As event logs are often not generated specifically for the application of process mining, events granularity of the event log at hand might be too low level. It is vital for successful application of process discovery techniques to have event logs at an appropriate level of abstraction. Process discovery techniques when the input event log is too low level might result in process model with one or more undesired properties. First of all, the resulting process model might be “spaghetti”-like, as shown in Figure \[fig:spaghetti\], containing of an uninterpretable mess of nodes and connections. The aim of process discovery is to discover a structured, “lasagna”-like, process model as shown in Figure \[fig:lasagna\], which is much more interpretable than a “spaghetti”-like model. Secondly, the activities in the process model might have too specific, non-meaningful, names. Third, as we show in section \[sec:motivating\_example\], process discovery algorithms are sometimes not able to discover a process model that represents the low-level event log well, while being able to discover to discover a representative process model from a corresponding high-level event log. The problems mentioned illustrate the need for a method to abstract too low-level event logs into higher level event logs.

![A structured, or 