Connecting databases with process mining: a meta model and toolset

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Abstract

Process mining techniques require event logs which, in many cases, are obtained from databases. Obtaining these event logs is not a trivial task and requires substantial domain knowledge. In addition, an extracted event log provides only a single view on the database. To change our view, e.g., to focus on another business process and generate another event log, it is necessary to go back to the source of data. This paper proposes a meta model to integrate both process and data perspectives, relating one to the other. It can be used to generate different views from the database at any moment in a highly flexible way. This approach decouples the data extraction from the application of analysis techniques, enabling the application of process mining in different contexts.

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González López de Murillas, E., Reijers, H. A., & van der Aalst, W. M. P. (2019). Connecting databases with process mining: a meta model and toolset. Software and Systems Modeling, 18(2), 1209–1247. https://doi.org/10.1007/s10270-018-0664-7

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