Managing Complexity in Object-Centric Process Mining: A Cohesion-Driven Decomposition and Aggregation Framework

Khalil Mecheraoui

doi:10.7250/csimq.2026-47.04

Managing Complexity in Object-Centric Process Mining: A Cohesion-Driven Decomposition and Aggregation Framework

Authors

Khalil Mecheraoui ICOSI Laboratory, Abbes Laghrour University, Khenchela, 40004, Algeria and Higher National School of Forests, Khenchela, 40000, Algeria https://orcid.org/0000-0001-9906-6074

DOI:

https://doi.org/10.7250/csimq.2026-47.04

Keywords:

Object-Centric Process Mining, Object-Centric Petri Nets, Process Decomposition, Process Architecture, Cohesion and Coupling

Abstract

Object-Centric Process Mining (OCPM) often discovers models that are too dense and complex for effective human comprehension. To address this challenge, this work proposes a novel framework for the automated decomposition and aggregation of Object-Centric Petri Nets (OCPNs). The framework is based on the principles of high cohesion and low coupling. First, the Composite Cohesion Metric is introduced to measure the relational strength between object types from three distinct perspectives: behavioral synchronization, structural composition, and empirical log-based co-occurrence. By mapping these measures to a weighted graph and applying modularity-based community detection, the overall model is partitioned into semantically coherent sub-process modules. Finally, an Aggregated Net is constructed to offer a high-level architectural view of the system. The proposed framework is evaluated using the standard Order Management benchmark. The results demonstrate that the approach used successfully structures the process into distinct logical execution layers. The approach correctly assigns resource objects to their functional modules. The proposed framework significantly reduces the complexity of the model without affecting its global validity.

Supporting Agencies

Ministry of Higher Education and Scientific Research of Algeria

References

W. M. P. van der Aalst, Process Mining: Data Science in Action. 2nd edition, Springer, 2016.

W. M. P. van der Aalst, Process Mining Handbook. Lecture Notes in Business Information Processing, vol. 448. Springer, 2022.

W. M. P. van der Aalst, “Object-centric process mining: Dealing with divergence and convergence in event data,” in Software Engineering and Formal Methods. SEFM 2019. Lecture Notes in Computer Science, vol. 11724, Springer, 2019, pp. 3–25.

W. M. P. van der Aalst, “Object-centric process mining: Unraveling the fabric of real processes,” Mathematics, vol. 11, no. 12, article 2691, 2023.

W. M. P. van der Aalst and A. Berti, “Discovering object-centric petri nets,” Fundamenta Informaticae, vol. 175, no. 1–4, pp. 1–40, 2020.

A. Berti, G. Park, M. Rafiei, and W. M. P. van der Aalst, “OCEL 2.0 specification,” RWTH Aachen University, Tech. Rep., 2024. Available: https://www.ocel-standard.org/

H. Dhama, “Quantitative models of cohesion and coupling in software,” Journal of Systems and Software, vol. 29, no. 1, pp. 65–74, 1995.

D. L. Parnas, “On the criteria to be used in decomposing systems into modules,” Communications of the ACM, vol. 15, no. 12, pp. 1053–1058, 1972.

V. D. Blondel, J.-L. Guillaume, R. Lambiotte, and E. Lefebvre, “Fast unfolding of communities in large networks,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2008, no. 10, article P10008, 2008.

W. M. P. van der Aalst, “Decomposing Petri nets for process mining: A generic approach,” Distributed and Parallel Databases, vol. 31, pp. 471–507, 2013.

W. M. P. van der Aalst, “Decomposing process mining problems using passages,” in Application and Theory of Petri Nets. PETRI NETS 2012. Lecture Notes in Computer Science, vol. 7347, Springer, 2012, pp. 72–91.

J. Muñoz-Gama, J. Carmona, and W. M. P. van der Aalst, “Conformance checking in the large: Partitioning and topology,” in Business Process Management. Lecture Notes in Computer Science, vol. 8094, Springer, 2013, pp. 130–145.

H. M. W. Verbeek and W. M. P. van der Aalst, “Merging Alignments for Decomposed Replay,” in Application and Theory of Petri Nets and Concurrency. PETRI NETS 2016. Lecture Notes in Computer Science, vol. 9698, Springer, 2016, pp. 219–239.

W. L. J. Lee, H. M. W. Verbeek, J. Muñoz-Gama, W. M. P. van der Aalst, and M. Sepúlveda, “Recomposing conformance: Closing the circle on decomposed alignment-based conformance checking in process mining,” Information Sciences, vol. 466, pp. 55–91, 2018.

K. Mecheraoui, J. C. Carrasquel, and I. A. Lomazova, “Compositional conformance checking of nested petri nets and event logs of multi-agent systems,” arXiv preprint arXiv:2003.07291, 2020.

M. Song, C. W. Günther, and W. M. P. van der Aalst, “Trace clustering in process mining,” in Business Process Management Workshops. BPM 2008. Lecture Notes in Business Information Processing, vol. 17, Springer, 2009, pp. 109–120.

S. J. J. Leemans, D. Fahland, and W. M. P. van der Aalst, “Using life cycle information in process discovery,” in Business Process Management Workshops. BPM 2015, Lecture Notes in Business Information Processing, vol. 256, Springer, 2016, pp. 204–217.

A. Jalali, “Object Type Clustering Using Markov Directly-Follow Multigraph in Object-Centric Process Mining,” IEEE Access, vol. 10, pp. 126569–126579, 2022.

S. Khayatbashi, N. Miri, and A. Jalali, “Advancing object-centric process mining with multi-dimensional data operations,” arXiv preprint arXiv:2412.00393, 2024.

S. Khayatbashi, N. Miri, and A. Jalali, “OLAP operations for object-centric process mining,” in Intelligent Information Systems. CAiSE 2025. Lecture Notes in Business Information Processing, vol. 557, Springer, 2025, pp. 111–118.

A. Lomazova, “Nested Petri Nets – a Formalism for Specification and Verification of Multi-Agent Distributed Systems,” Fundamenta Informaticae, vol. 43, no. 1–4, pp. 195–214, 2000.

D. Fahland, “Describing behavior of processes with many-to-many interactions,” in Application and Theory of Petri Nets and Concurrency. PETRI NETS 2019. Lecture Notes in Computer Science, vol. 11522, Springer, 2019, pp. 3–24.

M. E. J. Newman and M. Girvan, “Finding and evaluating community structure in networks,” Physical Review E, vol. 69, no. 2, 2004.

M. E. J. Newman, “Modularity and community structure in networks,” Proceedings of the National Academy of Sciences, vol. 103, no. 23, pp. 8577–8582, 2006.

OCEL Standard, “Order Management – OCEL 2.0 simulation log,” OCEL Standard Repository, 2023. Available: https://www.ocel-standard.org/event-logs/simulations/order-management/

A. Berti, S. van Zelst, and D. Schuster, “PM4Py: A process mining library for Python,” Software Impacts, vol. 17, article 100556, 2023.