A framework for multi-perspective process mining into a BPMN process model

Tiftik M. N., Gurgen Erdogan T., KOLUKISA TARHAN A.

MATHEMATICAL BIOSCIENCES AND ENGINEERING, vol.19, no.11, pp.11800-11820, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 19 Issue: 11
  • Publication Date: 2022
  • Doi Number: 10.3934/mbe.2022550
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, Compendex, EMBASE, MathSciNet, MEDLINE, zbMATH, Directory of Open Access Journals
  • Page Numbers: pp.11800-11820
  • Keywords: Process mining, multi-perspective process mining, BPMN, blockchain
  • Hacettepe University Affiliated: Yes


Process mining is mainly focused on process discovery from control perspective. It is further applied to mine the other perspectives such as time, data, and resources by replaying the events in event logs over the initial process model. When process mining is extended far beyond discovering the control-flow models to capture additional perspectives; roles, bottlenecks, amounts of time passed, guards, and routing probabilities in the process can be identified. This is a such extensions are considered under the topic of multi-perspective process mining, which makes the discovered process model more understandable. In this study, a framework for applying multi-perspective process mining and creating a Business Process Modelling Notation (BPMN) process model as the output is introduced. The framework, which uses a recently developed application programming interface (API) for storing the BPMN Data Model which keeps what is produced from each perspective as an asset into a private blockchain in a secure and immutable way, has been developed as a plugin to the ProM tool. In doing so, it integrates a number of techniques for multi-perspective process mining in literature, for the perspectives of control-flow, data, and resource; and represents a holistic process model by combining the outputs of these in the BPMN Data Model. In this article, we explain technical details of the framework and also demonstrate its usage over a case in medical domain.