  Processes tend to interact with other processes and operate on various
objects of different types. These objects can influence each other creating
dependencies between sub-processes. Analyzing the conformance of such complex
processes challenges traditional conformance-checking approaches because they
assume a single-case identifier for a process. To create a single-case
identifier one has to flatten complex processes. This leads to information loss
when separating the processes that interact on some objects. This paper
introduces an alignment approach that operates directly on these object-centric
processes. We introduce alignments that can give behavior-based insights into
how closely related the event data generated by a process and the behavior
specified by an object-centric Petri net are. The contributions of this paper
include a definition for object-centric alignments, an algorithm to compute
them, a publicly available implementation, and a qualitative and quantitative
evaluation. The qualitative evaluation shows that object-centric alignments can
give better insights into object-centric processes because they correctly
consider inter-object dependencies. Findings from the quantitative evaluation
show that the run-time grows exponentially with the number of objects, the
length of the process execution, and the cost of the alignment. The evaluation
results motivate future research to improve the run-time and make
object-centric alignments more applicable for larger processes.
