Paper Number
1918
Abstract
Handling inconsistencies in business rules is an important part of corporate compliance management. This includes the resolution of inconsistencies, which currently is a fully automated process that might not always be plausible in a real-world scenario. To include human experts and develop interactive resolution approaches, an understanding of inconsistencies is crucial. Thus, we focus on investigating inconsistency understanding in declarative process models by testing the applicability of insights from declarative process model understanding to different inconsistency characteristics. In the future, this will provide the basis for a series of cognitive experiments evaluating the effects of inconsistency characteristics and representation on inconsistency understanding in declarative process models.
Recommended Citation
Nagel, Sabine and Delfmann, Patrick, "Investigating Inconsistency Understanding to Support Interactive Inconsistency Resolution in Declarative Process Models" (2022). ECIS 2022 Research-in-Progress Papers. 59.
https://aisel.aisnet.org/ecis2022_rip/59
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