A DMN-Based Method for Context-Aware Business Process Modeling Towards Process Variability
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Business process modeling traditionally has not paid much attention to the interactive features considering the dynamism of the environment in which a business process is embedded. As context-awareness is accommodated in business process modeling, decisions are still considered within business processes in a traditional way. Moreover, context-aware business process modeling excessively relies on expert knowledge, due to a lack of a methodological way to guide its whole procedure. Lately, BPM (Business Process Management) is moving towards the separation of concerns paradigm by externalizing the decisions from the process flow. Most notably, the introduction of DMN (Decision Model and Notation) standard provides a solution and technique to model decisions and the process separately but consistently integrated. The DMN technique supports the ability to extract and operationalize value from data analytics since the value of data analytics lies in improving decision-making. In this paper, a DMN-based method is proposed for the separate consideration of decisions and business processes, which allows to model context into decisions as context-aware business process models for achieving business process variability. Using this method, the role of analytics in improving some part of the decision making can also be integrated in the context-aware business process modeling, which increases the potential for using big data and analytics to improve decision-making. Moreover, a formal presentation of DMN is extended with the context concept to set the theoretical foundation for the proposed DMN-based method.
KeywordsDecision modeling Context-aware business process Process modeling Process variability
This research is supported by the Natural Science Foundation of China under Grant 71502010.
- 4.Hallerbach, A., Bauer, T., Reichert, M.: Context-based configuration of process variants. In: 3rd International Workshop on Technologies for Context-Aware Business Process Management (TCoB 2008) Barcelona, Spain (2008)Google Scholar
- 6.Bucchiarone, A., Marconi, A., Pistore, M., Raik, H.: Dynamic adaptation of fragment-based and context-aware business processes. In: 2012 IEEE 19th International Conference on Web Services (ICWS), pp. 33–41. IEEE (2012)Google Scholar
- 7.OMG: Decision Model and Notation 1.2. (2018)Google Scholar
- 8.Recker, J., Flender, C., Ansell, P.: Understanding context-awareness in business process design. In: ACIS 2006 Proceedings, p. 79 (2006)Google Scholar
- 9.Bernal, J.F.M., Falcarin, P., Morisio, M., Dai, J.: Dynamic context-aware business process: a rule-based approach supported by pattern identification. In: Proceedings of the 2010 ACM Symposium on Applied Computing, Sierre, Switzerland, pp. 470–474. ACM (2010)Google Scholar
- 10.de la Vara, J.L., Ali, R., Dalpiaz, F., Sánchez, J., Giorgini, P.: COMPRO: a methodological approach for business process contextualisation. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2010. LNCS, vol. 6426, pp. 132–149. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16934-2_12CrossRefGoogle Scholar
- 13.Nunes, V.T., Werner, C.M.L., Santoro, F.M.: Dynamic process adaptation: a context-aware approach. In: 2011 15th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 97–104. IEEE (2011)Google Scholar
- 14.Rosemann, M., Recker, J.C.: Context-aware process design: exploring the extrinsic drivers for process flexibility. In: The 18th International Conference on Advanced Information Systems Engineering. Proceedings of Workshops and Doctoral Consortium, pp. 149–158. Namur University Press (2006)Google Scholar
- 18.Taylor, J., Fish, A., Vanthienen, J., Vincent, P.: Emerging standards in decision modeling. An introduction to decision model notation, pp. 133–146 (2013)Google Scholar
- 19.De Smedt, J., Hasić, F., vanden Broucke, S.K.L.M., Vanthienen, J.: Towards a holistic discovery of decisions in process-aware information systems. In: Carmona, J., Engels, G., Kumar, A. (eds.) BPM 2017. LNCS, vol. 10445, pp. 183–199. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65000-5_11CrossRefGoogle Scholar