Skip to main content

Towards Extending Business Process Modeling Formalisms with Information and Knowledge Dimensions

  • Conference paper
  • First Online:
Book cover Advances in Artificial Intelligence: From Theory to Practice (IEA/AIE 2017)

Abstract

Sensitive Business Processes (SBPs) modeling has become an effective way of managing and developing organization’s knowledge which needs to be capitalized. These processes are characterized by a high complexity and dynamism in their execution, high number of critical activities with intensive acquisition, sharing, storage and (re)use of very specific crucial knowledge, diversity of knowledge sources, and high degree of collaboration among experts. Hence, we propose a semantically rich conceptualization for describing an SBP organized in a generic Business Process Meta-model for Knowledge Identification (BPM4KI), in order to develop a rich and expressive representation of SBPs to identify and localize the crucial knowledge. BPM4KI covers all aspects of business process modeling: the functional, organizational, behavioral, informational, intentional and knowledge perspectives. This paper aims to introduce a more explicit border between information and knowledge concepts and dimensions which are relevant in SBP models, based on «core» domain ontologies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://home.mis.u-picardie.fr/~site-ic/site/spip.php?article53.

  2. 2.

    With respect to our notation, the informal labels on BPM4KI concepts appear in the text in the Courrier new font with First Capital Letters for the concepts and a javaLikeNotation for relations.

  3. 3.

    According to I&DA [33], Knowledge - for an Agent - corresponds to Propositions to which the Agent confers a truth value: this then allows him/her to use these Propositions in reasoning (whatever their truth value) in order to derive new knowledge.

    .

  4. 4.

    https://www.dropbox.com/s/0ia9xrjwrtoqqkq/Ontological%20Conceptual%20Pattern%20relating%20to%20the%20Knowledge%20Perspective%20of%20SBP.pdf?dl=0. The figure explicit the core concepts of the knowledge perspective of BPM4KI meta-model (marked in gray), in addition to inter-aspects relationships [4].

References

  1. Saad, I., Grundstein, M., Sabroux, C.: Une méthode d’aide à l’identification des connaissances cruciales pour l’entreprise. Revue SIM 14(3), 43–78 (2009)

    Google Scholar 

  2. Turki, M., Saad, I., Gargouri, F., Kassel, G.: A business process evaluation methodology for knowledge management based on multi-criteria decision making approach. In: Information Systems for Knowledge Management. Wiley-ISTE (2014). ISBN: 978-1-84821-664-8

    Google Scholar 

  3. Ben Hassen, M., Turki, M., Gargouri, F.: A business process meta-model for knowledge identification based on a core ontology. In: Shishkov, B. (ed.) BMSD 2015. LNBIP, vol. 257, pp. 37–61. Springer, Cham (2016). doi:10.1007/978-3-319-40512-4_3

    Google Scholar 

  4. Ben Hassen, M., Turki, M., Gargouri, F.: A proposal to model knowledge dimension in sensitive business processes. In: Madureira, A.M., Abraham, A., Gamboa, D., Novais, P. (eds.) ISDA 2016. AISC, vol. 557, pp. 1015–1030. Springer, Cham (2017). doi:10.1007/978-3-319-53480-0_100

    Chapter  Google Scholar 

  5. Gangemi, A.: Ontology Design Patterns: A primer, with applications and perspectives. Tutorial on ODP, Laboratory for Applied Ontology Institute of Cognitive Sciences and Technology CNR, Rome, Italy (2006)

    Google Scholar 

  6. Masolo, C., Vieu, L., Bottazzi, E., Catenacci, C., Ferrario, R., Gangemi, A., Guarino, N.: Social roles and their descriptions. In: Dubois, D., Welty, C., Williams, M.-A. (eds.) Proceedings of the Ninth International Conference on the Principles of Knowledge Representation and Reasoning, pp. 267–277 (2004)

    Google Scholar 

  7. Ben Hassen, M., Turki, M., Gargouri, F.: Choosing a sensitive business process modeling formalism for knowledge identification. Procedia Comput. Sci. 100, 1002–1015 (2016)

    Article  Google Scholar 

  8. Gronau, N., Korf, R., Müller, C.: KMDL-capturing, analysing and improving knowledge-intensive business processes. J. Univ. Comput. Sci. 11(4), 452–472 (2005)

    Google Scholar 

  9. Schlenoff, C., Gruninger, M., Tissot, F., Valois, J.: The process specification language (PSL) overview and version 1.0 specification (2000). http://www.mel.nist.gov/psl/

  10. Weidong, Z., Weihui, D.: Integrated modeling of business processes and knowledge flow based on RAD. In: IEEE International Symposium on Knowledge Acquisition and Modeling, Wuhan, China, pp. 49–53 (2008)

    Google Scholar 

  11. Zhaoli, Z., Zongkai, Y., Qingtang, L.: Modeling knowledge flow using petri net. In: International Symposium on Knowledge Acquisition and Modeling, Wuhan, China, pp. 142–146 (2008)

    Google Scholar 

  12. ARIS Expert Paper: Business Process Design as the Basis for Compliance Management, Enterprise Architecture and Business Rules (2007)

    Google Scholar 

  13. Unified Modeling Language (UML). Version 2.0. OMG (2011). http://www.uml.org/

  14. Business Process Modeling and Notation (BPMN). Version 2.0. OMG (2011). http://www.bpmn.org/

  15. Abecker, A.: DECOR Consortium: DECOR-Delivery of Context-Sensitive Organizational Knowledge. E-Work and E-Commerce. IOS Press, Amsterdam (2008)

