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Extensible ontology-based views for business process models
- Source :
- Knowledge and Information Systems. 63:2763-2789
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- A business process model may be used as both a communication artefact for gathering and sharing knowledge of a business practice among stakeholders and as a specification for the automation of the process by a Business Process Management System (BPMS). For each of these uses, it is desirable to have an ability to visualise the process model from a range of different perspectives and at various levels of granularity. Such views are a common feature of enterprise architecture frameworks, but process modelling and management systems and tools generally have a limited number of available views to offer. This paper presents a taxonomy of process views that are presented in the literature and then proposes the definition and use of a common process model ontology, from which an extensible range of process views may be derived. The approach is illustrated through the realisation of a plug-in component for the YAWL BPMS, although it is by no means limited to that environment. The component illustrates that the process views frequently mentioned in the literature as desirable can be effectively implemented and extended using an ontology-based approach. It is envisaged that the accessibility of a repertoire of views that support business process development will lead to greater efficiencies through more accurate process definitions and improved change management support.
- Subjects :
- Enterprise architecture framework
Process modeling
Computer science
Process (engineering)
business.industry
Business process
Business process modeling
Ontology (information science)
Human-Computer Interaction
Business process management
Artificial Intelligence
Hardware and Architecture
Change management (engineering)
Software engineering
business
Software
Information Systems
Subjects
Details
- ISSN :
- 02193116 and 02191377
- Volume :
- 63
- Database :
- OpenAIRE
- Journal :
- Knowledge and Information Systems
- Accession number :
- edsair.doi...........9efb8c9e4372e40a87107bc5173f481e
- Full Text :
- https://doi.org/10.1007/s10115-021-01604-1