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Synthesizing of Process-Aware Digital Twin Cockpits from Event Logs

Autor(en):
Bano, Dorina [DBLP] ;
Michael, Judith [DBLP] ;
Rumpe, Bernhard [DBLP] ;
Varga, Simon [DBLP] ;
Weske, Mathias [DBLP]
Zusammenfassung
In this work, we summarize our article “Process-Aware Digital Twin Cockpit Synthesis from Event Logs” published in the Journal of Computer Languages (COLA). The engineering of digital twins and their user interfaces with explicated processes, namely process-aware digital twin cockpits (PADTCs), is challenging due to the complexity of the systems and the need for information from different disciplines within the engineering process. Therefore, we have investigated how to facilitate their engineering by using already existing data, namely event logs. We present a low-code development approach that reduces the amount of hand-written code needed to derive PADTCs using process mining techniques. We describe what models could be derived from event log data, which generative steps are needed for the engineering of PADTCs, and how process mining could be incorporated into the resulting application. A PADTC prototype is created based on the MIMIC III dataset, which simulates an automated hospital transportation system. Initially, our approach requires no hand-written code and empowers the domain expert to iteratively create PADTC prototypes.
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Bano, D., Michael, J., Rumpe, B., Varga, S. & Weske, M., (2023). Synthesizing of Process-Aware Digital Twin Cockpits from Event Logs. In: Engels, G., Hebig, R. & Tichy, M. (Hrsg.), Software Engineering 2023. Bonn: Gesellschaft für Informatik e.V.. (S. 33-34).
@inproceedings{mci/Bano2023,
author = {Bano, Dorina AND Michael, Judith AND Rumpe, Bernhard AND Varga, Simon AND Weske, Mathias},
title = {Synthesizing of Process-Aware Digital Twin Cockpits from Event Logs},
booktitle = {Software Engineering 2023},
year = {2023},
editor = {Engels, Gregor AND Hebig, Regina AND Tichy, Matthias} ,
pages = { 33-34 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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Mehr Information

ISBN: 978-3-88579-726-5
ISSN: 1617-5468
Datum: 2023
Sprache: en (en)
Typ: Text/Conference Paper

Keywords

  • Process-Aware Digital Twin Cockpit
  • Low-Code Development Approaches
  • Sensor Data
  • Event Log
  • Process Mining
  • Process-Awareness
Sammlungen
  • P332 - Software Engineering 2023 [60]

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Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.