IUPC: Identification and Unification of Process Constraints

Business Process Compliance (BPC) has gained significant momentum in research and practice during the last years. Although many approaches address BPC, they mostly assume the existence of some kind of unified base of process constraints and focus on their verification over the business processes. However, it remains unclear how such an inte- grated process constraint base can be built up, even though this con- stitutes the essential prerequisite for all further compliance checks. In addition, the heterogeneity of process constraints has been neglected so far. Without identification and separation of process constraints from domain rules as well as unification of process constraints, the success- ful IT support of BPC will not be possible. In this technical report we introduce a unified representation framework that enables the identifica- tion of process constraints from domain rules and their later unification within a process constraint base. Separating process constraints from domain rules can lead to significant reduction of compliance checking effort. Unification enables consistency checks and optimizations as well as maintenance and evolution of the constraint base on the other side.Comment: 13 pages, 4 figures, technical repor

Data Flow Correctness in Adaptive Workflow Systems

Enterprises must be able to quickly adapt their business processes to react to changes in their environment. Needed business agility is often hindered by the lacking flexibility of contemporary workflow systems. In response to this inflexibility, adaptive workflow systems have emerged, which enable the dynamic adaptation of running workflows. One of the most important challenges in this context is to avoid inconsistencies and errors. So far, approaches providing respective correctness criteria for dynamic workflow change have mainly focused on control flow correctness (e.g., avoidance of deadlocks). However, little attention has been paid to data flow correctness even though this is crucial for any application of dynamic workflow change in practice. Specifically, missing or inconsistent input data of workflow activities, for example, can lead to blocking or breakdown of the underlying workflow system. This paper deals with fundamental challenges related to data flow correctness. We revisit and discuss data flow correctness at different phases of the workflow life cycle (i.e., buildtime and runtime), and show how data flow correctness can be ensured in an efficient way when dynamically changing a workflow

Cloud Process Execution Engine: Architecture and Interfaces

Process Execution Engines are a vital part of Business Process Management (BPM) and Manufacturing Orchestration Management (MOM), as they allow the business or manufacturing logic (expressed in a graphical notation such as BPMN) to be executed. This execution drives and supervises all interactions between humans, machines, software, and the environment. If done right, this will lead to a highly flexible, low-code, and easy to maintain solution, that allows for ad-hoc changes and functional evolution, as well as delivering a wealth of data for data-science applications. The Cloud Process Execution Engine CPEE.org implements a radically distributed scale-out architecture, together with a minimal set of interfaces, to allow for the simplest possible integration with existing services, machines, and existing data-analysis tools. Its open-source components can serve as a blueprint for future development of commercial solutions, and serves as a proven testbed for academic research, teaching, and industrial application since 2008. In this paper we present the architecture, interfaces that make CPEE.org possible, as well as discuss different lifecycle models utilized during execution to provide overarching support for a wide range of data-analysis tasks.Comment: 30 pages, 12 figures, 2 illustration

Collection and Elicitation of Business Process Compliance Patterns with Focus on Data Aspects

Business process compliance is one of the prevalent challenges for companies. Despite an abundance of research proposals, companies still struggle with manual compliance checks and the understanding of compliance violations in the light of missing root-cause explanations. Moreover, approaches have merely focused on the control flow perspective in compliance checking, neglecting other aspects such as the data perspective. This paper aims at analyzing the gap between existing academic work and compliance demands from practice with a focus on the data aspects. The latter emerges from a small set of regulatory documents from different domains. Patterns are assumed as the right level of abstraction for compliance specification due to their independence of (technical) implementation in (process-aware) information systems, potential for reuse, and understandability. A systematic literature review collects and assesses existing compliance patterns. A first analysis of ten regulatory documents from different domains specifically reveals data-oriented compliance constraints that are not yet reflected by existing compliance patterns. Accordingly, data-related compliance patterns are specified