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Knowledge-intensive Business Processes

Knowledge-intensive Business Processes. Business Process Technology Group Knowledge Processing and Information Systems Winter Semester 2012/2013. Agenda. Official Information Seminar Timeline Deliverables Topic Overview Topics Organizational Aspects. Official Information.

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Knowledge-intensive Business Processes

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  1. Knowledge-intensive Business Processes Business Process Technology Group Knowledge Processing and Information Systems Winter Semester 2012/2013

  2. Agenda • Official Information • Seminar Timeline • Deliverables • Topic Overview • Topics • Organizational Aspects Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  3. Official Information • Title: Knowledge-intensive Business Processes • Cooperation with colleague Prof. TorstenSchaub • Credit Points: 3 (graded) • SWS: 2 • Registration Deadline: 31st October 2012 Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  4. Seminar Timeline Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  5. Deliverables • 10 Pages • LNCS Style • PDF Format • 20 Minutes Talk + 10 Minutes Discussions • Focus: Overview of the whole work • Feedback session afterwards Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  6. Topic Selection • Send an E-Mail to andreas.meyer@hpi.uni-potsdam.de including: • Name • Student ID number • Three topics ranked by your preference Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  7. Topic Overview Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  8. eGovernment Process Knowledge OntologyBPM Knowledge Interdependencies in the Public Administration Rami-Habib Eid-Sabbagh rami.eidsabbagh@hpi.uni-potsdam.de

  9. ExampleRegistration of an enterprise Subprocesses Processes Actors Forms § B. Gewerbetreibende, die einer besonderen Genehmigung bedürfen (§§ 29 - 40) |    § 34cMakler, Anlageberater, Bauträger, Baubetreuer Laws Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  10. Context • Context eGovernment • Modernization efforts of administrations • Analysis of internal and external processes (G2B, G2C, G2G) • Public Administration’s operations based on laws and regulations • Operations based on form documents Problem: • Many interdependencies between process, data, and regulatory level • Change not always propagated • Inconsistencies • Compliance problems Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  11. Tasks Tasks • Literature review on framework/ontologies in regard to public service description, law, regulation and other input • Design framework/ontology • Evaluate ontology by designing different life situations • Design change propagation strategies Literature • eCh Projekt-Leitfaden • Adegboyega Ojo, Tomasz Janowski and Elsa Estevez, Domain Models and Enterprise Application Framework for Developing Electronic Public Services, UNU-IIST and UNU-IIST Reports 2007. • Konstantinos Tarabanis and Vassilios Peristeras, Requirements for Transparent Public Services Provision amongst Public Administrations, EGOV 2002. • Wissensbasiertes Prozessmanagement im E-Government, Klischweski und Wimmer, Hirschgraben 2005 • Yannis Charalabidis et al., The Greek Electronic Government Interoperability Framework: Standards and Infrastructures for One-Stop Service Provision. Panhellenic Conference on Informatics 2008 • Vassilios Peristeras and Konstantinos Tarabanis, Advancing the Government Enterprise Architecture – GEA: The Service Execution Object Model, EGOV 2004 • Eid-Sabbagh, R.-H., Dijkman, R.M., Weske, M.: Business Process Architecture: Use and Correctness. In: Barros, A.P., Gal, A., and Kindler, E. (eds.) BPM. pp. 65–81. Springer (2012). Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  12. Methods of Concept Drift Detection Andreas Rogge-Solti andreas.rogge-solti@hpi.uni-potsdam.de

