Bidimensional process discovery for mining BPMN models

Abstract

This paper presents “BPMN Miner”, a process discovery technique that uses BPMN as the representational language for the discovery result. The proposed approach is novel in the sense that it is able to represent control-flow with BPMN constructs, but also because it augments the control-flow perspective with an organizational dimension by discovering swimlanes that represent organizational roles in the business process. Additional advantages of the proposed mining approach can be summarized as follows: it provides intuitive and easy-to-use abstraction/ specification functionality which makes it applicable to event logs with various complexity levels, it provides instant feedback about the conformance between the input log and the resulting model based on a dedicated fitness metric, it is robust to noise, and it can easily integrate with modeling and other BPM tools with exporting functionality through the XPDL-format. In this way, BPMN Miner will take process mining one step closer to the status of indispensable for business process reengineering as discovered models are immediately available in the preferred language of a majority of practitioners, educators and researchers.