Kevin Andrews

Coordinating Business Processes Using Semantic Relationships

In enterprises, different business processes collaborate to achieve a common business goal. The processes involved in such a collaboration are connected to each other in one-to-one, one-to-many, and many-to-many relationships. The complex interdependencies between these processes require proper process coordination. Current approaches addressing process coordination rely on message exchanges between the interacting processes with focus on syntax, while neglecting the semantics of these message exchanges between multiple processes. This paper introduces semantic relationships, a concept that provides the means to model process coordination based on message semantics, resulting in a high level of abstraction and thus facilitating process coordination. Semantic relationships incorporate the support for one-to-many and many-to-many process relations and affect process execution solely if required, allowing for concurrent and asynchronous process execution.

The Relational Process Structure

Using data-centric process paradigms, small processes such as artifacts, object lifecycles, or Proclets have become an alternative to large, monolithic models. In these paradigms, a business process arises from the interactions between small processes. However, many-to-many relationships may exist between different process types, requiring careful consideration to ensure that the interactions between processes can be purposefully coordinated. Although several concepts exist for modeling interrelated processes, a concept that considers both many-to-many relationships and cardinality constraints is missing. Furthermore, existing concepts focus on design-time, neglecting the complexity introduced by many-to-many relationships when enacting extensive process structures at run-time. The knowledge which process instances are related to which other process instances is essential. This paper proposes the relational process structure, a concept providing full support for many-to-many-relationships and cardinality constraints at both design- and run-time. The relational process structure represents a cornerstone to the proper coordination of interrelated processes.

Data in Business Process Models, A Preliminary Empirical Study (Short Paper)

Traditional activity-centric process modeling languages treat data as simple black boxes acting as input or output for activities. Many alternate and emerging process modeling paradigms, such as case handling and artifact-centric process modeling, give data a more central role. This is achieved by introducing lifecycles and states for data objects, which is beneficial when modeling data-or knowledge-intensive processes. We assume that traditional activity-centric process modeling languages lack the capabilities to adequately capture the complexity of such processes. To verify this assumption we conducted an online interview among BPM experts. The results not only allow us to identify various profiles of persons modeling business processes, but also the problems that exist in contemporary modeling languages w.r.t. The modeling of business data. Overall, this preliminary empirical study confirms the necessity of data-awareness in process modeling notations in general.

Automation of Intralogistic Processes through Flexibilisation - A method for the flexible configuration and evaluation of systems of systems

The high system flexibility necessary for the full automation of complex and unstructured tasks leads to increased technological complexity, thus to higher costs and lower performance. In this paper, after an introduction to the different dimensions of flexibility, a method for flexible modular configuration and evaluation of systems of systems is introduced. The method starts from process requirements and, considering factors such as feasibility, development costs, market potential and effective impact on the current processes, enables the evaluation of a flexible systems of systems equipped with the needed functionalities before its actual development. This allows setting the focus on those aspects of flexibility that add market value to the system, thus promoting the efficient development of systems addressed to interested customers in intralogistics. An example of application of the method is given and discussed.

Enabling Process Variants and Versions in Distributed Object-Aware Process Management Systems

Business process variants are common in many enterprises and properly managing them is indispensable. Some process management suites already offer features to tackle the challenges of creating and updating multiple variants of a process. As opposed to the widespread activity-centric process modeling paradigm, however, there is little to no support for process variants in other process support paradigms, such as the recently proposed artifact-centric or object-aware process support paradigm. This paper presents concepts for supporting process variants in the object-aware process management paradigm. We offer insights into the distributed object-aware process management framework PHILharmonicFlows as well as the concepts it provides for implementing variants and versioning support based on log propagation and log replay. Finally, we examine the challenges that arise from the support of process variants and show how we solved these, thereby enabling future research into related fundamental aspects to further raise the maturity level of data-centric process support paradigms.

