scholarly journals Artifact Lifecycle Discovery

2015 ◽  
Vol 24 (01) ◽  
pp. 1550001 ◽  
Author(s):  
Viara Popova ◽  
Dirk Fahland ◽  
Marlon Dumas

Artifact-centric modeling is an approach for capturing business processes in terms of so-called business artifacts — key entities driving a company's operations and whose lifecycles and interactions define an overall business process. This approach has been shown to be especially suitable in the context of processes where one-to-many or many-to-many relations exist between the entities involved in the process. As a contribution towards building up a body of methods to support artifact-centric modeling, this article presents a method for automated discovery of artifact-centric process models starting from logs consisting of flat collections of event records. We decompose the problem in such a way that a wide range of existing (non-artifact-centric) automated process discovery methods can be reused in a flexible manner. The presented methods are implemented as a package for ProM, a generic open-source framework for process mining. The methods have been applied to reverse-engineer an artifact-centric process model starting from logs of a real-life business process.

Author(s):  
Alessandro Marchetto ◽  
Chiara Di Francescomarino

Web Applications (WAs) have been often used to expose business processes to the users. WA modernization and evolution are complex and time-consuming activities that can be supported by software documentation (e.g., process models). When, as often happens, documentation is missing or is incomplete, documentation recovery and mining represent an important opportunity for reconstructing or completing it. Existing process-mining approaches, however, tend to recover models that are quite complex, rich, and intricate, thus difficult to understand and use for analysts and developers. Model refinement approaches have been presented in the literature to reduce the model complexity and intricateness while preserving the capability of representing the relevant information. In this chapter, the authors summarize approaches to mine first and refine later business process models from existing WAs. In particular, they present two process model refinement approaches: (1) re-modularization and (2) reduction. The authors introduce the techniques and show how to apply them to WAs.


Author(s):  
Yutika Amelia Effendi ◽  
Nania Nuzulita

Background: Nowadays, enterprise computing manages business processes which has grown up rapidly. This situation triggers the production of a massive event log. One type of event log is double timestamp event log. The double timestamp has a start time and complete time of each activity executed in the business process. It also has a close relationship with temporal causal relation. The temporal causal relation is a pattern of event log that occurs from each activity performed in the process.Objective: In this paper, seven types of temporal causal relation between activities were presented as an extended version of relations used in the double timestamp event log. Since the event log was not always executed sequentially, therefore using temporal causal relation, the event log was divided into several small groups to determine the relations of activities and to mine the business process.Methods: In these experiments, the temporal causal relation based on time interval which were presented in Gantt chart also determined whether each case could be classified as sequential or parallel relations. Then to obtain the business process, each temporal causal relation was combined into one business process based on the timestamp of activity in the event log.Results: The experimental results, which were implemented in two real-life event logs, showed that using temporal causal relation and double timestamp event log could discover business process models.Conclusion: Considering the findings, this study concludes that business process models and their sequential and parallel AND, OR, XOR relations can be discovered by using temporal causal relation and double timestamp event log.Keywords:Business Process, Process Discovery, Process Mining, Temporal Causal Relation, Double Timestamp Event Log


Author(s):  
Alessandro Marchetto ◽  
Chiara Di Francescomarino

Web Applications (WAs) have been often used to expose business processes to the users. WA modernization and evolution are complex and time-consuming activities that can be supported by software documentation (e.g., process models). When, as often happens, documentation is missing or is incomplete, documentation recovery and mining represent an important opportunity for reconstructing or completing it. Existing process-mining approaches, however, tend to recover models that are quite complex, rich, and intricate, thus difficult to understand and use for analysts and developers. Model refinement approaches have been presented in the literature to reduce the model complexity and intricateness while preserving the capability of representing the relevant information. In this chapter, the authors summarize approaches to mine first and refine later business process models from existing WAs. In particular, they present two process model refinement approaches: (1) re-modularization and (2) reduction. The authors introduce the techniques and show how to apply them to WAs.


2019 ◽  
Vol 25 (5) ◽  
pp. 995-1019 ◽  
Author(s):  
Anna Kalenkova ◽  
Andrea Burattin ◽  
Massimiliano de Leoni ◽  
Wil van der Aalst ◽  
Alessandro Sperduti

Purpose The purpose of this paper is to demonstrate that process mining techniques can help to discover process models from event logs, using conventional high-level process modeling languages, such as Business Process Model and Notation (BPMN), leveraging their representational bias. Design/methodology/approach The integrated discovery approach presented in this work is aimed to mine: control, data and resource perspectives within one process diagram, and, if possible, construct a hierarchy of subprocesses improving the model readability. The proposed approach is defined as a sequence of steps, performed to discover a model, containing various perspectives and presenting a holistic view of a process. This approach was implemented within an open-source process mining framework called ProM and proved its applicability for the analysis of real-life event logs. Findings This paper shows that the proposed integrated approach can be applied to real-life event logs of information systems from different domains. The multi-perspective process diagrams obtained within the approach are of good quality and better than models discovered using a technique that does not consider hierarchy. Moreover, due to the decomposition methods applied, the proposed approach can deal with large event logs, which cannot be handled by methods that do not use decomposition. Originality/value The paper consolidates various process mining techniques, which were never integrated before and presents a novel approach for the discovery of multi-perspective hierarchical BPMN models. This approach bridges the gap between well-known process mining techniques and a wide range of BPMN-complaint tools.


