Extraction of Object-Centric Event Logs through Virtual Knowledge Graphs

Jing Xiong; Guohui Xiao; T. E. Kalayci; Marco Montali; Zhenzhen Gu; Diego Calvanese

Extraction of Object-Centric Event Logs through Virtual Knowledge Graphs

Jing Xiong, Guohui Xiao, T. E. Kalayci, Marco Montali, Zhenzhen Gu, Diego Calvanese

Virtual Vehicle Research GmbH (98830)

Publikation: Konferenzbeitrag › Paper › Begutachtung

Abstract

Process mining is a family of techniques that supports the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream (XES)
is the most widely adopted. In XES, each event must be related to a single case object, which may lead to convergence and divergence problems. To solve such issues, object-centric approaches become promising, where objects are the central notion, and one event may refer to multiple objects. In particular,
the Object-Centric Event Logs (OCEL) standard has been proposed recently. However, the crucial problem of extracting OCEL logs from external sources is still largely unexplored. In this paper, we try to fill this gap by leveraging the Virtual Knowledge Graph (VKG) approach to access data in relational databases.
We have implemented this approach in the OnProm system, extending it from XES to OCEL support.
The full version of this article has been submitted to an international conference.

Originalsprache	englisch
Seitenumfang	6
Publikationsstatus	Veröffentlicht - 10 Aug. 2022
Veranstaltung	35th International Workshop on Description Logics - Haifa, Haifa, Israel Dauer: 7 Aug. 2022 → 10 Aug. 2022 https://dai.fmph.uniba.sk/events/dl2022/

Workshop

Workshop	35th International Workshop on Description Logics
Land/Gebiet	Israel
Ort	Haifa
Zeitraum	7/08/22 → 10/08/22
Internetadresse	https://dai.fmph.uniba.sk/events/dl2022/

Zugriff auf Dokument

http://ceur-ws.org/Vol-3263/abstract-15.pdfLizenz: CC BY 4.0

Dieses zitieren

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title = "Extraction of Object-Centric Event Logs through Virtual Knowledge Graphs",

abstract = "Process mining is a family of techniques that supports the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream (XES)is the most widely adopted. In XES, each event must be related to a single case object, which may lead to convergence and divergence problems. To solve such issues, object-centric approaches become promising, where objects are the central notion, and one event may refer to multiple objects. In particular,the Object-Centric Event Logs (OCEL) standard has been proposed recently. However, the crucial problem of extracting OCEL logs from external sources is still largely unexplored. In this paper, we try to fill this gap by leveraging the Virtual Knowledge Graph (VKG) approach to access data in relational databases.We have implemented this approach in the OnProm system, extending it from XES to OCEL support.The full version of this article has been submitted to an international conference.",

author = "Jing Xiong and Guohui Xiao and Kalayci, {T. E.} and Marco Montali and Zhenzhen Gu and Diego Calvanese",

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T1 - Extraction of Object-Centric Event Logs through Virtual Knowledge Graphs

AU - Xiong, Jing

AU - Xiao, Guohui

AU - Kalayci, T. E.

AU - Montali, Marco

AU - Gu, Zhenzhen

AU - Calvanese, Diego

PY - 2022/8/10

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AB - Process mining is a family of techniques that supports the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream (XES)is the most widely adopted. In XES, each event must be related to a single case object, which may lead to convergence and divergence problems. To solve such issues, object-centric approaches become promising, where objects are the central notion, and one event may refer to multiple objects. In particular,the Object-Centric Event Logs (OCEL) standard has been proposed recently. However, the crucial problem of extracting OCEL logs from external sources is still largely unexplored. In this paper, we try to fill this gap by leveraging the Virtual Knowledge Graph (VKG) approach to access data in relational databases.We have implemented this approach in the OnProm system, extending it from XES to OCEL support.The full version of this article has been submitted to an international conference.

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