Business process management employs process models and event logs to represent the behavior of the information systems under study. Traditional case-centric notions consider the order of activities and events in isolated process instances. The emerging field of object-centric processes challenges this assumption by putting objects in the center. Object-centric process mining and modeling approaches identify the structure of co-evolving data objects that influence the behavior of an information system to provide a comprehensive view of the system behavior. Object-centricity has been investigated independently in process modeling and in process mining, which resulted in the coexistence of seemingly contradictory assumptions and definitions. As a community effort, this research manifesto relates and aligns existing terminologies, definitions, and perspectives to provide a common ground for current and future research in object-centric business process management. Based on the current state of research, we propose a conceptualization that sets process models and event logs in relation to the information system’s behavior and the execution data it generates. The conceptualization aims at aligning different terminologies and, thus, providing a basis to model and analyze behavioral characteristics. Building on this common ground, we identify open research challenges along the most relevant research areas in object-centric process management. For each research area, its current status is investigated and an outline of the most relevant research challenges is presented.

The current push towards interoperability drives companies to collaborate through process choreographies. At the same time, they face a jungle of continuously changing regulations, e.g., due to the pandemic and developments such as the BREXIT, which strongly affect cross-organizational collaborations. Think of, for example, supply chains spanning several countries with different and maybe even conflicting COVID19 traveling restrictions. Hence, providing automatic compliance verification in process choreographies is crucial for any cross-organizational business process. A particular challenge concerns the restricted visibility of the partner processes at the presence of global compliance rules (GCR), i.e., rules that span across the process of several partners. This work deals with the question how to verify global compliance if affected tasks are not fully visible. Our idea is to decompose GCRs into so called assertions that can be checked by each affected partner whereby the decomposition is both correct and lossless. The algorithm exploits transitivity properties of the underlying rule specification, and its correctness and complexity are proven, considering advanced aspects such as loops. The algorithm is implemented in a proof-of-concept prototype, including a model checker for verifying compliance. The applicability of the approach is further demonstrated on a real-world manufacturing use case.

Contemporary process management systems support users during the execution of predefined business processes. However, when unforeseen situations occur, which are not part of the process model serving as the template for process execution, contemporary technology is often unable to offer adequate user support. One solution to this problem is to allow for ad-hoc changes to process models, i.e., changes that may be applied on the fly to a running process instance. As opposed to the widespread activity-centric process modeling paradigm, for which the support of instance-specific ad-hoc changes is well researched, albeit not properly supported by most commercial process engines, there is no corresponding support for ad-hoc changes in other process support paradigms, such as artifact-centric or object-aware process management. This article presents concepts for supporting ad-hoc changes in data-centric and data-driven processes, and gives insights into the challenges to be tackled when implementing this kind of process flexibility in the PHILharmonicFlows process execution engine. We evaluated the concepts by implementing a proof-of-concept prototype and applying it to various scenarios. The development of advanced flexibility features is highly relevant for data-centric processes, as the research field is generally perceived as having low maturity compared to activity-centric processes.

The proper management of privacy and security constraints in information systems in general and access control in particular constitutes a tremendous, but still prevalent challenge. Role-based access control (RBAC) and its variations can be considered as the widely adopted approach to realize authorization in information systems. However, RBAC lacks a proper object-specific support, which disallows establishing the fine-grained access control required in many domains. By comparison, attribute-based access control (ABAC) enables a fine-grained access control based on policies and rules evaluating attributes. As a drawback, ABAC lacks the abstraction of roles. Moreover, it is challenging to engineer and to audit the granted privileges encoded in rule-based policies. This paper presents the generic approach of object-specific role-based access control (ORAC). On one hand, ORAC enables information system engineers, administrators and users to utilize the well-known principle of roles. On the other hand, ORAC allows realizing the access to objects in a fine-grained way where required. The approach was systematically established according to well-elicited key requirements for fine-grained access control in information systems. For the purpose of evaluation, the approach was applied to real-world scenarios and implemented in a proof-of-concept prototype demonstrating its feasibility and applicability.

Enabling process changes constitutes a major challenge for any process-aware information system. This not only holds for processes running within a single enterprise, but also for collaborative scenarios involving distributed and autonomous partners. In particular, if one partner adapts its private process, the change might affect the processes of the other partners as well. Accordingly, it might have to be propagated to concerned partners in a transitive way. A fundamental challenge in this context is to find ways of propagating the changes in a decentralized manner. Existing approaches are limited with respect to the change operations considered as well as their dependency on a particular process specification language. This paper presents a generic change propagation approach that is based on the Refined Process Structure Tree, i.e., the approach is independent of a specific process specification language. Further, it considers a comprehensive set of change patterns. For all these change patterns, it is shown that the provided change propagation algorithms preserve consistency and compatibility of the process choreography. Finally, a proof-of-concept prototype of a change propagation framework for process choreographies is presented. Overall, comprehensive change support in process choreographies will foster the implementation and operational support of agile collaborative process scenarios.