    Google Scholar 

  16. Heisig, P.: The GPO-WM® method for the integration of knowledge management into business processes. In: International Conference on Knowledge Management, Graz, Austria, pp. 331–337 (2006)

    Google Scholar 

  17. Hildebrandt, T.T., Mukkamala, R.R.: Declarative event-based workflow as distributed dynamic condition response graphs. In: Programming Languages Approaches to Concurrency and Communication-cEntric Software, Cyprus, pp. 59–73 (2010)

    Google Scholar 

  18. Woitsch, R., Karagiannis, D.: Process oriented knowledge management: a service based approach. J. Univ. Comput. Sci. 11(4), 565–588 (2005)

    Google Scholar 

  19. Oliveira, F.F.: Ontology Collaboration and its Applications. MSc Dissertation. Programa de Pós-Graduação em Informática, Universidade Federal do Espírito Santo, Vitória, Brazil (2009)

    Google Scholar 

  20. Arbeitsbericht.: KMDL® v2.2 (2009). http://www.kmdl.de/

  21. Netto, J.M, Franca, J.B.S., Baião, F.A., Santoro, F.M.: A notation for knowledge-intensive processes. In: IEEE 17th International Conference on Computer Supported Cooperative Work in Design, vol. 1, pp. 1–6 (2013)

    Google Scholar 

  22. Kassel, G.: Integration of the DOLCE top-level ontology into the OntoSpec methodology (2005)

    Google Scholar 

  23. Kassel, G., Turki, M., Saad, I., Gargouri, F.: From collective actions to actions of organizations: an ontological analysis. In: Symposium Understanding and Modelling Collective Phenomena (UMoCop). University of Birmingham, Birmingham, England (2012)

    Google Scholar 

  24. Turki, M., Kassel, G., Saad, I., Gargouri, F.: A core ontology of business processes based on DOLCE. J. Data Semant. 5(3), 165–177 (2016)

    Article  Google Scholar 

  25. Yankovsky, S.Ya.: Les concepts de la théorie de l’information générale (2001). http://n-t.ru/tp/ng/oti.htm

  26. Gray, P.: Knowledge management Overview. Center for Research on Information Technology and Organizations, University of California (2000)

    Google Scholar 

  27. Gibaut, B., Kassel, G.: Sémantique des données de l’observation: une approche ontologique. Technical report, Boston, MA, USA (2013)

    Google Scholar 

  28. Fitchett, J.: Managing your organization’s key asset: knowledge. Health Forum J. 9(41), 50–60 (1998)

    Google Scholar 

  29. Ferrary, M., Pesqueux, Y.: Management de la connaissance: knowledge management, apprentissage organisationnel et société de la connaissance, Economica Edition. Eyrolles (2006)

    Google Scholar 

  30. CIFREG. Gérer les connaissances. Défi, enjeu et conduite de projet. (Report No. ATTJ8KE4, p. 15). CIGREF, Club Informatique des GRandes Entreprises Françaises, Paris (2000)

    Google Scholar 

  31. Davenport, T., Long, D.D., Beers, M.: Successful knowledge management projects. Sloan Manag. Rev. 39(2), 43–57 (1998)

    Google Scholar 

  32. Nonaka, I., Takeuchi, H.: Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, New York (1995)

    Google Scholar 

  33. Fortier, J.-Y., Kassel, G.: Managing knowledge at the information level: an ontological approach. In: Proceedings of the ECAI 2004 Workshop on Knowledge Management and Organizational Memories, Valencia, Spain, pp. 39–45 (2004)

    Google Scholar 

  34. Floridi, L.: Semantic conceptions of information. The Stanford Encyclopedia of Philosophy (2013)

    Google Scholar 

  35. Kassel, G.: A formal ontology of artefacts. Appl. Ontology 5(3–4), 223–246 (2010)

    Google Scholar 

  36. Sultanow, E., Zhou, X., Gronau, N.: Modeling of processes, systems and knowledge: a multi-dimensional comparison of 13 chosen methods. Int. Rev. Comput. Softw. 7(6), 3309–3319 (2012)

    Google Scholar 

  37. Liu, D.R., Lai, D.R., Liu, C.H., Chih-Wei, L.: Modeling the knowledge-flow view for collaborative knowledge support. J. Know. Based Syst. 31, 41–54 (2012)

    Article  Google Scholar 

  38. Ammann, E.: Modeling of knowledge-intensive business processes. Int. J. Soc. Behav. Educ. Bus. Ind. Eng. 6(11), 3144–3150 (2012)

    Google Scholar 

  39. Schwitzgebel, E.: Belief. In: Zalta, E.N. (ed.) The Stanford Encyclopedia of Philosophy (2014). http://plato.stanford.edu/archives/spr2014/entries/belief/

  40. Bonnet, C., Ghiglione, R., Richard, J.-F.: Traité de Psychologie Cognitive, Tome 1: Perception, action, langage. Dunod, vol. 3, Paris, 280 p. (2003). ISBN: 2100078445

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mariam Ben Hassen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Ben Hassen, M., Turki, M., Gargouri, F. (2017). Towards Extending Business Process Modeling Formalisms with Information and Knowledge Dimensions. In: Benferhat, S., Tabia, K., Ali, M. (eds) Advances in Artificial Intelligence: From Theory to Practice. IEA/AIE 2017. Lecture Notes in Computer Science(), vol 10350. Springer, Cham. https://doi.org/10.1007/978-3-319-60042-0_45

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-60042-0_45

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60041-3

  • Online ISBN: 978-3-319-60042-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics