Knowledge Engineering for Business Process Modeling

Sonya Ouali, Mohamed Mhiri, Faiez Gargouri

2017

Abstract

The process is the pivot of the business modeling. Thus, the goal of modeling is to present the main flows exchanged with the internal and external environment. Indeed, there are several pieces of information that take place throughout the process life cycle, from design to execution. Behind these pieces of information, there is a lot of business knowledge that should be acquired to improve the quality of such a modeling. The aim of this paper is to manipulate the business knowledge when developing modeling perspectives. For this reason, our solution consists in proposing an ontological approach to create a Multidimensional Business Knowledge base (MBK BASE) to help the designers of the business process with their tasks. In this way, on the one hand, we outline an overview of our proposed solution by relating it to other research. In fact, we define the main business concepts and we describe some semantic relationships which are expressed with the descriptive logic. On the other hand, we give an illustrative case study related to the treatment choice process of a patient with breast cancer in order to demonstrate the applicability of our solution.

References

  1. Andersson, B., Bergholtz, M., Edirisuriya, A., Ilayperuma, T., Johannesson, P., Gordijn, J., Grégoire, B., Schmitt, M., Dubois, E., Abels, S., et al. (2006). Towards a reference ontology for business models. In International Conference on Conceptual Modeling, pages 482-496. Springer.
  2. Antoniou, G., Franconi, E., and Van Harmelen, F. (2005). Introduction to semantic web ontology languages. In Reasoning web, pages 1-21. Springer.
  3. Baader, F., Horrocks, I., and Sattler, U. (2009). Description logics. In Handbook on ontologies, pages 21-43. Springer.
  4. Becker, J., Pfeiffer, D., Falk, T., and Räckers, M. (2010). Semantic business process management. In Handbook on Business Process Management 1, pages 187-211. Springer.
  5. Born, M., Dörr, F., and Weber, I. (2007). User-friendly semantic annotation in business process modeling. In International Conference on Web Information Systems Engineering, pages 260-271. Springer.
  6. Cherfi, S. S.-S., Ayad, S., and Comyn-Wattiau, I. (2013). Aligning business process models and domain knowledge: a meta-modeling approach. In Advances in Databases and Information Systems, pages 45-56. Springer.
  7. Coalition, W. M. (1996). Terminology & glossary. WFMC Document WFMCTC-1011, Workflow Management Coalition, Avenue Marcel Thiry, 204:1200.
  8. Daconta, M. C., Obrst, L. J., and Smith, K. T. (2003). The semantic web: a guide to the future of XML, web services, and knowledge management. John Wiley & Sons.
  9. Delfmann, P., Herwig, S., Lis, L., and Becker, J. (2011). Supporting conceptual model analysis using semantic standardization and structural pattern matching. Semantic Technologies for Business and Information Systems Engineering: Concepts and Applications (Smolnik, S., Teuteberg, F., Thomas, O. Eds.), page 125.
  10. Di Francescomarino, C. (2011). Semantic annotation of business process models. PhD thesis, University of Trento.
  11. Dumas, M., La Rosa, M., Mendling, J., Reijers, H. A., et al. (2013). Fundamentals of business process management, volume 1. Springer.
  12. Evans, M., Dalkir, K., and Bidian, C. (2015). A holistic view of the knowledge life cycle: the knowledge management cycle (kmc) model. Leading Issues in Knowledge Management, Volume Two, 2:47.
  13. Fellmann, M. (2013). Semantic process engineeringkonzeption und realisierung eines werkzeugs zur semantischen prozessmodellierung.
  14. Gábor, A. and Szabó, Z. (2013). Semantic technologies in business process management. In Integration of practice-oriented knowledge technology: trends and prospectives, pages 17-28. Springer.
  15. Gernert, C. and Köppen, V. (2006). Handbuch-it in der verwaltung, chapter geschäftsprozesse optimal gestalten.
  16. Gruber, T. R. et al. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2):199-220.
  17. Hammer, M. and Champy, J. (1993). Reengineering the corporations.
  18. Harrington, H. J. (1991). Business process improvement: The breakthrough strategy for total quality, productivity, and competitiveness. McGraw Hill Professional.
  19. Hoang, H. H., Jung, J. J., and Tran, C. P. (2014). Ontologybased approaches for cross-enterprise collaboration: A literature review on semantic business process management. Enterprise Information Systems, 8(6):648- 664.
  20. Indulska, M., Recker, J., Rosemann, M., and Green, P. (2009). Business process modeling: Current issues and future challenges. In International Conference on Advanced Information Systems Engineering, pages 501-514. Springer.
