontologies Construct Service Requirement template Annotate using ontologies Discover services based on the template annotations

36. WSDL-S (WSDL with Semantic Annotation) Mapping Input and Output Message Parts to Ontology –XML Schema elements used in Input/Output messages do not reflect the semantics of the data involved in Web Service operation –Use of ontologies or standard vocabulary* brings service provider and requestor to common conceptual space providing well defined semantics for operational data Mapping Operations to Ontology –Service selection involves discovering appropriate WSDL description and locating an operation to invoke –Operations with same signature could have different functionalities –Ontology or vocabulary depicting functionality is used for annotation Additional tags to represent pre-conditions and effects of each operation (should be added to next ver. of WSDL?) –Preconditions and effects are added for each operation –Can be optionally used for service discovery and selection * RosettaNet Business/Technical dictionary or ebXML Core Component catalog/dictionary The focus of our work is not in developing ontologies for representing functionality/preconditions/effects but to use such ontologies for semantic annotation

37. Annotation Syntax* Each Operation in WSDL is annotated using an fully qualified attribute name-value pair in the operation element under portType element. The attribute name is operation-concept Each Message part is annotated using a fully qualified attribute name-value pair in the part element under message element. The attribute name is onto-concept Preconditions and effects are respectively represented using fully qualified additional tags with the names precondition and effect. These elements have two attributes name (optional) and precondition-concept (or effect-concept). Each operation can have multiple precondition and effect elements. * conforms to extensibility support in WSDL version 1.2

38. WSDL Annotation Example <wsdl:definitions xmlns:TravelOnto=lsdis.cs.uga.edu//METEORS/TravelServiceOntology.daml ….. >lsdis.cs.uga.edu//METEORS/TravelServiceOntology.daml

39. Semantics in UDDI tModels are used to categorize and characterize service entries in UDDI (limited form of semantics) Our approach uses categorizes* (using metadata constructs tModels and CategoryBags) the services in UDDI based on the semantic annotations * similar to [Paolucci et al.]

40. Semantic Categorization of Services in UDDI* Service KeyedReferenceGroup (SemanticGroupTModelKey) KeyedReferenceGroup (SemanticGroupTModelKey) CategoryBag TmodelKey:OperationalTModelKey, Value:TicketBooking, Name:buyTicket TmodelKey:InputTModelKey, Value:TicketInformation TmodelKey:OutputTModel, Value:ConfirmationMessage * conforming to UDDI Version 3 spec [UDDI-v3] TmodelKey:OperationalTModelKey, Value:TicketCancellation, Name:cancelTicket TmodelKey:InputTModelKey, Value:TicketInformation TmodelKey:OutputTModel, Value:ConfirmationMessage For the example discussed earlier: Travel Arrangement Service with two operations buyTicket and cancelTicket

41. Semantic Categorization of Services in UDDI* Service KeyedReferenceGroup (SemanticGroupTModelKey) KeyedReferenceGroup (SemanticGroupTModelKey) CategoryBag TmodelKey:OperationalTModelKey, Value:TravelOnto:TicketBooking, Name:buyTicket TmodelKey:InputTModelKey, Value:TravelOnto:TicketInformation TmodelKey:OutputTModelKey, Value:GeneralTradeOnto:ConfirmationMessage TmodelKey:OperationalTModelKey, Value: TravelOnto:TicketCancellation, Name:cancelTicket TmodelKey:InputTModelKey, Value: TravelOnto:TicketInformation TmodelKey:OutputTModelKey, Value: GeneralTradeOnto: ConfirmationMessage Functional/Operational Semantics: Operation-ontology mapping in WSDL for buyTicket operation * conforming to UDDI Version 3 spec [UDDI-v3]

42. Semantic Categorization of Services in UDDI* Service KeyedReferenceGroup (SemanticGroupTModelKey) KeyedReferenceGroup (SemanticGroupTModelKey) CategoryBag TmodelKey:OperationalTModelKey, Value:TicketBooking, Name:buyTicket TmodelKey:InputTModelKey, Value:TravelOnto:TicketInformation TmodelKey:OutputTModelKey, Value: GeneralTradeOnto:ConfirmationMessage TmodelKey:OperationalTModelKey, Value:TravelOnto:TicketCancellation, Name:cancelTicket TmodelKey:InputTModelKey, Value: GeneralTradeOnto:TicketInformation TmodelKey:OutputTModel, Value: GeneralTradeOnto:ConfirmationMessage Data/Information Semantics: Input Message part-ontology mapping in WSDL for buyTicket operation * conforming to UDDI Version 3 spec [UDDI-v3]

43. Semantic Categorization of Services in UDDI* Service KeyedReferenceGroup (SemanticGroupTModelKey) KeyedReferenceGroup (SemanticGroupTModelKey) CategoryBag TmodelKey:OperationalTModelKey, Value:TicketBooking, Name:buyTicket TmodelKey:InputTModelKey, Value:TravelOnto:TicketInformation TmodelKey:OutputTModelKey, Value: GeneralTradeOnto:ConfirmationMessage TmodelKey:OperationalTModelKey, Value:TravelOnto:TicketCancellation, Name:cancelTicket TmodelKey:InputTModelKey, Value: GeneralTradeOnto:TicketInformation TmodelKey:OutputTModel, Value: GeneralTradeOnto:ConfirmationMessage Data/Information Semantics: Output Message part-ontology mapping in WSDL for buyTicket operation * conforming to UDDI Version 3 spec [UDDI-v3]

