Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/43083
Title: | Extracting Event Data from Document-Driven Enterprise Systems | Authors: | Calvanese, Diego JANS, Mieke Kalayci, Tahir Emre Montali, Marco |
Issue Date: | 2023 | Publisher: | Springer | Source: | Indulska, M.; Reinhartz-Berger, I.; Cetina, C.; Pastor, O. (Ed.). Advanced Information Systems Engineering, Springer, p. 193 -209 | Series/Report: | Lecture notes in Computer Science | Series/Report no.: | 13901 | Abstract: | The preparation of input event data is one of the most critical phases in process mining projects. Different frameworks have been developed to offer methodologies and/or supporting toolkits for data preparation. One of these frameworks, called OnProm, relies on sophisticated semantic technologies to extract event logs from relational databases. The toolkit consists of a series of general steps, meant to work on arbitrary, legacy databases. However, in many settings, the input database is not a legacy one but is structured with conceptually understandable object types and relationships that can be effectively employed to support business users in the extraction process. This is, for example, the case for document-driven enterprise systems. In this paper, we focus on this class of systems and propose a guided approach, erprep, to support a group of business and technical users in setting up OnProm with minimal effort. We demonstrate the approach in a real-life use case. | Keywords: | Data preparation;event log extraction;ERP systems;Ontology-based event modeling | Document URI: | http://hdl.handle.net/1942/43083 | ISBN: | 978-3-031-34559-3 978-3-031-34560-9 |
DOI: | 10.1007/978-3-031-34560-9_12 | ISI #: | 001284775300012 | Category: | C1 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
Files in This Item:
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Pages from 978-3-031-34560-9.pdf Restricted Access | Published version | 755.85 kB | Adobe PDF | View/Open Request a copy |
erprep_CAiSE.pdf | Peer-reviewed author version | 436.29 kB | Adobe PDF | View/Open |
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