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Archive · dataset · 2016

Data-driven Process Discovery - Artificial Event Log

Listed in DataCite

A synthetic event log with 100,000 traces and 900,000 events that was generated by simulating a simple artificial process model.

Description

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 (cpntools.org) was used to generate the event log and inject the noise.

Links

Topics

Stated by source
Economics and business
Provenance · 1 source records, 6 field assertions
SourceKeyLast seenRaw
DataCite10.4121/uuid:32cad43f-8bb9-46af-8333-48aae2bea03711 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].fos:economics-and-businesssource · DataCiteconnector:datacite@1.0.0
descriptionsource · DataCiteconnector:datacite@1.0.0/data/attributes/descriptions
license_textsource · DataCiteconnector:datacite@1.0.0
publication_datesource · DataCiteconnector:datacite@1.0.0/data/attributes/dates
titlesource · DataCiteconnector:datacite@1.0.0/data/attributes/titles/0/title
version_labelsource · DataCiteconnector:datacite@1.0.0