  21. Jablonski, S. and Bussler, C. (1996). Workflow management: modeling concepts, architecture and implementation.
  22. Koschmider, A., Hornung, T., and Oberweis, A. (2011). Recommendation-based editor for business process modeling. Data & Knowledge Engineering, 70(6):483-503.
  23. La Rosa, M., Dumas, M., Uba, R., and Dijkman, R. (2013). Business process model merging: An approach to business process consolidation. ACM Transactions on Software Engineering and Methodology (TOSEM), 22(2):11.
  24. Lin, Y. and Krogstie, J. (2010). Semantic annotation of process models for facilitating process knowledge management. International Journal of Information System Modeling and Design (IJISMD), 1(3):45-67.
  25. Lodhi, A., Köppen, V., and Saake, G. (2011). Business process modeling: Active research areas and challenges. Tec. Rep: FIN-001.
  26. Markovic, I. (2010). Semantic business process modeling. KIT Scientific Publishing.
  27. Missikoff, M., Proietti, M., and Smith, F. (2011). Querying semantically enriched business processes. In International Conference on Database and Expert Systems Applications, pages 294-302. Springer.
  28. Model, B. P. (2011). Notation (bpmn) version 2.0. OMG Specification, Object Management Group.
  29. Nonaka, I. and Takeuchi, H. (1995). The KnowledgeCreating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press.
  30. Omrane, N., Nazarenko, A., Rosina, P., Szulman, S., and Westphal, C. (2011). Lexicalized ontology for a business rules management platform: An automotive use case. In Rule-Based Modeling and Computing on the Semantic Web, pages 179-192. Springer.
  31. Ouali, S., Mhiri, M., and Bouzguenda, L. (2016). A multidimensional knowledge model for business process modeling. Procedia Computer Science, 96:654-663.
  32. Recker, J., Rosemann, M., Indulska, M., and Green, P. (2009). Business process modeling-a comparative analysis. Journal of the Association for Information Systems, 10(4):1.
  33. Rosemann, M. and vom Brocke, J. (2015). The six core elements of business process management. In Handbook on Business Process Management 1, pages 105-122. Springer.
  34. Sheth, A. P. and Ramakrishnan, C. (2003). Semantic (web) technology in action: Ontology driven information systems for search, integration, and analysis. IEEE Data Engineering Bulletin, 26(4):40.
  35. Sveiby, K. E. (1997). The new organizational wealth: Managing & measuring knowledge-based assets. BerrettKoehler Publishers.
  36. Tétreault, M. (2012). Modélisation d'une ontologie et conceptualisation d'une application sémantique dédiée au e-recrutement dans le domaine des technologies de l'information.
  37. Van den Berg, H. A. (2013). Three shapes of organisational knowledge. Journal of Knowledge Management, 17(2):159-174.
  38. van der Aalst, W. M. (2013). Business process management: a comprehensive survey. ISRN Software Engineering, 2013.
  39. Wache, H., Voegele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H., and Hübner, S. (2001). Ontology-based integration of information-a survey of existing approaches. In IJCAI-01 workshop: ontologies and information sharing, volume 2001, pages 108-117. Citeseer.
  40. Wagner, W. P., Otto, J., and Chung, Q. (2002). Knowledge acquisition for expert systems in accounting and financial problem domains. Knowledge-Based Systems, 15(8):439-447.
  41. Wang, X., Li, N., Cai, H., and Xu, B. (2010). An ontological approach for semantic annotation of supply chain process models. In OTM Confederated International Conferences” On the Move to Meaningful Internet Systems” , pages 540-554. Springer.
  42. Weissgerber, A. (2011). Semantically-enriched business process modeling and management.
  43. Weske, M. (2007). Business process management architectures. Business Process Management: Concepts, Languages, Architectures, pages 305-343.
  44. Yessad, A. and Labat, J.-M. (2011). Approche ontologique pour la détection de la pertinence d'une action dans un jeu sérieux. In IC 2011, 22èmes Journées francophones d'Ingénierie des Connaissances, pages 557- 572.
Download


Paper Citation


in Harvard Style

Ouali S., Mhiri M. and Gargouri F. (2017). Knowledge Engineering for Business Process Modeling . In Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-250-9, pages 81-90. DOI: 10.5220/0006323200810090


in Bibtex Style

@conference{enase17,
author={Sonya Ouali and Mohamed Mhiri and Faiez Gargouri},
title={Knowledge Engineering for Business Process Modeling},
booktitle={Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2017},
pages={81-90},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006323200810090},
isbn={978-989-758-250-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Knowledge Engineering for Business Process Modeling
SN - 978-989-758-250-9
AU - Ouali S.
AU - Mhiri M.
AU - Gargouri F.
PY - 2017
SP - 81
EP - 90
DO - 10.5220/0006323200810090