Incorporating Data Inaccuracy Considerations in Process Models

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Authors: Anna Zamansky, Pnina Soffer, Yotam Evron

Tags: 2017, conceptual modeling

Business processes are designed with the assumption that the data used by the process is an accurate reflection of reality. However, this assumption does not always hold, and situations of data inaccuracy might occur which bear substantial consequences to the process and to business goals. Until now, data inaccuracy has mainly been addressed in the area of business process management as a possible exception at runtime, to be resolved through exception handling mechanisms. Design-time analysis of potential data inaccuracy has been mostly overlooked so far. In this paper we propose a conceptual framework for incorporating data inaccuracy considerations in process models to support an analysis of data inaccuracy at design time and empirically evaluate its usability by process designers.

Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-319-59466-8_19