  The meet up between data, processes and structural knowledge in modeling
enterprise systems is a challenging task that has led to the study of combining
formalisms from knowledge representation, database theory, and process
management. To ensure system correctness, formal verification also comes into
play and offers well-established techniques. In line with this, significant
results have been obtained within the research on data-aware business processes
(DABP), which studies the marriage between static and dynamic aspects of a
system within a unified framework.
  Here, we investigate the verification of DABP in the presence of ontologies,
and provide the following contributions: (1) We propose a formal framework
called Golog-KABs (GKABs), by leveraging on the state of the art formalisms for
DABP equipped with ontologies. GKABs enable us to specify semantically-rich
DABP, where the system dynamics are specified using a high-level action
language inspired by the Golog programming language. (2) We propose a
parametric execution semantics for GKABs that is able to elegantly accommodate
a plethora of inconsistency-aware semantics based on the well-known notion of
repair, and this leads us to several variants of inconsistency-aware GKABs. (3)
We enhance GKABs towards context-sensitive GKABs. (4) We introduce the
so-called Alternating-GKABs that allow for a more fine-grained analysis over
the systems. (5) We introduce a novel framework called Semantically-Enhanced
Data-Aware Processes (SEDAPs) that, by utilizing ontologies, enable us to have
a high-level conceptual view over the evolution of the underlying system.
  We also provide reductions for the verification of sophisticated first-order
temporal properties over all of the settings above, and show that verification
can be addressed using existing techniques developed for Data-Centric Dynamic
Systems (a well-established DABP framework).