2019 ◽  
Vol 25 (5) ◽  
pp. 908-922 ◽  
Author(s):  
Remco Dijkman ◽  
Oktay Turetken ◽  
Geoffrey Robert van IJzendoorn ◽  
Meint de Vries

Purpose Business process models describe the way of working in an organization. Typically, business process models distinguish between the normal flow of work and exceptions to that normal flow. However, they often present an idealized view. This means that unexpected exceptions – exceptions that are not modeled in the business process model – can also occur in practice. This has an effect on the efficiency of the organization, because information systems are not developed to handle unexpected exceptions. The purpose of this paper is to study the relation between the occurrence of exceptions and operational performance. Design/methodology/approach The paper does this by analyzing the execution logs of business processes from five organizations, classifying execution paths as normal or exceptional. Subsequently, it analyzes the differences between normal and exceptional paths. Findings The results show that exceptions are related to worse operational performance in terms of a longer throughput time and that unexpected exceptions relate to a stronger increase in throughput time than expected exceptions. Practical implications These findings lead to practical implications on policies that can be followed with respect to exceptions. Most importantly, unexpected exceptions should be avoided by incorporating them into the process – and thus transforming them into expected exceptions – as much as possible. Also, as not all exceptions lead to longer throughput times, continuous improvement should be employed to continuously monitor the occurrence of exceptions and make decisions on their desirability in the process. Originality/value While work exists on analyzing the occurrence of exceptions in business processes, especially in the context of process conformance analysis, to the best of the authors’ knowledge this is the first work that analyzes the possible consequences of such exceptions.


2021 ◽  
Vol 6 (3) ◽  
pp. 170
Author(s):  
Hilman Nuril Hadi

Business process model was created to make it easier for business process stakeholders to communicate and discuss the structure of the process more effectively and efficiently. Business process models can also be business artifacts and media that can be analyzed further to improve and maintain organizational competitiveness. To analyze business processes in a structured manner, the effect/results of the execution of business processes will be one of the important information. The effect/result of the execution of certain activities or a business process as a whole are useful for managing business processes, including for improvements related to future business processes. This effect annotation approach needs to be supported by business process modeling tools to assist business analysts in managing business processes properly. In previous research, the author has developed a plugin that supports business analysts to describe the effects semantically attached to activities in the Business Process Model and Notation (BPMN) business process model. In this paper, the author describes the unit testing process and its results on the plugin of semantic effect annotation that have been developed. Unit testing was carried out using the basic path testing technique and has obtained three test paths. The results of unit test for plugin are also described in this paper.


2021 ◽  
Vol 28 (1) ◽  
pp. 39-46
Author(s):  
Florian Spree

Predictive process monitoring is a subject of growing interest in academic research. As a result, an increased number of papers on this topic have been published. Due to the high complexity in this research area a wide range of different experimental setups and methods have been applied which makes it very difficult to reliably compare research results. This paper's objective is to investigate how business process models and their characteristics are used during experimental setups and how they can contribute to academic research. First, a literature review is conducted to analyze and discuss the awareness of business process models in experimental setups. Secondly, the paper discusses identified research problems and proposes the concept of a web-based business process model metric suite and the idea of ranked metrics. Through a metric suite researchers and practitioners can automatically evaluate business process model characteristics in their future work. Further, a contextualization of metrics by introducing a ranking of characteristics can potentially indicate how the outcome of experimental setups will be. Hence, the paper's work demonstrates the importance of business process models and their characteristics in the context of predictive process monitoring and proposes the concept of a tool approach and ranking to reliably evaluate business process models characteristics.


2014 ◽  
Vol 11 (2) ◽  
pp. 461-480 ◽  
Author(s):  
Nuno Castela ◽  
Paulo Dias ◽  
Marielba Zacarias ◽  
José Tribolet

Business process models are often forgotten after their creation and its representation is not usually updated. This appears to be negative as processes evolve over time. This paper discusses the issue of business process models maintenance through the definition of a collaborative method that creates interaction contexts enabling business actors to discuss about business processes, sharing business knowledge. The collaboration method extends the discussion about existing process representations to all stakeholders promoting their update. This collaborative method contributes to improve business process models, allowing updates based in change proposals and discussions, using a groupware tool that was developed. Four case studies were developed in real organizational environment. We came to the conclusion that the defined method and the developed tool can help organizations to maintain a business process model updated based on the inputs and consequent discussions taken by the organizational actors who participate in the processes.


Author(s):  
Bruna Brandão ◽  
Flávia Santoro ◽  
Leonardo Azevedo

In business process models, elements can be scattered (repeated) within different processes, making it difficult to handle changes, analyze process for improvements, or check crosscutting impacts. These scattered elements are named as Aspects. Similar to the aspect-oriented paradigm in programming languages, in BPM, aspect handling has the goal to modularize the crosscutting concerns spread across the models. This process modularization facilitates the management of the process (reuse, maintenance and understanding). The current approaches for aspect identification are made manually; thus, resulting in the problem of subjectivity and lack of systematization. This paper proposes a method to automatically identify aspects in business process from its event logs. The method is based on mining techniques and it aims to solve the problem of the subjectivity identification made by specialists. The initial results from a preliminary evaluation showed evidences that the method identified correctly the aspects present in the process model.


2020 ◽  
pp. 464-478
Author(s):  
Loubna El Faquih ◽  
Mounia Fredj

In recent years, business process modeling has increasingly drawn the attention of enterprises. As a result of the wide use of business processes, redundancy problems have arisen and researchers introduced the variability management, in order to enhance the business process reuse. The most approach used in this context is the Configurable Process Model solution, which consists in representing the variable and the fixed parts together in a unique model. Due to the increasing number of variants, the configurable models become complex and incomprehensible, and their quality is therefore impacted. Most of research work is limited to the syntactic quality of process variants. The approach presented in this paper aims at providing a novel method towards syntactic verification and semantic validation of configurable process models based on ontology languages. We define validation rules for assessing the quality of configurable process models. An example in the e-healthcare domain illustrates the main steps of our approach.


Sign in / Sign up

Export Citation Format

Share Document