Semantic Business Process Management

Transcription

1 Arbeitsgruppe Lecture Semantic Business Process Management Prof. Dr. Adrian Paschke Corporate Semantic Web (AG-CSW) Institute for Computer Science, Freie Universitaet Berlin

2 Overview Semantic Business Process Management Retrospective of the SBPM course

3 Semantic Business Process Managment SBPM Ontology-based BPM Rule-based BPM (intelligent BPM) Event-driven BPM

4 Ontologies in Business Process Modeling Ontology Semantic-enriched Business Process Model

5 Semantic Extension of Information Entities in BPMN Utilize corporate or domain ontology concepts to define information flow on a non-technical conceptual level suitable for business process experts due to formal nature consistent link between the business or conceptual level and underlying technical information models can be derived formal domain information models are foundation for semantic mediation between heterogeneous conceptualizations used by different organizations or domains

6 SBPM: Homogenous Integration of Rules in BPMN 2.0 Option 1

7 SBPM: Heterogeneous Integration of Rules in BPMN 2.0 Option 2

8 Semantic Business Process Execution with Semantic Web Services Semantic Web Service Service Customer/User Service Using Application Semantic WSDL Service Provider Web Service Application Business Processes Business Vocabulary (Ontologies) ITSM (Rules) Semantic SLA Non-functional Properties Response Time Delay / Availability Resource Utilization Functionality Guarantees Pricing /Policies Rights & Obligations Escalation Business Vocabulary (Ontologies) ITSM (Rules) Enterprise Application Components Services Approaches OWL-S (former DAML-S), WSDL-S RBSLA SAWSDL Hardware SWWS / WSMF WSMO / WSML Meteor-S SWSI

9 Rule-based BPEL (Semantic BPEL) Rules-enabled BPEL Application events, facts BRMS (Business Rules Management System) CEP Logic Ontology / Model Mapping Vocabularies / Semantic Ontology Models results Reaction Logic Decision Logic BPEL run-time Constraints Rule Inference Service Rule Interchange Rule Repositories

10 BPEL + Rules Rules engines can be invoked as a Semantic Decision / Inference Service from a BPEL process. Dynamic processing Intelligent routing Validation of policies within process Constraint checks Ad-hoc Workflow Policy based task assignment Various escalation policies Load balancing of tasks Business Activity Monitoring Alerts based on certain policies and complex event processing (rule-based CEP) Dynamic processing based KPI reasoning BPEL Process Manager and Rules together enable agile and adaptive business processes

11 Rule Inference Service - Usage 1. Create Decision Service Select Rule Connection Create service based on interaction pattern. Select input and output facts / events 2. Invoke rules from Process Call rule inference service Map BPEL variables to input and output facts (results) 3. Most common patterns include Execute function (stateless) Assert-Execute-Watch (stateless) Assert, Assert. Execute, Watch (stateful)

12 Rule-based BPEL How To Do It? 1. Create a rule inference service with rule repository Create semantic interface description of the inference service 2. Create a new Inference Service Partnerlink Choose a rule connection Choose an interaction pattern and parameter bindings 3. Add a Decide Activity Bind BPEL variables to parameters of partnerlink

13 Orchestrated BPEL + Choreography Rule Workflow Rules can be used to implement choreography workflows as subprocesses in the BPEL flow Workflows might span several communicating (messaging) rule inference services Rules-enabled BPEL Application events, facts results BRMS (Business Rules Management System) CEP Logic Reaction Logic Decision Logic Constraints % receive query and delegate it to another party rcvmsg(cid,esb, Requester, acl_query-ref, Query) :- responsiblerole(agent, Query), sendmsg(sub-cid,esb,agent,acl_query-ref, Query), rcvmsg(sub-cid,esb,agent,acl_inform-ref, Answer),... (other goals)... sendmsg(cid,esb,requester,acl_inform-ref,answer). BPEL runtime Rule Inference Service

14 Example: Rule Responder Project

15 Example BPEL + Ontology: sbpel Ontology of the SUPER Project SUPER Execution 1 Execute Task Semantic BPEL Execution Engine Semantic Execution Environment 15

16 What it missing for SBPM? Process / Event / State / Action Ontologies The ability to interchange semantic models across major BPM & BRMS vendors would dramatically increase the market for reusable, enterpriserelevant knowledge. The lack of ontology for events, processes, states, actions, and other concepts that relate to change over time limits rules or logic that govern processes or react to events to implementations rather than declarative knowledge Knowledge modeling / representation should be integrated into the context of BPM and CEP

