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Modelling and Execution of Data-Driven Processes with JSON-Nets

Fritsch, Andreas 1; Schüler, Selina ORCID iD icon 1; Forell, Martin ORCID iD icon 1; Oberweis, Andreas ORCID iD icon 1
1 Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB), Karlsruher Institut für Technologie (KIT)

Abstract:

Modern business environments are governed by a wide range of data in various data formats. Despite the importance of integrating the data and control-flow perspective, existing business process modelling languages have only limited capability to precisely describe data-driven processes. In this paper, we propose a new approach called JSON-Nets, a variant of high-level Petri nets, that utilizes JSON technologies to integrate complex data objects in executable process models. We introduce JSON-Nets using an illustrative example and provide a formal specification, as well as a prototypical implementation of a modelling tool to evaluate our conception.


Originalveröffentlichung
DOI: 10.1007/978-3-031-34241-7_3
Scopus
Zitationen: 2
Dimensions
Zitationen: 1
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Buchaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISBN: 978-3-031-34241-7
ISSN: 1865-1348
KITopen-ID: 1000166023
Erschienen in Enterprise, Business-Process and Information Systems Modeling : 24th International Conference, BPMDS 2023, and 28th International Conference, EMMSAD 2023, Zaragoza, Spain, June 12–13, 2023, Proceedings. Ed.: H. van der Aa
Verlag Springer Nature Switzerland
Seiten 29–43
Serie Lecture Notes in Business Information Processing ; 479
Vorab online veröffentlicht am 31.05.2023
Nachgewiesen in Dimensions
Scopus
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