The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/afd6f608-469e-48f9-977d-875b45840d39

Eric Verbeek; Verbeek, H.M.W. (Eric) (2023): Process Discovery Contest 2023. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/afd6f608-469e-48f9-977d-875b45840d39.v1

Dataset

• Information Systems
• Information and Computing Sciences

Artificial event logs, PDC 2023, Process Discovery Contest, Task Force on Process Mining

CC0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Eric Verbeek , H.M.W. (Eric) Verbeek

This data set contains the data set as was used for the Process Discovery Contest of 2023 (PDC 2023).

The data set contains 384 training logs, 96 corresponding test logs and base logs, 96 corresponding

ground truth logs, and 96 models. The logs are all stored using the IEEE XES file format (see either

 https://www.xes-standard.org/ or https://ieeexplore.ieee.org/document/7740858), while the models are

workflow nets (a subclass of Petri nets) stored in the PNML fileformat (see

https://www.iso.org/obp/ui/#iso:std:iso-iec:15909:-2:ed-1:v1:en).

• 2023-10-04 first online, published, posted

4TU.ResearchData

IEEE XES, ISO PNML

https://icpmconference.org/2023/process-discovery-contest/

Task Force on Process Mining (https://tf-pm.org)