Browsing SINTEF Open by Author "Koschmider, Agnes"

Now showing items 1-5 of 5

    • ELPaaS: Event Log Privacy as a Service 

      Bauer, Martin; Fahrenkrog-Petersen, Stephan A.; Koschmider, Agnes; Mannhardt, Felix; van der Aa, Han; Weidlich, Matthias (Peer reviewed; Journal article, 2019)
      The privacy of an organization's workers represents a crucial concern in process mining settings, where data on an individual's performance is recorded and possibly shared for analysis. To enable users to appropriately ...

    • Event abstraction in process mining: literature review and taxonomy 

      van Zelst, Sebastiaan J.; Mannhardt, Felix; de Leoni, Massimiliano; Koschmider, Agnes (Peer reviewed; Journal article, 2020)
      The execution of processes in companies generates traces of event data, stored in the underlying information system(s), capturing the actual execution of the process. Analyzing event data, i.e., the focus of process mining, ...

    • On the Contextualization of Event-Activity Mappings 

      Koschmider, Agnes; Mannhardt, Felix; Tobias, Heuser (Journal article; Peer reviewed, 2019)
      Event log files are used as input to any process mining algorithm. A main assumption of process mining is that each event has been assigned to a distinct process activity already. However, such mapping of events to activities ...

    • Privacy-Preserving Process Mining: Differential Privacy for Event Logs 

      Mannhardt, Felix; Koschmider, Agnes; Baracaldo, Nathalie; Weidlich, Matthias; Michael, Judith (Journal article; Peer reviewed, 2019)
      Privacy regulations for data can be regarded as a major driver for data sovereignty measures. A specific example for this is the case of event data that is recorded by information systems during the processing of entities ...

    • Quantifying the Re-identification Risk of Event Logs for Process Mining 

      Nuñez von Voigt, Saskia; Fahrenkrog-Petersen, Stephan; Janssen, Dominik; Koschmider, Agnes; Tschorsch, Florian; Mannhardt, Felix; Landsiedel, Olaf; Weidlich, Matthias (Peer reviewed; Journal article, 2020)
      Event logs recorded during the execution of business processes constitute a valuable source of information. Applying process mining techniques to them, event logs may reveal the actual process execution and enable reasoning ...