Abstract
Unmanaged business processes are an inevitable part of the operation of enterprises of all kinds. At the same time, monitoring such processes and measuring compliance against business policies is particularly difficult due to the effort needed to manually piece together information. A major challenge here is the presumption of incomplete or missing information and the uncertainty in making inferences about what actually occured.
This work proposes the use of a probabilistic provenance model to track the history of various process artifacts and reconstruct process traces. The major contribution of the work is the method of modeling the uncertainty associated with raw information as well as inferred relationships in a first class manner within the provenance model. We apply the techniques described here to a real world problem and compare results obtained in previous work where such uncertainties were ignored. The techniques described here are widely applicable to unmanaged business processes.
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Mukhi, N.K. (2010). Monitoring Unmanaged Business Processes. In: Meersman, R., Dillon, T., Herrero, P. (eds) On the Move to Meaningful Internet Systems: OTM 2010. OTM 2010. Lecture Notes in Computer Science, vol 6426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16934-2_7
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DOI: https://doi.org/10.1007/978-3-642-16934-2_7
Publisher Name: Springer, Berlin, Heidelberg
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