A Web-based System for Business Process Discovery: Leveraging the SICN-Oriented Process Mining Algorithm with Django, Cytoscape, and Graphviz

• Thanh-Hai Nguyen,
• Kyoung-Sook Kim,
• Dinh-Lam Pham,
• Kwanghoon Pio Kim,

Vol. 18, No. 8, August 31, 2024
10.3837/tiis.2024.08.014, Download Paper (Free):

• Business process discovery
• web-based application
• Process Mining
• Business Process Management
• Workflow Management

Abstract

In this paper, we introduce a web-based system that leverages the capabilities of the ρ(rho)-algorithm, which is a Structure Information Control Net (SICN)-oriented process mining algorithm, with open-source platforms, including Django, Graphviz, and Cytoscape, to facilitate the rediscovery and visualization of business process models. Our approach involves discovering SICN-oriented process models from process instances from the IEEE XES-formatted process enactment event logs dataset. This discovering process is facilitated by the ρ-algorithm, and visualization output is transformed into either a JSON or DOT formatted file, catering to the compatibility requirements of Cytoscape or Graphviz, respectively. The proposed system utilizes the robust Django platform, which enables the creation of a user-friendly web interface. This interface offers a clear, concise, modern, and interactive visualization of the rediscovered business processes, fostering an intuitive exploration experience. The experiment conducted on our proposed web-based process discovery system demonstrates its ability and efficiency showing that the system is a valuable tool for discovering business process models from process event logs. Its development not only contributes to the advancement of process mining but also serves as an educational resource. Readers, students, and practitioners interested in process mining can leverage this system as a completely free process miner to gain hands-on experience in rediscovering and visualizing process models from event logs.

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