  Process mining is a subfield of process science that analyzes event data
collected in databases called event logs. Recently, novel types of event data
have become of interest due to the wide industrial application of process
mining analyses. In this paper, we examine uncertain event data. Such data
contain meta-attributes describing the amount of imprecision tied with
attributes recorded in an event log. We provide examples of uncertain event
data, present the state of the art in regard of uncertainty in process mining,
and illustrate open challenges related to this research direction.