  13. Monitoring & Predicting • We monitor executions of a business process • Prediction models can be used: • Model for prediction should be accurate! • But there is a problem of changes in the environment: a.k.a. “concept drift” Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  14. Types of Concept Drift • Source: J.C. Bose, W.M.P. van der Aalst, I. Zliobaite, M. Pechenizkiy. Handling Concept Drift in Process Mining. Lecture Notes in Computer Science, ProceedingsofCAiSE 2011, London, UK, 2011 Origin: Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  15. Methods of Concept Drift Detection • Your tasks in this seminar: • Use given literature (or further works)to categorize detection methods • Sketch an architecture to detect concept drift in a monitoring environment Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  16. Methods of Concept Drift Detection • Literature: • B. Depaire, J. Swinnen, M. Jans, K. Vanhoof. A Process Deviation Analysis Framework, BPM Workshops 2012, Workshop on Security in Business Processes, Tallinn, Estonia, 2012 • J.C. Bose, W.M.P. van der Aalst, I. Zliobaite, M. Pechenizkiy. Handling Concept Drift in Process Mining. Lecture Notes in Computer Science, ProceedingsofCAiSE 2011, London, UK, 2011 • IndréZliobaite. Learning underConcept Drift: an Overview. Technical report, FacultyofMathematicsandInformatics,Vilnius University, Lituania, 2009 Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  17. Vertical Workflow Run-time Optimization Luise Pufahl luise.pufahl@hpi.uni-potsdam.de

  18. Vertical Workflow Run-time Optimization Patient 5 Patient 4 Patient 3 Patient 2 Patient 1 Patient 1 Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  19. Vertical Workflow Run-time Optimization Patient 5 Patient 4 Patient 3 Patient 2 Patient 1 Patient 1 Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  20. Vertical Workflow Run-time Optimization • Tasks • Provide insight into multi-instance process tasks and their limitations • Consider the given literature to come up with a structured comparison of approaches for realizing batch services • Characteristics of the approaches • Strengths and weaknesses • Use the given use case for the evaluation • Optional: an own approach can be proposed (e.g. how to present batch services in the Business Process Modeling Notation) Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  21. Vertical Workflow Run-time Optimization • Literature • Sadiq, S., Orlowska, M., Sadiq, W., Schulz, K.: When workflows will not deliver: The case of contradicting work practice. In: Proc. BIS'05. (2005) • Liu, J. and Hu, J., Dynamic batchprocessing in workflows: Model and implementation, Future Generation Computer Systems Volume 23(3)(2007), 338–347. • Wen, Y.; Chen, Z.; Liu, J., Activity Instance Oriented Handling to Support Run-time Optimization of Process Cases, 2011 Seventh International Conference on Semantics, Knowledge and Grids. • Liu, J. and Wen, Y. and Li, T. and Zhang, X.:A data-operation model based on partial vector space for batch processing in workflow, Concurrency and Computation: Practice and Experience 23(16) (2011) 1936-195. • Mangler, J. and Rinderle-Ma, S., Rule-based synchronization of process activities, 2011 IEEE 13th Conference on Commerce and Enterprise Computing (CEC), 2011. • http://www.workflowpatterns.com/patterns/control/ Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  22. Process Architecture in Healthcare Nico Herzberg and Luise Pufahl luise.pufahl@hpi.uni-potsdam.de nico.herzberg@hpi.uni-potsdam.de

