An automated method for the construction of semantic business process patterns

Lobna Makni, Nahla Zaaboub Haddar and Hanêne Ben-Abdallah

International Journal of Process Management and Benchmarking, 2018, vol. 8, issue 3, 263-290

Abstract: The effectiveness of reuse in the development of software prompted researchers to look for reuse techniques for business process modelling. Indeed, a variety of reusable business artefact types has been proposed during the last decade. Among the recently proposed reuse artefact types, semantic business process patterns (SB2Ps) offer process patterns that encapsulate knowledge and commonly used practices in a particular domain. The design using an SB2P provides for the adaptation of these practices and it offers guidance on possible variations. This paper presents an automated method to construct SB2P starting from a set of process models in a given domain. The proposed method has the merit of accounting for the semantic, structural and behavioural information of the initial models. In addition, it produces process patterns where common fragments are distinguished from variation points, which assists business process designers in reusing an SB2P to meet their requirements. The method is illustrated through a case study in the cost accounting domain.

Keywords: business process modelling; semantic business process pattern; SB2P; business object ontology; BOON; semantic rules; mandatory activities; variation points. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=92889 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpmbe:v:8:y:2018:i:3:p:263-290

Access Statistics for this article

More articles in International Journal of Process Management and Benchmarking from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().