Abstract
Business process monitoring aims at identifying how well running processes are performing with respect to performance measures and objectives. By observing the execution of a process, process monitoring is also responsible for creating process traces, which can be subsequently used by process mining algorithms to gain further insights on the process.
Among the various monitoring solutions, artifact-driven monitoring has been proposed as a viable solution to continuously and autonomously monitor business processes. By monitoring the changes in the physical and virtual objects (i.e., artifacts) participating in the process, artifact-driven monitoring can autonomously generate traces that include events related to semi-automatic and manual tasks. Also, by relying on a declarative representation of the process to monitor, artifact-driven monitoring can detecting violations in the execution flow as soon as they occur. In addition, artifact-driven monitoring can identify the process elements affected by a violation, and it can continue monitoring the process without human intervention.
This tutorial paper will firstly provide an introduction to process monitoring, and the recent advancements in this field. Then, an overview on how artifact-driven monitoring works will be provided.
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Damaggio, E., Hull, R., Vaculín, R.: On the equivalence of incremental and fixpoint semantics for business artifacts with guard-stage-milestone lifecycles. Inf. Syst. 38(4), 561–584 (2013)
Dumas, M., La Rosa, M., Mendling, J., Reijers, A.: Fundamentals of Business Process Management (2013)
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)
Meroni, G.: Assessing and improving process monitorability. In: Artifact-Driven Business Process Monitoring. LNBIP, vol. 368, pp. 93–106. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-32412-4
Meroni, G., Baresi, L., Montali, M., Plebani, P.: Multi-party business process compliance monitoring through iot-enabled artifacts. Inf. Syst. 73, 61–78 (2018)
Reichert, M., Weber, B.: Enabling Flexibility in Process-Aware Information Systems - Challenges, Methods, Technologies. Springer (2012)
van der Aalst, W.M.P.: Business process management: a comprehensive survey. ISRN Softw. Eng. 2013(507984), 37 (2013)
Acknowledgments
The author would like to acknowledge the input from his colleague and former supervisor Pierluigi Plebani, the Information Systems research group in Politecnico di Milano, and the colleagues Marco Montali and Claudio Di Ciccio in this multi-year research work.
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Meroni, G. (2021). Artifact-Driven Process Monitoring: A Viable Solution to Continuously and Autonomously Monitor Business Processes. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds) Business Process Management. BPM 2021. Lecture Notes in Computer Science(), vol 12875. Springer, Cham. https://doi.org/10.1007/978-3-030-85469-0_5
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DOI: https://doi.org/10.1007/978-3-030-85469-0_5
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