1,721,129 research outputs found
Managing variability in process-aware information systems
No full textConfigurable process models are integrated representations of multiple variants of a process model in a given domain, e.g. multiple variants of a shipment-to-delivery process in the logistics domain. Configurable process models provide a basis for managing variability and for enabling reuse of process models in Process-Aware Information Systems. Rather than designing process models from scratch, analysts can derive process models by configuring existing ones, thereby reusing proven practices. This thesis starts with the observation that existing approaches for capturing and managing configurable process models suffer from three shortcomings that affect their usability in practice. Firstly, configuration in existing approaches is performed manually and as such it is error-prone. In particular, analysts are left with the burden of ensuring the correctness of the individualized models. Secondly, existing approaches suffer from a lack of decision support for the selection of configuration alternatives. Consequently, stakeholders involved in the configuration of process models need to possess expertise both in the application domain and in the modeling language employed. This assumption represents an adoption obstacle in domains where users are unfamiliar with modeling notations. Finally, existing approaches for configurable process modeling are limited in scope to control-flow aspects, ignoring other equally important aspects of process models such as object flow and resource management. Following a design science research method, this thesis addresses the above shortcomings by proposing an integrated framework to manage the configuration of process models. The framework is grounded on three original and interrelated contributions: (i) a conceptual foundation for correctness-preserving configuration of process models; (ii) a questionnaire-driven approach for process model configuration, providing decision support and abstraction from modeling notations; (iii) a meta-model for configurable process models covering control-flow, data objects and resources. While the framework is language-independent, an embodiment of the framework in the context of a process modeling language used in practice is also developed in this thesis. The framework was formally defined and validated using four scenarios taken from different domains. Moreover, a comprehensive toolset was implemented to support the validation of the framework
Special issue: Selected papers of ICPM 2019
No full textThis editorial is the foreword of a special issue I guest edited
Configurable Process Models: How To Adopt Standard Practices In Your How Way?
No full textConfigurable process models enable a systematic documentation and reuse of standardized "best" practices, while allowing process analysts to understand possible variations contemplated by these standards, and to link these variations to business decisions. This article discusses the potential benefits of configurable process models and introduces a method and a toolset for process design based on configurable process models
Managing Process Model Complexity - Part I: Concrete Syntax
No full textWhile Business Process Management (BPM) is an established\ud
discipline, the increased adoption of BPM technology in recent years has introduced new challenges. One challenge concerns dealing with process model complexity in order to improve the understanding of a process model by stakeholders and process analysts. Features for dealing with this complexity can be classified in two categories: 1) those that are solely concerned with the appearance of the model, and 2) those that in essence change the structure of the model. In this paper we focus on the former category and present a collection of patterns that generalize and conceptualize various existing features. The paper concludes with a detailed analysis of the degree of support of a number of state-of-the-art languages and language implementations for these patterns
Noise Filtering of Process Execution Logs based on Outliers Detection
No full textThis paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs
Discovering Local Concurrency Relations in Business Process Event Logs
No full text<i>Detecting concurrency relations between events is a fundamental primitive in process mining. Existing approaches to this problem identify concurrency relations between pairs of event types under a global interpretation. If two event types are found to be concurrent, every occurrence of one event type is deemed to be concurrent to one occurrence of the other. In practice, this assumption not always holds. This paper proposes a finer-grained approach, whereby two event types may be in a concurrency relation relative to one state of the process, but not relative to other states, i.e. the concurrency relation holds locally. Experimental results both with artificial and real-life logs show that the proposed local concurrency detection approach improves the accuracy of existing concurrency detection techniques.</i
Local concurrency detection in business process event logs
No full textDetecting concurrency relations between events is a fundamental primitive underpinning a range of process mining techniques. Existing approaches to this problem identify concurrency relations at the level of event types under a global interpretation. If two event types are declared to be concurrent, every occurrence of one event type is deemed to be concurrent to one occurrence of the other. In practice, this interpretation is too coarse-grained and leads to over-generalization. This paper proposes a finer-grained approach, whereby two event types may be deemed to be in a concurrency relation relative to one state of the process, but not relative to other states. In other words, the detected concurrency relation holds locally, relative to a set of states. Experimental results both with artificial and real-life logs show that the proposed local concurrency detection approach improves the accuracy of existing concurrency detection techniques
Modelling Business Process Variability
No full textA reference process model represents multiple variants of a common business process in an inte-grated and reusable manner. It is intended to be individualized in order to fit the requirements of a specific organization or project. This practice of individualizing reference process models provides an attractive alternative with respect to designing process models from scratch. In particular, it en-ables the reuse of proven practices. This chapter introduces techniques for representing variability in the context of reference process models, as well as techniques that facilitate the individualization of reference process model with respect to a given set of requirements
Correctness of Business Process Models with Roles and Objects
No full textThe verification of business process models is an important step in the design phase\ud
of process-aware information systems. While a process model often describes different\ud
perspectives like control flow, object flow, and role assignment, most of the\ud
contributions in the areas of verification consider only the control flow. Hardly any\ud
work considers these three perspectives in a combined verification approach. In this\ud
paper we address this gap and introduce Integrated EPCs (iEPCs), a business process\ud
modeling language that extends EPCs with a concept of object flow and role\ud
assignment. By abstracting from the subtle differences of recent EPC semantics definitions, we show how any of these formalizations can be enhanced with transition\ud
rules that consider object existence and role availability as part of the state concept.\ud
Furthermore, we define three theorems that relate soundness of EPCs to soundness\ud
of iEPCs with different initial role and object set. These theorems provide the basis\ud
for a systematic verification approach of iEPCs that first identifies control-flow\ud
problems, then object-flow problems, and finally suitable role subsets. This way, our\ud
work contributes to a better identification of correctness issues already in conceptual\ud
process models in the early design phases
- …
