Data-driven Process Discovery - Artificial Event Log

Datacite citation style:
Mannhardt, Felix (2016): Data-driven Process Discovery - Artificial Event Log. Version 1. 4TU.ResearchData. dataset.
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A synthetic event log with 100,000 traces and 900,000 events that was generated by simulating a simple artificial process model. There are three data attributes in the event log: Priority, Nurse, and Type. Some paths in the model are recorded infrequently based on the value of these attributes. Noise is added by randomly adding one additional event to an increasing number of traces. CPN Tools ( was used to generate the event log and inject the noise.
  • 2016-12-08 first online, published, posted
Eindhoven University of Technology
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Eindhoven University of Technology, Department of Mathematics and Computer Science


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