Gast ::
A transformation between object-centric causal nets and object-centric Petri nets
2026
Bachelorarbeit, RWTH Aachen University, 2025
Veröffentlicht auf dem Publikationsserver der RWTH Aachen University
Genehmigende Fakultät
Fak01
Hauptberichter/Gutachter
; ;
Tag der mündlichen Prüfung/Habilitation
2025-09-23
Online
DOI: 10.18154/RWTH-2026-00605
URL: http://publications.rwth-aachen.de/record/1025217/files/1025217.pdf
Einrichtungen
Thematische Einordnung (Klassifikation)
DDC: 004
Kurzfassung
Process mining analyzes event data to improve real-world processes. The use of various process models, each with distinct representational biases, necessitates transformations between them to leverage unique strengths and tool support. The emerging field of object-centric process mining predominantly lacks such methods. This thesis addresses this gap by proposing bidirectional transformations between object-centric causal nets, a newly proposed formalism, and object-centric Petri nets, a well-established process model. This work contributes formal definitions of the transformations, formal proofs of their correctness, a publicly available implementation, a qualitative evaluation, and play-out and replay procedures for both process models. An object-centric Petri net is transformed into a behaviorally equivalent object-centric causal net. Conversely, an object-centric causal net is transformed into an object-centric Petri net that underfits the initial net. Our qualitative evaluation shows that the degree of underfitting is directly related to the structure of the initial object-centric causal net, particularly the number of activities having markers allowed to consume a variable amount of obligations.
OpenAccess: 
PDF
(zusätzliche Dateien)
Dokumenttyp
Bachelor Thesis
Format
online
Sprache
English
Interne Identnummern
RWTH-2026-00605
Datensatz-ID: 1025217
Beteiligte Länder
Germany
|
The record appears in these collections: |