  Process events are recorded by multiple information systems at different
granularity levels. Based on the resulting event logs, process models are
discovered at different granularity levels, as well. Events stored at a
fine-grained granularity level, for example, may hinder the discovered process
model to be displayed due the high number of resulting model elements. The
discovered process model of a real-world manufacturing process, for example,
consists of 1,489 model elements and over 2,000 arcs. Existing process model
abstraction techniques could help reducing the size of the model, but would
disconnect it from the underlying event log. Existing event abstraction
techniques do neither support the analysis of mixed granularity levels, nor
interactive exploration of a suitable granularity level. To enable the
exploration of discovered process models at different granularity levels, we
propose INEXA, an interactive, explainable process model abstraction method
that keeps the link to the event log. As a starting point, INEXA aggregates
large process models to a "displayable" size, e.g., for the manufacturing use
case to a process model with 58 model elements. Then, the process analyst can
explore granularity levels interactively, while applied abstractions are
automatically traced in the event log for explainability.