  23. Process Architecture in Healthcare Process Architecture in Healthcare Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  24. Process Architecture in Healthcare • Tasks • Consider given literature (or even further literature) to come up with an overview (picture) • Recommend at which level process model diagrams are useful • Clarify the term process architecture • Give based on the overview a first proposal for a general process architecture in the healthcare domain • Optional: medical experts of University Hospital of Jena could support in literature selection and verification of the developed process architecture Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  25. Process Architecture in Healthcare • Literature • U. Ronellenfitsch and M. Schwarzbach. KlinischesProzessmanagement - KlinischePfade in der Chirurgie: Evidenz und Potenzial. ZentralblattChirurgie, 135(2):99–101, 2010. • T. Rotter et al. Clinical pathways: effects on professional practice, patient outcomes, length of stay and hospital costs. Cochrane Database Syst Rev, Issue 3, 2010. • M. Uerlich, A. Dahmen, S. Tuschy, U. Ronellenfitsch, K. Eveslage, O. VargasHein?, G. Tuerk-Ihli, and M. Schwarzbach. KlinischePfade - Terminologie und Entwicklungsstufen. Periop.Med., 1(3):155–163, 2009. • M. Raetzell and M. Bauer. Standard operating procedures und klinischeBehandlungspfade. In OP-Management: praktisch und effizient, pages 187–198. Springer, 2006 • H. Köth, K. Miller, M. Lein, et al. Entwicklung und EffekteeinesstandortübergreifendenklinischenBehandlungspfades am Beispiel: "LaparoskopischeProstatektomie". Perioperative Medizin, 1(3):173–180, 2009. • R. Müller and A. Rogge-Solti. BPMN for healthcare processes. In 3rd Central-European Workshop on Services and their Composition (ZEUS), pp. 65–72, 2011 • R. Lenz and M. Reichert. IT support for healthcare processes – premises, challenges, perspectives. In Data & Knowledge Engineering, 61(1): 39-58, 2007. Literature Review on Techniques and Methods for Service Retrieval with respect to Process Data Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  26. A Repository for Event Descriptions Nico Herzberg nico.herzberg@hpi.uni-potsdam.de

  27. A Repository for Event Descriptions • N. Herzberg. Towards a High-quality Event Base – • A Research Agenda (unpublished yet) Knowledge-intensive Business Processes | BPT Group | 22th October 2012

  28. A Repository for Event Descriptions • Tasks • Proposal for an event repository • Information about business event definition in one place • Name • Description • Extraction rules for event information • Utilization of external and runtime knowledge • etc. • Validation of SOA approach for that problem • How could repositories entries be managed and found? • Link to BPT bachelor project 2012/2013 • Optional: investigation whether approach applicable for normalized events also Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  29. A Repository for Event Descriptions • Literature • N. Herzberg, M. Kunze, A. Rogge-Solti. Towards process evaluation in non-automated process execution environments. 4th Central-European Workshop on Services and their Composition (ZEUS), 2012 • Oasis. Reference Model for Service Oriented Architecture. Public Review Draft 2. Oasis Standard, 2006 • N. Herzberg. Towards a High-quality Event Base - A Research Agenda (unpublished yet) Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  30. AdvancedQueryingwithBehavioral Relations Matthias Kunze matthias.kunze@hpi.uni-potsdam.de

  31. Business Process Model Querying • process models capture the operations carried out to create business value • documentation and analysis • automation, certification • modern companies maintain thousands of process models, e.g., for reference and reuse • requires effective search capabilities Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  32. Querying by Behavior Inclusion query model repository • Which of the process models stored in the repository can replay the behavior of a given query? ✔ ✗ Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  33. Efficient Comparison of Behavior Precedence –Local BehaviorA > B ⇔B is executed directly after A Weak Order – Global BehaviorA ≻ B ⇔B is executed some time after A Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  34. Business Process Model Querying • initial empirical studies show • works well on simple examples • humans are challenged by complex queries, e.g., gateways • somequeriesreturnresultsthathumans do not expect! Hereyoustart! Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  35. Your Task Survey expected results of queries and adapt querying semantics to match expectations closer. • readrelatedliteratureto understand thefundamentalsofbehavioralquerying • comprehendanddiscussqueryinglimitationsandpeculiaritiesoftheapproach • prepare a userstudyto find out, whatusersexpectfrom potential queries Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  36. User Study Considerations • considerreal worldprocessesfromexistingprocesscollections • design specificqueriesthataddresstheparticularitiesofthequeryingapproach • prepare potential matchestothequerythatshallbeevaluatedbyhumans query ☑ ☑ ☒ ☒ ☑ Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  37. Literature • R. M. Dijkman, M. L. Rosa, and H. A. Reijers. Managing large collections of business process models - current techniques and challenges. Computers in Industry, 63(2):91–97, 2012. • M. Weidlich, J. Mendling, and M. Weske. Efficient consistency measurement based on behavioral profiles of process models. IEEE Trans. Softw. Eng., 37(3):410–429, May 2011. • M. Kunze and M. Weske. Local behavior similarity. In BPMDS 2012 and EMMSAD 2012, volume 113 of LNBIP, pages 107–120. Springer, 2012. • M. Kunze, M. Weidlich, M. Weske. Querying Process Models by Example. (submitted) • F. Pittke, H. Leopold, J. Mendling, G. Tamm. Enabling Reuse of Process Models trough the Detection of Similar Process Parts. In rBPM workshop 2012. Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  38. Literature Review on Techniques and Methods for Service Retrieval with respect to Process Data Oleh Khovalko oleh.khovalko@hpi.uni-potsdam.de

