Knowledge enable Information & Services Science Kno.e.sis CenterKno.e.sis Wright State University, Dayton, OH. Role of semantics in Autonomic & Adaptive Web Services and Processes Amit Sheth LexisNexis Ohio Eminent Scholar Amit Sheth LexisNexis Ohio Eminent Scholar

Historical work - samples 1."From Contemporary Workflow Process Automation to Adaptive and Dynamic Work Activity Coordination and Collaboration", Keynote Address at the Workshop on Workflows in Scientific and Engineering applications, Toulouse, France, September Y. Han, A. Sheth, K. Bussler, "A Taxonomy of Adaptive Workflow Management," CSCW-98 Workshop Towards Adaptive Workflow Systems, November 14, A. Sheth, W. Aalst, and I. Arpinar, “Processes Driving the Networked Economy,” IEEE Concurrency, 7 (3), July-September 1999, pp Several projects in 1990s that dealt with adaptive and dynamic workflows (ADEPT, eFlow, METEOR, WAMO, etc.)

Talk focus Need a rich representational framework to capture requirements and capabilities to support adaptive and autonomic services and processes SEMANTICS Earlier work on adaptive and dynamic workflows/business processes What has changed? SAWSDL became W3C Candidate Recommendation last week.

Aspect of Agreement Gen. Purpose, Broad Based Scope of Agreement Task/ App Domain Industry Common Sense Technical PeopleOrganization Agreement About Data/ Info. Functional Non Functional Execution Ontologies to Describe Service Semantics (ontologies are about agreements) METEOR-S Implementation Layer (Databases, OS, etc.) Execution Layer (SOA Based IT Processes and Services) Strategy Layer (Corporate Strategy and Goals) Operational Layer (Modeling Business Process to provide business services) Strategy Layer Requirement: Only Provide customer support to gold customer IT Layer Requirement: If cost > $$$$, customer = gold Autonomic Web Process* Self Healing Agile Self Optimizing Self Configuring * it’s about the business, not just computing resources

Semantics for Services Lifecycle Data/Information Semantics What: (Semi-)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 Model References on Messages in SAWSDL Functional Semantics (Semi-) 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 Model References on Operations in SAWSDL Non Functional Semantics ( WS-*) (Semi-) formally represent qualitative and quantitative measures of Web process Non- Quantitative includes security, transactions Quantitative includes cost, time etc. Business constraints and inter service dependencies (Domain and application ontologies) Via attaching Semantically Enhanced Policies and Agreements to SAWSDL interfaces. Execution Semantics (Semi-) 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. Adding Semantics to Web Service Standards, ICWS 2003

SAWSDL + SemPol= Semantic Templates SAWSDL for data and functional semantics Semantic Policy Descriptions for non- functional semantics

Semantic Template in action Data Semantics Functional Semantics Non-Functional Semantics Non-Functional Semantics

Development / Description / Annotation WSDL, WSDL-S, SAWSDL, WSMO, OWL-S METEOR-S (MWSAF) Publication / Discovery (Semantic) UDDI METEOR-S (MWSDI) Composition, Configuration and Negotiation WS-BPEL, WS- Agreement, WS- Policy Execution, Adaptation and Mediation Oracle BPM, activeBPEL, WSMX Four types of semantics in services lifecycle

Data Semantics Development / Description / Annotation Execution, Adaptation and Mediation BPWS4J, activeBPEL. WSMX METEOR-S Composition, Configuration and Negotiation BPEL, WS- Agreement, WS- Policy METEOR-S (MWSCF) Publication / Discovery (Semantic) UDDI METEOR-S (MWSDI) WSDL, WSDL-S, SAWSDL, WSMO, OWL-S METEOR-S (MWSAF) Four types of semantics in services lifecycle

Functional Semantics Development / Description / Annotation Execution, Adaptation and Mediation BPWS4J, activeBPEL, WSMX METEOR-S Composition, Configuration and Negotiation BPEL, WS- Agreement, WS- Policy METEOR-S (MWSCF) Publication / Discovery (Semantic) UDDI METEOR-S (MWSDI) WSDL, WSDL-S, SAWSDL, WSMO, OWL-S METEOR-S (MWSAF) Four types of semantics in services lifecycle