Knowledge workers are confronted with a massive load of data from numerous heterogeneous sources, making it difficult for them to identify the information relevant for performing their tasks. Particularly challenging is the alignment of information with business processes. In previous work, we introduced a Semantic Network (SN) for bridging this gap, i.e., for identifying relations between information and business processes. What has been neglected so far is the maintenance of an SN in order to keep the SN consistent, complete, and up-to-date. This paper tackles this issue and extends our approach with algorithms dealing with the maintenance of an SN. For this purpose, we identify and classify properties of objects and relations captured in an SN and show how these properties can be maintained. We use a case from the automotive domain in order to demonstrate and validate the feasibility and applicability of our maintenance framework.

The diversity and quantity of medical information emerging from patient treatment makes it a challenging task for medical staff to identify and handle the information they need to perform their tasks in the best possible way. The doctor's ward round, for example, is a knowledge-intensive process comprising complex information-centric tasks such as patient examination and diagnosis. Goal is to provide medical staff with relevant information dependent on their work context. This paper picks up this challenge and presents iCare, a semantic application enabling an intelligent integration, analysis, and delivery of personalized medical information.

During the last years a new generation of adaptive Process-Aware Information Systems (PAIS) has emerged, which enables dynamic process changes at runtime, while preserving PAIS robustness and consistency. Such adaptive PAIS allow authorized users to add new process activities, to delete existing activities, or to change pre-defined activity sequences during runtime. Both this runtime flexibility and process configurations at build-time, lead to a large number of process variants being derived from the same process model, but slightly differing in structure due to the applied changes. Generally, process variants are expensive to configure and difficult to maintain. This paper presents selected results from our MinAdept project. In particular, we provide a clustering algorithm that fosters learning from past process changes by mining a collection of process variants. As mining result we obtain a process model for which average distance to the process variant models becomes minimal. By adopting this process model as reference model in the PAIS, need for future process configuration and adaptation decreases. We have validated our clustering algorithm by means of a case study as well as comprehensive simulations. Altogether, our vision is to enable full process lifecycle support in adaptive PAIS.

The need for more flexibility of process-aware information systems (PAISs) has been discussed for several years and different approaches for adaptive process management have emerged. However, only few of them provide support for both changes of individual process instances and the propagation of process type changes to a collection of related process instances. Furthermore, knowledge about process changes has not yet been exploited by any of these systems. This paper presents the ProCycle approach which overcomes this practical limitation by capturing the whole process life cycle and all kinds of changes in an integrated way. Users are not only allowed to deviate from the predefined process in exceptional situations, but are also assisted in retrieving and reusing knowledge about previously performed changes in this context. If similar instance deviations occur frequently, process engineers will be supported in deriving improved process models from them. This, in turn, allows engineers to evolve the PAIS (including the knowledge about the changes) over time. Feasability of the ProCycle approach is demonstrated by a proof-of-concept prototype which combines adaptive process management technology with concepts and methods provided by case-based reasoning (CBR) technology.

Process-aware information systems have to be frequently adapted due to business process changes. One important challenge not adequately addressed so far concerns the evolution of process choreographies. If respective modifications are applied in an uncontrolled manner, inconsistencies or errors might occur in the sequel. In particular, modifications of private processes performed by a single party may affect the implementation of the private processes of partners as well. In this paper we sketch a framework that allows process engineers to detect how changes of private processes may affect related public views and - if so - how they can be propagated to the public and private processes of partners. Our approach exploits the semantics of the applied changes in order to automatically determine the adaptations necessary for the partner processes.

In the ADEPT project we have been working on the design and implementation of next generation process management software. Based on a conceptual framework for dynamic process changes, on novel process support functions, and on advanced implementation concepts, the developed system enables the realization of adaptive, process-aware information systems (PAIS). Basically, process changes can take place at the type as well as the instance level: changes of single process instances may have to be carried out in an ad-hoc manner and must not affect system robustness and consistency. Process type changes, in turn, must be quickly accomplished in order to adapt the PAIS to business process changes. ADEPT2 offers powerful concepts for modeling, analyzing, and verifying process schemes. Particularly, it ensures schema correctness, like the absence of deadlock-causing cycles or erroneous data flows. This, in turn, constitutes an important prerequisite for dynamic process changes as well. ADEPT2 supports both ad-hoc changes of single process instances and the propagation of process type changes to running instances.

For enterprise-wide and cross-organizational process-oriented applications, the execution of workflows (WF) may generate a very high load. This load may affect WF servers as well as the underlying communication network. To improve system scalability, several approaches for distributed WF management have been proposed in the literature. They have in common that different partitions of a WF instance graph may be controlled by different WF servers from different subnets. The control over a particular WF instance, therefore, may be transferred from one WF server to another during run-time if this helps to reduce the overall communication load. Thus far, such distributed approaches assume that exactly one WF server resides in each subnet. A single server per subnet, however, may become overloaded. In this paper, we present and verify a novel approach for replicating WF servers in a distributed workflow management system. It enables an arbitrary and changeable distribution of the load to the WF servers of the same subnet, without requiring additional communication.