  The discipline of process mining aims to study processes in a data-driven
manner by analyzing historical process executions, often employing Petri nets.
Event data, extracted from information systems (e.g. SAP), serve as the
starting point for process mining. Recently, novel types of event data have
gathered interest among the process mining community, including uncertain event
data. Uncertain events, process traces and logs contain attributes that are
characterized by quantified imprecisions, e.g., a set of possible attribute
values. The PROVED tool helps to explore, navigate and analyze such uncertain
event data by abstracting the uncertain information using behavior graphs and
nets, which have Petri nets semantics. Based on these constructs, the tool
enables discovery and conformance checking.
