  Event logs, as viewed in process mining, contain event data describing the
execution of operational processes. Most process mining techniques take an
event log as input and generate insights about the underlying process by
analyzing the data provided. Consequently, handling large volumes of event data
is essential to apply process mining successfully. Traditionally, individual
process executions are considered sequentially ordered process activities.
However, process executions are increasingly viewed as partially ordered
activities to more accurately reflect process behavior observed in reality,
such as simultaneous execution of activities. Process executions comprising
partially ordered activities may contain more complex activity patterns than
sequence-based process executions. This paper presents a novel query language
to call up process executions from event logs containing partially ordered
activities. The query language allows users to specify complex ordering
relations over activities, i.e., control flow constraints. Evaluating a query
for a given log returns process executions satisfying the specified
constraints. We demonstrate the implementation of the query language in a
process mining tool and evaluate its performance on real-life event logs.
