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Automatic discovery of data-centric and artifact-centric processes

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Automatic Discovery of Data-Centric and Artifact-Centric Processes E.H.J. Nooijen, B.F. van Dongen, and D. Fahland Eindhoven University of Technology Eindhoven, The Netherlands [email protected], {b.f.v.dongen,[email protected] Abstract. Process discovery is a technique that allows for automatically discov- ering a process model from recorded executions of a process as it happens in reality. This technique has successfully been applied for classical processes where one process execution is constituted by a single case with a unique case identi- fier. Data-centric and artifact-centric systems such as ERP systems violate this assumption. Here a process execution is driven by process data having various notions of interrelated identifiers that distinguish the various interrelated data objects of the process. Classical process mining techniques fail in this setting. This paper presents an automatic technique for discovering for each notion of data object in the process a separate process model that describes the evolution of this object, also known as artifact life-cycle model. Given a relational database that stores process execution information of a data-centric system, the technique extracts event information, case identifiers and their interrelations, discovers the central process data objects and their associated events, and decomposes the data source into multiple logs, each describing the cases of a separate data object. Then classical process discovery techniques can be applied to obtain a process model for each object. The technique is implemented and has been evaluated on the production ERP system of a large retailer. Key words: artifact, process discovery, ERP system, event log 1 Introduction Process discovery is a technique for automatically discovering a process model from recorded executions of the process. The technique is successfully applied for classical processes where each process execution is recorded as a case (the sequence of its events) in an event log. E

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