Abstract
So far, business process monitoring approaches have mainly focused on monitoring executions with respect to a single process model. This setting aptly captures monolithic scenarios from domains in which all possible behaviors can be folded into a single model. However, this strategy cannot be applied to domains where multiple interacting (procedural) sub-processes work under additional (declarative) constraints. For example, in healthcare, co-morbid patients may be subject to multiple clinical pathways at once, in the presence of additional, general constraints capturing basic medical knowledge. To support monitoring of thus emerging hybrid specifications, we propose a Multi-Model Monitoring Framework. On the one hand, the framework allows for a hybrid representation of a process, using both procedural and declarative models. This admits more flexible process model design as domain experts can focus on specific procedures and domain constraints without needing to merge them into one single specification. On the other hand, the framework includes an automata-based monitoring technique to simultaneously account for multiple models within one execution while resolving conflicts caused by the interplay of such models. We describe the overall framework, report on a prototypical implementation of the monitoring technique, and demonstrate its feasibility with a healthcare scenario.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Classifiers available at: https://www.who.int/standards/classifications.
- 2.
For example: https://reference.medscape.com/drug-interactionchecker.
References
Alman, A., Maggi, F.M., Montali, M., Patrizi, F., Rivkin, A.: Monitoring hybrid process specifications with conflict management: The automata-theoretic approach. Technical report, arXiv.org (2021)
Andaloussi, A.A., Burattin, A., Slaats, T., Kindler, E., Weber, B.: On the declarative paradigm in hybrid business process representations: a conceptual framework and a systematic literature study. Inf. Syst. 91, 101505 (2020)
Bergami, G., Maggi, F.M., Marrella, A., Montali, M.: Aligning data-aware declarative process models and event logs. In: BPM, pp. 235–251 (2021)
Bottrighi, A., Chesani, F., Mello, P., Montali, M., Montani, S., Terenziani, P.: Conformance checking of executed clinical guidelines in presence of basic medical knowledge. In: BPM Workshops, pp. 200–211 (2011)
Burattin, A., Maggi, F.M., Sperduti, A.: Conformance checking based on multi-perspective declarative process models. Expert Syst. Appl. 65, 194–211 (2016)
De Masellis, R., Maggi, F.M., Montali, M.: Monitoring data-aware business constraints with finite state automata. In: ICSSP, pp. 134–143. ACM (2014)
De Smedt, J., De Weerdt, J., Vanthienen, J.: Fusion miner: process discovery for mixed-paradigm models. Decis. Support Syst. 77, 123–136 (2015)
van Dongen, B.F., De Smedt, J., Di Ciccio, C., Mendling, J.: Conformance checking of mixed-paradigm process models. Inf. Syst. 102, 101685 (2021)
Hopcroft, J.E., Motwani, R., Ullman, J.D.: Introduction to automata theory, languages, and computation, 3rd Edition. Addison-Wesley (2007)
Jalali, A., Maggi, F.M., Reijers, H.A.: A hybrid approach for aspect-oriented business process modeling. J. Softw. Evol. Process. 30(8), e1931 (2018)
de Leoni, M., Felli, P., Montali, M.: A holistic approach for soundness verification of decision-aware process models. In: Trujillo, J.C., et al. (eds.) ER 2018. LNCS, vol. 11157, pp. 219–235. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00847-5_17
Ly, L.T., Maggi, F.M., Montali, M., Rinderle-Ma, S., van der Aalst, W.M.P.: Compliance monitoring in business processes: functionalities, application, and tool-support. Inf. Syst. 54, 209–234 (2015)
Maggi, F.M., Montali, M., Bhat, U.: Compliance monitoring of multi-perspective declarative process models. In: EDOC, pp. 151–160. IEEE (2019)
Maggi, F.M., Montali, M., Westergaard, M., van der Aalst, W.M.P.: Monitoring business constraints with linear temporal logic: an approach based on colored automata. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) BPM 2011. LNCS, vol. 6896, pp. 132–147. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23059-2_13
Maggi, F.M., Slaats, T., Reijers, H.A.: The automated discovery of hybrid processes. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 392–399. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-10172-9_27
Mannhardt, F., de Leoni, M., Reijers, H.A., van der Aalst, W.M.P.: Balanced multi-perspective checking of process conformance. Computing 98(4), 407–437 (2015). https://doi.org/10.1007/s00607-015-0441-1
Montali, M., Pesic, M., van der Aalst, W.M.P., Chesani, F., Mello, P., Storari, S.: Declarative specification and verification of service choreographiess. ACM Trans. Web 4(1), 3:1–3:62 (2010)
Pla, A., Gay, P., Meléndez, J., López, B.: Petri net-based process monitoring: a workflow management system for process modelling and monitoring. J. Intell. Manuf. 25(3), 539–554 (2012). https://doi.org/10.1007/s10845-012-0704-z
Prock, J.: A new technique for fault detection using petri nets. Automatica 27(2), 239–245 (1991)
Sadiq, S.W., Orlowska, M.E., Sadiq, W.: Specification and validation of process constraints for flexible workflows. Inf. Syst. 30(5), 349–378 (2005)
Slaats, T.: Declarative and hybrid process discovery: recent advances and open challenges. J. Data Semant. 9(1), 3–20 (2020)
Spiotta, M., Terenziani, P., Theseider Dupré, D.: Temporal conformance analysis and explanation of clinical guidelines execution: an answer set programming approach. IEEE Trans. Knowl. Data Eng. 29(11), 2567–2580 (2017)
Acknowledgements
The work of A. Alman was supported by the European Social Fund via “ICT programme” measure and by the Estonian Research Council grant PRG1226. F.M. Maggi was supported by the UNIBZ project CAT.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Alman, A., Maggi, F.M., Montali, M., Patrizi, F., Rivkin, A. (2022). Multi-model Monitoring Framework for Hybrid Process Specifications. In: Franch, X., Poels, G., Gailly, F., Snoeck, M. (eds) Advanced Information Systems Engineering. CAiSE 2022. Lecture Notes in Computer Science, vol 13295. Springer, Cham. https://doi.org/10.1007/978-3-031-07472-1_19
Download citation
DOI: https://doi.org/10.1007/978-3-031-07472-1_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-07471-4
Online ISBN: 978-3-031-07472-1
eBook Packages: Computer ScienceComputer Science (R0)