Container Logistics Object-centric Event Log Simulated with CPN-Tools

Benedikt Knopp from RWTH Aachen University created an artificial event log for container logistics. The log contains 35,761 events and 14,013 objects across 7 object types, simulated according to the OCEL 2.0 standard using CPN-Tools. It models the process from customer order registration to container shipment, including events like booking vehicles and loading trucks.

Use Cases

• Develop and test process discovery algorithms based on the described multi-object interactions like containers, vehicles, and orders.
• Train predictive models for container rescheduling based on the described 'reschedule container' event and vehicle capacity constraints.
• Analyze object lifecycle conformance in logistics workflows based on the 7 object types and 14 event types described.
• Benchmark process mining tools using the standardized OCEL 2.0 format and the provided CPN model.

Strengths

• Log follows the standardized OCEL 2.0 format, ensuring interoperability with compliant tools.
• Contains a substantial volume of 35,761 simulated events for model training and testing.
• Models a complex, multi-object process with 7 distinct object types (e.g., order, container, vehicle).

Limitations

• Data is artificially simulated, which may not capture all real-world complexities and variances.
• Column-level documentation is absent; field semantics must be inferred from the process description or after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Benedikt Knopp, RWTH Aachen University

Collection Method

Artificially simulated using CPN-Tools according to the OCEL 2.0 standard.