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A Decision Framework for Understanding Data-Aware Business Process Models

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 618))

Abstract

Business Process Management is a discipline that enables organizations to analyze, design and deploy business processes, providing tools to investigate the processes from an organizational point of view and transforming the design into a working software implementation.

The Business Process Modeling and Notation (BPMN [1]) is the most widely adopted modeling language for designing and re-engineering business processes. One of best feature is that it provides a graphical representation that is not only easy to understand by business people without technical expertise but also machine processable, with tasks assigned to software or human agents based on the workflow and rules defined within the process.

This paper extends the framework presented by the author in [2] adding the possibility of verifying more properties of data-aware business processes using a novel approach. This approach enables the verification of the conformance to the business rules combining logic and mathematical expressions. Moreover, the new framework gives the possibility of separating the business requirements from the implementation, giving hints to the process designer and to the programmer. Finally, it gives directions for open research challenges.

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Correspondence to Raffaele Dell’Aversana .

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Dell’Aversana, R. (2018). A Decision Framework for Understanding Data-Aware Business Process Models. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics: In the Tradition of Herbert A. Simon's Heritage. DCAI 2017. Advances in Intelligent Systems and Computing, vol 618. Springer, Cham. https://doi.org/10.1007/978-3-319-60882-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-60882-2_5

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