Non Functional Semantics Development / Description / Annotation Execution, Adaptation and Mediation BPWS4J, activeBPEL, WSMX METEOR-S Composition, Configuration and Negotiation BPEL, WS- Agreement, WS- Policy METEOR-S (MWSCF) Publication / Discovery (Semantic) UDDI METEOR-S (MWSDI) WSDL, WSDL-S, SAWSDL, WSMO, OWL-S METEOR-S (MWSAF) Four types of semantics in services lifecycle

Execution Semantics Development / Description / Annotation Execution, Adaptation and Mediation BPWS4J, activeBPEL, WSMX METEOR-S Composition, Configuration and Negotiation BPEL, WS- Agreement, WS- Policy METEOR-S (MWSCF) Publication / Discovery (Semantic) UDDI METEOR-S (MWSDI) WSDL, WSDL-S, SAWSDL, WSMO, OWL-S METEOR-S (MWSAF) Four types of semantics in services lifecycle

Execution Semantics Non-Functional Semantics Functional Semantics Data Semantics Development / Description / Annotation Execution, Adaptation and Mediation BPWS4J, activeBPEL, WSMX METEOR-S Composition, Configuration and Negotiation BPEL, WS- Agreement, WS- Policy METEOR-S (MWSCF) Publication / Discovery (Semantic) UDDI METEOR-S (MWSDI) WSDL, WSDL-S, SAWSDL, WSMO, OWL-S METEOR-S (MWSAF) Four types of semantics in services lifecycle

Approaches to modeling Data Semantics Pre-defined agreement on all data fields Limited flexibility, hard to integrate new suppliers in process Use a standard like Rosetta Net/ebXML Greater flexibility, but limited to suppliers following standard Standard may not be expressive enough for everyone's needs Annotate data fields with domain ontologies Most flexible, semi-automatic transformation based on ontology mapping Ontology can be based on domain standard, while providing more flexibility and extensibility Data mediation can be realized using XSLT transformation, addressing data heterogeneities.

Capturing Data semantics using SAWSDL Annotation on input and output messages in WSDL documents Leaf level annotation for complex types Schema level annotation Example of message level annotation:

Representing mappings for data mediation Address xsd:string OWL ontology has_City has_StreetAddress has_Zip WSDL complex type element Mapping using XSLT: Add Meena et al, ICWS 2006 as refernece.

Functional Semantics Keyword based search in UDDI Needs human involvement Low precision and high recall Port Type based search in UDDI Requires service providers to agree on port types Less flexible, requires total agreement on method names and data type names Template Based Semantic Discovery Requires ontological commitment of data types and operations Can search on any or many aspects of description+interface Can have complex similarity measures and be used to provide ranked results based on similarity

Semantic Discovery Semantic based publication and discovery Unlike interface and operation based publication and discovery, semantics are modeled into UDDI data structures SAWSDL descriptions can be published and template based discovery is supported.

Non Functional Semantics Business and Application constraints

Non Functional Semantics Does the supplier support customer’s business constraints e.g. cost, supply time etc. Interaction should adhere to the entities’ policies e.g security, transactions In case of more suppliers, domain constraints should be satisfied e.g. a certain supplier’s parts do not work with other supplier’s parts Non functional semantics in a semantic template: Template level policy: Akin to service level policy. Operation level policy: Policy for a specific operation in the template.

Non Functional Semantics Used in lifecycle Agreement Matching Matching syntactically heterogeneous by semantically homogeneous agreements Dynamic Process Configuration Configuring process based on process constraint We will demonstrate how ontology-driven semantic approach supports these capabilities.

SWAPS: Use of Semantics in Agreement Matching An agreement is a collection of alternatives. A={Alt1, Alt2, …, AltN} An alternative is a collection of guarantees. Alt={G1, G2,...GN} A guarantee is defined as a collection- G={Scope, Obligated, SLO, Qualifying Condition, Business Value} There is a potential match between provider and consumer alternatives if: For all requirement of one alternative, there is a capability in other alternative, which has the same scope and the same obligation and the SLO of the capability satisfies the request. “requirement(Alt, G)” returns true if G is a requirement of Alt “capability(Alt, G)” returns true if G is an assurance of Alt “scope(G)” returns the scope of G “obligation(G)” returns the obligated party of G “satisfies(Gj, Gi)” returns true if the SLO of Gj is equivalent to or stronger than the SLO of Gi An alternative Alt1 is a suitable match for Alt2 if: ("  Gi) such that Gi  Alt1  requirement(Alt1, Gi)  ($  Gj) such that Gj  Alt2  capability(Alt2, Gj)  scope(Gi) = scope(Gj)  obligation(Gi) = obligation(Gj)  satisfies(Gj, Gi)

