May I Take Your Order? On the Interplay Between Time and Order in Process Mining

Abstract

Process mining starts from event data. The ordering of events is vital for the discovery of process models. However, the timestamps of events may be unreliable or imprecise. To further complicate matters, also causally unrelated events may be ordered in time. The fact that one event is followed by another does not imply that the former causes the latter. This paper explores the relationship between time and order. Moreover, it describes an approach to preprocess event data having timestamp-related problems. This approach avoids using accidental or unreliable orders and timestamps, creates partial orders to capture uncertainty, and allows for exploiting domain knowledge to (re)order events. Optionally, the approach also generates interleavings to be able to use existing process mining techniques that cannot handle partially ordered event data. The approach has been implemented using ProM and can be applied to any event log.

Visualizing Trace Variants From Partially Ordered Event Data

“…Various visualizations of event data are offered; however, a variant explorer, as considered in this paper, is not available. In [2], the authors present a plugin for ProM to visualize partially ordered event data. The approach considers events to be atomic, i.e., an event representing the start and an event representing the completion of an activity are considered to be separate events.…”

“…Compared to our approach, we consider non-atomic activity instances, i.e., we map start and complete events of a process activity to an activity instance. Next, we relate these activity instances to each other instead of atomic events as proposed in [2]. Therefore, both approaches, the one presented in [2] and the one presented in this paper, can coexist and each have their advantages and disadvantages.…”

“…Next, we relate these activity instances to each other instead of atomic events as proposed in [2]. Therefore, both approaches, the one presented in [2] and the one presented in this paper, can coexist and each have their advantages and disadvantages.…”