Abstract
During the last two decades, increasing attention has been given to the challenging problem of resolving the dichotomy between business process management and master data management. A substantial number of foundational results has been produced towards the formalisation and verification of data-aware business processes. Unfortunately, with few notable exceptions, such results never had a concrete impact in practice. As a consequence, contemporary process-management systems still lack suitable conceptual abstractions for data management, and do not consider data in the context of process verification.
In this thesis work we advance the state of the art in data-aware business process management We create a bridge between foundational frameworks data-aware processes, and corresponding models that are closer to actual systems and implementations. We do so by considering both data-centric and process-centric modelling styles. As for data-centric approaches, we evolve the framework of data-centric dynamic systems into an actual instantiation and implementation that supports at once modelling, enactment, and verification on top of standard relational technology. As for process-centric approaches, we consider the framework of Petri nets with name creation and management, and establish novel results related to conceptual modelling and verification. Finally, we propose DB-nets, a new formal approach that suitably balances such contrasting modelling styles through the marriage of colored Petri nets and relational databases.