Extended Event Log: Towards a Unified Standard for Process Mining

Process mining has grown popular today given their ability to provide managers with insights into the actual business process as executed by employees. Process mining depends on event logs found in process aware information systems to model business processes. This has raised the need to develop event log standards given that event logs are the entry point to any process mining project. One of the main challenges of event logs and process mining in general as was mentioned by the IEEE task force on process mining deals with the finding, merging & cleaning event data. This resulted in having multiple event log standards with different features. This paper attempts to propose a new unified standard for event logs that enriches the results of process mining without the need to tailor event logs for each process mining project.

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Published
2024-12-17
DOI
https://doi.org/10.1109/icca62237.2024.10927750
Primary Topic
Business Process Modeling and Analysis
Type
article
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article

Extended Event Log: Towards a Unified Standard for Process Mining

Ali Suleiman, Gamal Kassem
Business Process Modeling and Analysis
article

Extended Event Log: Towards a Unified Standard for Process Mining

Ali Suleiman, Gamal Kassem
article en

Abstract

Process mining has grown popular today given their ability to provide managers with insights into the actual business process as executed by employees. Process mining depends on event logs found in process aware information systems to model business processes. This has raised the need to develop event log standards given that event logs are the entry point to any process mining project. One of the main challenges of event logs and process mining in general as was mentioned by the IEEE task force on process mining deals with the finding, merging & cleaning event data. This resulted in having multiple event log standards with different features. This paper attempts to propose a new unified standard for event logs that enriches the results of process mining without the need to tailor event logs for each process mining project.

German University in Cairo (EG)
Openalex Percentile: Top 55%
Business Process Modeling and Analysis
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