Automating data exchange in process choreographies

Meyer, Andreas; Pufahl, Luise; Batoulis, Kimon; Fahland, Dirk; Weske, Mathias

doi:10.1016/j.is.2015.03.008

Cited by 34 publications

(24 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Another related work is about data modeling in BPC. The authors of [19] emphasize automating data exchange between processes use messages. Furthermore, Hahn et al [11] introduce TraDE to improve the flexibility of data modeling, supporting data exchange and runtime data change across processes.…”

Section: B Detecting Data Flow Errors In Bpcmentioning

confidence: 99%

Detecting Data Flow Errors Across Processes in Business Process Collaboration

Xiong

Pan

et al. 2020

IEEE Access

View full text Add to dashboard Cite

In business process collaboration (BPC), especially when it comes to message communication and data exchange, there are complex data dependencies among sender process, receiver process and messages. However, each participant of the overall BPC develops its part independently as a service, including its own communication part and data flow. As a result, data flow errors across processes may occur easily. In this paper, we propose a method based on BPMN to detect these errors caused by data dependency violations. Our method is inspired by the study of detecting data flow errors within a single process and focuses on a subset of the elements of the BPC model, without having to consider the complete set. In particular, we define a set of data flow error patterns by analyzing and formalizing data dependencies in order to clearly clarify and identify errors. Then we give the corresponding automatic detection algorithm. Finally, through two evaluations, we demonstrate the effectiveness of our proposal. INDEX TERMS Business process management, business process collaboration, data flow error across processes, data dependency.

show abstract

Section: B Detecting Data Flow Errors In Bpcmentioning

confidence: 99%

Detecting Data Flow Errors Across Processes in Business Process Collaboration

Xiong

Pan

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…To this end attribute labels and types, also the relationship between objects (e.g. foreign keys) can be used [42][43][44][45]. Adding these features to the proposed method can provide a complete framework for calculating the similarity of processes.…”

Section: Future Workmentioning

confidence: 99%

Data‐driven business process similarity

Amiri

Koupaee

2017

IET softw.

View full text Add to dashboard Cite

Although measuring the similarity of business processes based on activity labels, structural and behavioural factors can be effective, defining inexact and incomplete labels and the existence of multiple labels for similar activities cause challenges for determining similar processes. Recent attempts to consider data in business process management and the support of data modelling in business process standards have led to the creation of multiple business models with data access. In this study, a method considering data for measuring business process similarity is presented in which first the similarity of activities is measured according to their structures and behaviours in a process and also their data access. Then based on the similarity of activities, the similarity of processes is determined using the proposed algorithm.

show abstract

“…Li et al [25] use SOA-based collaborative models and collaborative agents to solve problems with collaborative management for service convergence under the condition of process and data fragmentation. Meyer et al [28] describe an entirely model-driven approach for BPMN by introducing a few concepts that model data retrieval, data transformation, message exchange, which are the four aspects of data exchange.…”

Section: Related Workmentioning

confidence: 99%

Collaborative process cartography deduction based on collaborative ontology and model transformation

Bénaben

Pingaud

2016

Information Sciences

View full text Add to dashboard Cite

With an increasing background in inter-enterprise collaboration and interoperability, the automatic deduction of collaborative business processes is increasingly being viewed as a crucial research subject. The common solution is believed to involve either semantic ontologies or metamodeling, which can be combined with semantic algorithms or transformation rules. However, from the viewpoint of enterprises, the modeling of collaborative processes should be software integrated and can be changed to workflow. The design of the targeted collaborative process model does not fit the need. This has led to a lack of concepts and transformation rules for the ontology or metamodel. In this paper, a new collaborative process model called collaborative process cartography is designed. Related collaborative ontology and its knowledge-expanding rules have also been updated. Collaborative ontology contains essential concepts for the collaborative situation and includes the rules and algorithms for process deduction. A prototype for the supporting tools is also provided.

show abstract

Automating data exchange in process choreographies

Cited by 34 publications

References 54 publications

Detecting Data Flow Errors Across Processes in Business Process Collaboration

Detecting Data Flow Errors Across Processes in Business Process Collaboration

Data‐driven business process similarity

Collaborative process cartography deduction based on collaborative ontology and model transformation

Contact Info

Product

Resources

About