Artificial event log of an e-commerce process

Published: 5 April 2023| Version 1 | DOI: 10.17632/csb2scywmp.1


The synthetic event logs in this dataset were automatically generated using CPN Tools in the XES format. The generated event logs result from executing the provided process model through the simulation feature in CPT Tools. The Petri net model (ecom_web_application.cpn) we used was designed based on the specification of a popular open-source e-commerce shopping website named OsCommerce (version The following aspects were prioritized when developing the model: • Including all the three supported roles by OsCommerce (admin, guest, and registered users). • Enforcing business rules through guard inscription associated with transitions. • Allowing a more realistic behavior through weighted random selection. • Maintaining users’ state during the simulation. Simulating the execution of the OsCommerce-based process model yielded an XES event log of 910 cases. Around 10,500 events from 56 classes were distributed among the cases. The events count per case ranged from 0 to 105 with a mean value of 11, and the average number of event classes per case was around 6. The generated event log reflected realistic behaviors for all the supported roles by assigning weights to the simulator transition decisions: 10% of customers placed an order, admin traffic represented 15% of the overall, customers did not usually enter long loops (e.g., add/remove from cart, login/logout), and customers followed links within the website as intended.



Auburn University


e-Commerce, Data Mining