DALEC: a framework for the systematic evaluation of data-centric approaches to process management software

The increasing importance of data in business processes has led to the emergence of data-centric business process management, which deviates from the widely used activity-centric paradigm. Data-centric approaches set their focus on data, aiming at supporting data-intensive business processes and increased process flexibility. The objective of this article is to gain profound insights into the maturity of different data-centric approaches as well as their capabilities. In particular, this article will provide a framework for systematically evaluating and comparing data-centric approaches, with regard to the phases of the business process lifecycle. To this end, a systematic literature review (SLR) was conducted with the goal of evaluating the capabilities of data-centric process management approaches. The SLR comprises 38 primary studies which were thoroughly analyzed. The studies were categorized into different approaches, whose capabilities were thoroughly assessed. Special focus was put on the tooling and software of the approaches. The article provides the empirically grounded DALEC framework to evaluate and compare data-centric approaches. Furthermore, the results of the SLR offer insights into existing data-centric approaches and their capabilities. Data-centric approaches promise better support of loosely structured and data-intensive business processes, which may not be adequately represented by activity-centric paradigms.

A Smart Mobile Assessment Tool for Collecting Data in Large-Scale Educational Studies.

Abstract Conducting scientific studies is an often frustrating and tedious task. To minimize recurring problems, such as lack of concentration or willingness to participate, and instead promote interest in the study, a smart mobile device assessment tool was developed focusing on educational studies. The tablet-based assessment tool offers a wide range of visual tasks that can be employed when conducting studies utilizing the European Framework of Visual Literacy (ENViL). Furthermore, the assessment tool is highly configurable in the field by using a centralized server and spreadsheet-based configuration files, thereby ensuring that no programming language is required to adapt the tasks on the mobile devices participating in the study. Finally, the presented framework and architecture adhere to the cross-platform and cross-device style and can be re-used and extended for any number of similar studies.

Modeling Process Interactions with Coordination Processes

With the rise of data-centric process management paradigms, small and interdependent processes, such as artifacts or object lifecycles, form a business process by interacting with each other. To arrive at a meaningful overall business process, these process interactions must be coordinated. One challenge is the proper consideration of one-to-many and many-to-many relations between interacting processes. Other challenges arise from the flexible, concurrent execution of the processes. Relational process structures and semantic relationships have been proposed for tackling these individual challenges. This paper introduces coordination processes, which bring together both relational process structures and semantic relationships, leveraging their features to enable proper coordination support for interdependent, concurrently running processes. Coordination processes contribute an abstracted and concise model for coordinating the highly complex interactions of interrelated processes.

Engineering a Highly Scalable Object-Aware Process Management Engine Using Distributed Microservices

Scalability of information systems has been a research topic for many years and is as relevant as ever with the dramatic increases in digitization of business processes and data. This also applies to process-aware information systems, most of which are currently incapable of scaling horizontally, i.e., over multiple servers. This paper presents the design science artifact that resulted from engineering a highly scalable process management system relying on the object-aware process management paradigm. The latter allows for distributed process execution by conceptually encapsulating process logic and data into multiple interacting objects that may be processed concurrently. These objects, in turn, are represented by individual microservices at run-time, which can be hosted transparently across entire server clusters. We present measurement data that evaluates the scalability of the artifact on a compute cluster, demonstrating that the current prototypical implementation of the run-time engine can handle very large numbers of users and process instances concurrently in single-case mechanism experiments with large amounts of simulated user input. Finally, the development of scalable process execution engines will further the continued maturation of the data-centric business process management field.

Enabling Fine-Grained Access Control in Flexible Distributed Object-Aware Process Management Systems

To increase flexibility, object-aware process management systems enable data-driven process execution and dynamic generation of form-based tasks at run-time. Therefore, a powerful access control concept becomes necessary to define which data elements users may read or write at a given point in time during process execution. The access control concept we present in this paper has been realized in the context of the PHILharmonicFlows framework, which provides a distributed data-driven process execution engine. We present solutions that allow for complex as well as fine-grained permissions and roles, which are granted depending on the states of processes and data elements. We show how one can resolve authorization queries in real-time over multiple business objects and process instances. This constitutes a significant advantage over centralized access control systems.