44. Discovery using UDDI V1 API Our implementation used UDDI Version 1 API –KeyedReferenceGroups are not supported –Each operation is grouped with its operation-concept, input and output onto-concepts each as a keyedReference in the keyedReferenceVector as tModelKey = “OpTModel” KeyValue = “operation-concept” KeyName = “OpName” tModelKey = “InTModel” KeyValue = “onto-concept” KeyName = “OpName” tModelKey = “OutTModel” KeyValue = “onto-concept” KeyName = “OpName” OpTModel: Key for the tModel representing functional semantics of the operation named “OpName” in a WSDL file linked to the UDDI entry InTModel: Key for the tModel representing semantics of the inputs of the operation named “OpName” in the WSDL OutTModel: Key for the tModel representing semantics of the outputs of the operation named “OpName” in the WSDL operation-concept: Fully qualified Id of a class in a functional ontology represented by OpTModel onto-concept: Fully qualfied Id of a class in a ontology that is used to annotate inputs (or outputs) represented by InTModel (or OutTModel)

45. Summary of Steps in Discovery 1.Services selection based on the functional requirements Using operation-ontology mapping 2.Ranking based on semantic similarity based on input/output semantics of candidate services and requirement template Using message part-ontology mapping 3.Optional step includes semantic similarity based on semantics of preconditions/effects of the candidate services and requirement template Using precondition and effect tags

46. METEOR-S Web Service Composition Framework (MWSCF)

47. Template Builder Activity Interfaces Process Templates UDDI Ontologies Execution Engine Process Generator Process Designer Repositories Discovery Infrastructure (MWSDI) Repositories are used to store 1. Web Service Interfaces 2. Ontologies 3. Process Templates Process Designer 1. Template Construction activity specification using - interfaces - services - semantic activity templates - other details 2. Process Generation - Service discovery (automatic) and selection (semi-automatic) - Data flow MWSCF Architecture Process Execution 1. Validation and deployment 2. Executing the process using a client

48. Web Process Life-Cycle Find Matches Rank Services Select a Service Discovery Add to Process Data Transformation Data Flow Composition Generate Process Validate Syntax Execute Execution Design Create Process WSDL Create Process Template and Add Activities Add Control Flow Find Ontologies & Annotate Activity Requirements

49. Template Construction Discovery not needed Process Template can be constructed with 3 types of activities –Concrete Web Service Implementation activity is bound to Web service by linking it to a WSDL file and an operation in it –Web Service Interface activity is bound to a Web service interface by linking it to a interface identifier (which is linked to a WSDL file ) and an operation in it –Semantic Activity Template activity is semantically enriched by linking it to semantic specifications of its inputs/outputs/functionality/precondition and effects

50. Template Construction QoS requirements are specified too Process Template can be constructed with 3 types of activities –Concrete Web Service Implementation activity is bound to Web service by linking it to a WSDL file and an operation in it –Web Service Interface activity is bound to a Web service interface by linking it to a interface identifier (which is linked to a WSDL file ) and an operation in it –Semantic Activity Template activity is semantically enriched by linking it to semantic specifications of its inputs/outputs/functionality/precondition and effects

51. Process Generation Template Repository Process Generator Template Customized Template Executable BPEL Process BPEL Execution Engine Manual service selection & data flow

52. Template Construction

53. Process Generation

59. Advantages of Semantic Process Template Flexible and rapid approach to process composition –Configuration and re-use of templates –Process is not bound to any Web service intefaces or implementations. (partners/services can be dynamically changed) –Template/Process designer need not perform discovery of services. Discovery can be delegated to the tool Well defined semantics for each activity –Using ontologies –Richer description of semantics of activities Can be generated in executable process in any standard Process re-design is easier Can be advertised/published as reference/business models for reuse across vertical industry segments

60. Conclusion Semantics can help address big challenges related to scalability, dynamic environments,.. But comprehensive approach to semantics will be needed: –Data/information, function/operation, execution, QoS Semantic (Web) principles and technology bring new tools and capabilities that we did not have in EAI, workflow management of the past More at: http://lsdis.cs.uga.edu/SWP.htm

61. References [Kreger] http://www-3.ibm.com/software/solutions/webservices/pdf/WSCA.pdfhttp://www-3.ibm.com/software/solutions/webservices/pdf/WSCA.pdf [Sivashanmugam et al.-1] Adding Semantics to Web Services Standards [Sivashanmugam et al.-2] Framework for Semantic Web Process Composition [Verma et al.] MWSDI: A Scalable Infrastructure of Registries for Semantic Publication and Discovery of Web Services [Chandrasekaran et al.] Performance Analysis and Simulation of Composite Web Services [Cardoso et al.] Modeling Quality of Service for Workflows and Web Service Processes [Silver et al.] Modeling and Simulation of Quality of Service for Composition of Web Services [Paolucci et al.] Importing Semantic Web in UDDI [UDDI-v3] http://uddi.org/pubs/uddi-v3.00-published-20020719.htm More at: http://lsdis.cs.uga.edu/SWP.htm Extensive related work at: IBM, Karlsruhe, U. Manchester, DAML-S (CMU, Stanford, UMD)

62. Now, what can we do together?