Connecting databases with process mining: a meta model and toolset

• Published in: Software and systems modeling Vol. 18; no. 2; pp. 1209 - 1247
• Main Authors: González López de Murillas, Eduardo, Reijers, Hajo A., van der Aalst, Wil M. P.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2019; Springer Nature B.V
• Subjects: Compilers; Computer Science; Information Systems Applications (incl.Internet); Interpreters; IT in Business; Mining; Programming Languages; Programming Techniques; Software Engineering; Software Engineering/Programming and Operating Systems; Special Section Paper; Process mining; Database; Meta model; Data schema; Event extraction
• ISSN: 1619-1366; 1619-1374
• DOI: 10.1007/s10270-018-0664-7

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.