SeaFlows – A Compliance Checking Framework for Supporting the Process Lifecycle

Compliance-awareness is undoubtedly of utmost importance for companies nowadays. Even though an automated approach to compliance checking and enforcement has been advocated in recent literature as a means to tame the high costs for compliance-awareness, the potential of automated mechanisms for supporting business process compliance is not yet depleted. Business process compliance deals with the question whether business processes are designed and executed in harmony with imposed regulations. In this thesis, we propose a compliance checking framework for automating business process compliance verification within process management systems (PrMSs). Such process-aware information systems constitute an ideal environment for the systematic integration of automated business process compliance checking since they bring together different perspectives on a business process and provide access to process data. The objective of this thesis is to devise a framework that enhances PrMSs with compliance checking functionality.
As PrMSs enable both the design and the execution of business processes, the designated compliance checking framework must accommodate mechanisms to support these different phases of the process lifecycle.
A compliance checking framework essentially consists of two major building blocks: a compliance rule language to capture compliance requirements in a checkable manner and compliance checking mechanisms for verification of process models and process instances. Key to the practical application of a compliance checking framework will be its ability to provide comprehensive and meaningful compliance diagnoses.
Based on the requirements analysis and meta-analyses, we developed the SeaFlows compliance checking framework proposed in this thesis. We introduce the compliance rule graph (CRG) language for modeling declarative compliance rules. The language provides modeling primitives with a notation based on nodes and edges. A compliance rule is modeled by defining a pattern of activity executions activating a compliance rule and consequences that have to apply once a rule becomes activated.
In order to enable compliance verification of process models and process instances, the CRG language is operationalized.
Key to this approach is the exploitation of the graph structure of CRGs for representing compliance states of the respective CRGs in a transparent and interpretable manner. For that purpose, we introduce execution states to mark CRG nodes in order to indicate which parts of the CRG patterns can be observed in a process execution. By providing rules to alter the markings when a new event is processed, we enable to update the compliance state for each observed event.
The beauty of our approach is that both design and runtime can be supported using the same mechanisms. Thus, no transformation of compliance rules in different representations for process model verification or for compliance monitoring becomes necessary. At design time, the proposed approach can be applied to explore a process model and to detect which compliance states with respect to imposed CRGs a process model is able to yield. At runtime, the effective compliance state of process instances can be monitored taking also the future predefined in the underlying process model into account. As compliance states are encoded based on the CRG structure, fine-grained and intelligible compliance diagnoses can be derived in each detected compliance state. Specifically, it becomes possible to provide feedback not only on the general enforcement of a compliance rule but also at the level of particular activations of the rule contained in a process.
In case of compliance violations, this can explain and pinpoint the source of violations in a process. In addition, measures to satisfy a compliance rule can be easily derived that can be seized for providing proactive support to comply.
Altogether, the SeaFlows compliance checking framework proposed in this thesis can be embedded into an overall integrated compliance management framework.