WS-Agreement Definition and Ontology GuaranteeTerm Scope ServiceLevelObjectivev OWL ontology Predicate Parameter hasScope hasObjective Unit Value hasCondition Qualifying Condition Predicate Parameter Unit Value BusinessValue Penalty Reward hasReward hasPenalty hasGuaranteeTerm Importance hasImportance hasBusinessValue Assessment Interval ValueExpression ValueUnit TimeIntervalCount Assessment Interval ValueExpression ValueUnit TimeInterval Count An agreement consists of a collection of Guarantee terms A guarantee term has a scope – e.g. operation of service A guarantee term may have collection of service level objectives e.g. responseTime < 2 seconds A guarantee term may have a qualifying condition for SLO’s to hold. e.g. numRequests < 100 There might be business values associated with each guarantee terms. Business values include importance, confidence, penalty, and reward. e.g. Penalty 5 USD Agreement represented as an instance of ontology

Using Semantic Agreements with SAWSDL Time Domain Independent QoS WS-Agreement Ontology Guarantee SLO Obligated BV Scope Predicate Greater Less Quality Moistur e Weight Split Pric e FarmerAdd r Crop Agriculture Ontology GetMoisture GetWeight GetPrice GetSplits Merchant Service WSDL-S WS-Agreement agri:moisture less 12% obligated: less 12% agri:splits less 20% agri:weight greater 54 lbs agri:price equals 10 USD Input: Address Merchant WS-Agreement Domain Dependent Adding Semantics to Agreements: Improves Monitoring and Negotiation Improves the accuracy of matching Adding Semantics to Web Services: Enables more accurate discovery and composition.

SWAPS Ontologies  WS-Agreement: individual agreements are instances of the WS-Agreement ontology  Temporal Concepts: time.owl (OWL version of DAML time  Concepts: seconds, dayOfWeek, ends  Quality of Service: Max Maximilien’s QoS ontology (IBM) -> Ont-Qos  Concepts: responseTime, failurePerDay  Domain Ontology: an ontology used to represent the domain

Dynamic Process Configuration Find optimal partners for the process based on process constraints – cost, supply time, etc. Conceptual Approach 1.Create framework to capture represent domain knowledge 2.Represent constraints on the domain knowledge 3.Ability to reason on the constraints and configure the process

Dynamic Process Configuration Research Challenges Capturing functional and non-functional requirements of the Web process (Abstract process specification) Discovering service partners based on functional requirements (Semantic Web service discovery) Choosing optimal partners that satisfy non- functional requirements (Constraint Analysis) K. Verma, R. Akkiraju, R. Goodwin, P. Doshi, J. Lee, On Accommodating Inter Service Dependencies in Web Process Flow, AAAI Spring Symposium on Semantic Web Services, 2004 R. Aggarwal, K. Verma, J. A. Miller, Constraint Driven Composition in METEOR-S, SCC K. Verma, K.Gomadam, J. Miller and A. Sheth, Configuration and Execution of Dynamic Web Processes, LSDIS Lab Technical Report, 2005.

Autonomic Web Process Vision K. Verma, A. Sheth. Autonomic Web Processes. In Proceedings of the Third International Conference on Service-oriented Computing (ICSOC), Vision Paper (invited), LNCS 3826, Springer Verlag, 2005, pp

Extending service skeleton to handle business level exceptions

Technical Details to Follow Karthik Gomadam Creating infrastructure for dynamic configuration Identifying events from semantic templates Prashant Doshi MDP based approach to adaptation in Web processes.

Conclusions Four types of semantics Data, Functional, Non-Functional and Execution Semantics. Role played in the lifecycle of Web process Modeling data, functional and non-functional semantics using semantic templates Capturing the four types of semantics using SAWSDL Vision of Autonomic Web process Modeling service execution using service skeletons. More at