BPMN Data Model for Multi-Perspective Process Mining on Blockchain

Ekici B., ERDOĞAN T., KOLUKISA TARHAN A.

INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, cilt.32, sa.02, ss.317-345, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Sayı: 02
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1142/s0218194022500115
  • Dergi Adı: INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.317-345
  • Anahtar Kelimeler: Process mining, blockchain, BPMN, business process, methodologies and tools
  • Hacettepe Üniversitesi Adresli: Evet

Özet

Process mining mainly focuses on discovering control flow models, conformance checking and analyzing bottlenecks. It extends the scope by looking at the other perspectives like time, data and resources by connecting events in the event logs to this process model. These perspectives are not isolated and are all related to each other. For each perspective, there is a different technique, which is dedicated to the relevant perspective, applied and these techniques may need to consume the results of one another in a sequence of process mining analyses. As a result, a holistic process model is created by attaching and binding related attributes of the event logs to the backbone (control flow) of the model. Therefore, representing the holistic model and keeping what is produced from each perspective in a secure and immutable way while applying the multiple perspectives become important. In this study, a BPMN-extended Data Model is proposed to put together the models from the multi-perspective process mining and a tool is developed to keep this data model as an asset into a private blockchain developed by using Hyperledger Fabric. The practical relevance and validity of the approach are shown in the case studies that use real-life data from two different domains.