Cross-organisational Process Mining from Message Logs
Abstract
Enterprise nets and Industry nets are specific Petri net models that together form a framework for the modelling of collaborating business processes and the specification of interactions between them. In this set-up, individual business process are modelled as Enterprise nets, while Industry nets consist of Enterprise nets that interact by exchanging messages through unidirectional channels. In previous contributions (see [21,22]), it was established how to leverage algorithms for the discovery of single processes (modelled as Enterprise nets) from event logs (consisting of finite sequences of executed actions), to synthesise systems consisting of asynchronously communicating processes (modelled as Industry nets). However, in general, it may be difficult to work with event logs from different organisations or even get access to them. Recordings of message exchanges between processes may be easier available.Therefore, we focus in this paper on the communications between different processes and turn to the investigation of message logs, \ie collections of recordings of communications in the form of message exchanges (output and input events) between two processes. In particular, the question is addressed of how a message log can be transformed into a description of the communication behaviour in the form of an event log such that the causal order on message events is preserved. Following the approach from [21,22], this event log can then be used to synthesis an Industry net.
Cite
@article{arxiv.2607.26917,
title = {Cross-organisational Process Mining from Message Logs},
author = {Pieter Kwantes and Jetty Kleijn},
journal= {arXiv preprint arXiv:2607.26917},
year = {2026}
}
Comments
This paper is the full version of an extended abstract with the same title, presented at the third International workshop on Collaboration Mining for Distributed Systems (COMINDS 2024) held in conjunction with ICPM 2024 in Copenhagen