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Dynamically Switching Execution Context in Data-Centric BPM Approaches

In contemporary business process management software, the context in which a process is executed is largely static. While the execution of the process itself may be flexible, on-the-fly changes to the context, i.e., physical or logical surroundings, are either limited or impossible. This paper prese...

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Detalles Bibliográficos
Autores principales: Andrews, Kevin, Steinau, Sebastian, Reichert, Manfred
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7254560/
http://dx.doi.org/10.1007/978-3-030-49418-6_1
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author Andrews, Kevin
Steinau, Sebastian
Reichert, Manfred
author_facet Andrews, Kevin
Steinau, Sebastian
Reichert, Manfred
author_sort Andrews, Kevin
collection PubMed
description In contemporary business process management software, the context in which a process is executed is largely static. While the execution of the process itself may be flexible, on-the-fly changes to the context, i.e., physical or logical surroundings, are either limited or impossible. This paper presents concepts for enabling context switching at runtime for the object-aware process management paradigm. Such context switches are enabled at various granularity levels, such as shifting entire process instances to different systems, or migrating sub-processes between different parent processes. We further contribute the algorithms employed in our proof-of-concept implementation and discuss use cases in which context switching capabilities can be utilized. Implementing these advanced concepts helps showcase the maturity of data-centric BPM.
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spelling pubmed-72545602020-05-28 Dynamically Switching Execution Context in Data-Centric BPM Approaches Andrews, Kevin Steinau, Sebastian Reichert, Manfred Enterprise, Business-Process and Information Systems Modeling Article In contemporary business process management software, the context in which a process is executed is largely static. While the execution of the process itself may be flexible, on-the-fly changes to the context, i.e., physical or logical surroundings, are either limited or impossible. This paper presents concepts for enabling context switching at runtime for the object-aware process management paradigm. Such context switches are enabled at various granularity levels, such as shifting entire process instances to different systems, or migrating sub-processes between different parent processes. We further contribute the algorithms employed in our proof-of-concept implementation and discuss use cases in which context switching capabilities can be utilized. Implementing these advanced concepts helps showcase the maturity of data-centric BPM. 2020-05-05 /pmc/articles/PMC7254560/ http://dx.doi.org/10.1007/978-3-030-49418-6_1 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Andrews, Kevin
Steinau, Sebastian
Reichert, Manfred
Dynamically Switching Execution Context in Data-Centric BPM Approaches
title Dynamically Switching Execution Context in Data-Centric BPM Approaches
title_full Dynamically Switching Execution Context in Data-Centric BPM Approaches
title_fullStr Dynamically Switching Execution Context in Data-Centric BPM Approaches
title_full_unstemmed Dynamically Switching Execution Context in Data-Centric BPM Approaches
title_short Dynamically Switching Execution Context in Data-Centric BPM Approaches
title_sort dynamically switching execution context in data-centric bpm approaches
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7254560/
http://dx.doi.org/10.1007/978-3-030-49418-6_1
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