  39. Context ProceedOrderService ValidateOrderService StockControlService ? ? ? CheckOrderService VerifyOrderPositions Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  40. Context • An important issue arising from execution of business processes is how to conveniently, accurately and efficiently retrieve services from large-scale and expanding service repositories. • However, it has been observed that service providers typically release poor service descriptions. Several approaches have been proposed to tackle this problem by enriching poor service descriptions with additional information from other sources. Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  41. Task • Literature review on techniques and methods for service discovery and selection with respect to process data • Compare current theoretical approaches and practical solutions as well as future trends in this research area • What is possible and what is not? • Where are the limits of current methods? • propose further steps on improving those techniques Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  42. References • Fensel D., Keller U., Lausen H., Polleres A., Toma I. WWW Or What Is Wrong With Web Service Discovery - Position Paper for the Workshop on Frameworks for Semantics in Web Services, Innsbruck, Austria, June 2005 • AbuJarour M., Naumann F. Dynamic tags for dynamic data web services; Proceeding WEWST '10 Proceedings of the 5th International Workshop on Enhanced Web Service Technologies, Pages 3-9 • AbuJarour M., Ahmed A. Enriched Service Descriptions Using Business Process Configurations; Proceedings of the 4th International Workshop on Enterprise Modelling and Information Systems Architectures, EMISA 2011, Hamburg, Germany, September 22-23, 2011 • AbuJarour M., Oerge S. Automatic Sampling of Web Services; Conference Publications ICWS2011, 4-9 July 2011; Page(s): 291 – 298 • Yiqiao W. Flexible Interface Matching for Web-Service Discovery. WISE 2003. Proceedings of the Fourth International Conference, Page(s): 147 - 156 Alberta Univ., Edmonton, Alta., Canada • Klein M., Bernstein A. Towards High-Precision Service Retrieval, Journal IEEE Internet Computing archive Volume 8 Issue 1, January 2004 Page 30-36 • Blanzieri E., D'Andrea V., Giorgini P., Kokash N. Improving Web Service Discovery with Usage Data; IEEE Software, Nov.-Dec. 2007 Volume: 24 , Issue: 6, Page(s): 47 - 54 • Vitvar T., Moran M. Towards Optimized Data Fetching for Service Discovery. ECOWS '07 26-28 Nov. 2007 Page(s): 191 - 200 Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  43. Data Object Abstraction as Standalone Technique Andreas Meyer andreas.meyer@hpi.uni-potsdam.de

  44. Motivation Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  45. Task Product • Framework for data object abstraction • Without affecting control flow • Considering data object states and its life cycles • Allowing aggregation and generalization of data objects • Qualitative evaluation of your proposal ??Purchase Order?? Order Invoice Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  46. Literature • A. Meyer and M. Weske: Data Support in Process Model Abstraction • A. Polyvyanyy, S. Smirnov, M. Weske: Process Model Abstraction: A Slider Approach • S. Smirnov, H. Reijers, and M. Weske: A Semantic Approach for Business Process Model Abstraction • R. Eshuis, P. Grefen: Constructing Customized Process Views • G. Berthelot: Transformations and Decompositions of Nets Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  47. Next Steps Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

  48. Questions Knowledge-intensive Business Processes | BPT Group | 22nd October 2012

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