17 What is missing for SBPM? Rules and Processes Integration is loose and inadequate Rules have no visibility to process or state Decisions are isolated from processes Governance of processes by rules is not addressed Definition of processes by logic is not addressed no precise logical semantics in e.g. BPMN no declerative representation, only static syntactical flow descriptions Logical and business rules are 2 nd class citizens Knowledge management is denigrated Rules are merely implementation

18 Semantic BPM: easier & better Each (graphical) syntax concept in a BPM model is using an ontology concept that references the semantics of it Processes have causality and roles Semantic inferences result in findings inferences are performed by inference agents/services The object / result of inference are process knowledge

19 Semantic CEP: easier & better Managing state becomes much simpler a plane is no longer flying after it lands a plane begins flying when it takes off Knowing that events and processes occur allows when (and where) to be understood a landing starts when a plane approaches CEP becomes simpler with a BRMS that understands aggregates over time that understands tense wrt states and processes

20 Summary Key Benefits of SBPM Semantic Business Process Management = combination of Corporate Semantic Web technologies, such as rules, events and ontologies, with BPM Goals enhanced automation in discovery, configuration and composition of appropriate process components, information objects, and services automated mediation between different heterogeneous interfaces and abstraction levels targeted complex queries on the process space and flow much more agile business process management. Key benefits: Complementary technologies: semantic technologies + ITSM/BPM technologies BPMN-BPEL for orchestration of services, systems, people & partners Rules focus on decision making and policies Rules can be used to integrate choreography sub-workflows in orchestrated BPEL processes Declarative specification of constantly changing business policies and regulations Enables business users to participate in business processes Modify and apply new rules without redeploying processes Centralized policy management across the organization

21 Retrospection of the SBPM course

22 Goals The assumption behind Business Process Management (BPM) is, that the uniqueness of an enterprise lies in the way how it manages and executes its business processes. Deepen the knowledge about BPM in combination with modern Corporate Semantic technologies Methods, Technologies, Standards and Tools in SBPM

23 Lecture 1: Introduction BPM

24 Lecture 2: Modeling with UML

25 Lecture 3: Business Process Management Standards BPDM 1.1 BPMN 2.0 BPEL 3.0 Source: Martin Bartonitz/Saperion

26 Lecture 4: Interworkflows with BPEL

27 Lecture 5: Semantic Computing I Ontologies - OMG Ontology Definition Metamodel

28 Lecture 6: Semantic Computing II Ontologies - W3C Web Ontology Language 2 <owl:subclass owl:name="person"> <owl:super> <Class "Animal"/></owl:super> <owl:restriction> <owl:property resouce="hasparent"> <owl:range> <owl:class owl:id="person"/> </owl:range> </owl:property> </owl:restriction> <owl:restriction> <owl:property resource="hasfather exactly= 1"/> </owl:restriction> </owl:subclass> OWL

29 Lecture 7+8: Semantic Computing III & IV Business Rules / Web Rules / Event/Actions Users employ rules to express what they want, the responsibility to interpret this and to decide on how to do it is delegated to an interpreter Represent knowledge in a way that is understandable by the business, but also executable by rule engines, thus bridging the gap between business and technology PRR ILog IRL SBVR RuleML RIF Blaze SRL Prova

30 Lecture 9: Semantic Web Services Semantic Web Service Service Customer/User Service Provider Business Processes Service Using Application Semantic WSDL Web Service Application Application Components Business Vocabulary Contract / SLA Management Semantic SLA Non-functional Properties Response Time Delay / Availability Resource Utilization Functionality Guarantees Pricing /Policies Rights & Obligations Escalation Business Vocabulary Contract / SLA Management Services Hardware Approaches OWL-S (former DAML-S), WSDL-S RBSLA SAWSDL Super SWWS / WSMF WSMO / WSML Meteor-S SWSI

31 Lecture 10: Semantic Complex Event Processing

32 Lecture 11: Summary & Outlook "Advanced Agile Semantic Business Process Management" Rules-enabled BPEL Application events, facts BRMS (Business Rules Management System) Ontology / Model Mapping Vocabularies / Semantic Ontology Models CEP Logic Reaction Logic result s Decision Logic BPEL runtime Constraints Rule Inference Service Rule Interchan ge Rule Repositories

33 12: Final Exam Written Exam Monday, July 11th, 2pm 90 minutes

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