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Towards Semantically-Aided Domain Specific Business Process Modeling
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| Nikolaos Lagos, Adrian Mos, Mario Cortes-Cornax |
| Data Technologies and Applications |
@article{article,
author = {Lagos, Nikolaos and Mos, Adrian and Cortes Cornax, Mario},
year = {2018},
month = {07},
pages = {},
title = {Towards Semantically-Aided Domain Specific Business Process Modeling (Full text at https://www.emeraldinsight.com/eprint/KZFCESS3GHUYXBGVP3P8/full - Limited access)},
journal = {Program electronic library and information systems},
doi = {10.1108/DTA-01-2018-0007}
}Purpose – Domain-specific process modelling has been proposed in the literature as a solution to several problems in Business Process Management (BPM).
Structured Abstract:
Purpose – Domain-specific process modelling has been proposed in the literature as a solution to several problems in Business Process Management (BPM). The problems arise when using only the generic Business Process Model and Notation (BPMN) standard language for modelling. This language includes domain ambiguity and difficult long-term model evolution. Domain-specific modelling involves developing concept definitions, domain specific processes and eventually industry-standard BPMN models. This entails a multi-layered modelling approach, where any of these artefacts can be modified by various stakeholders and changes done by one person may influence models used by others. There is therefore a need for tool support to keep track of changes done and their potential impacts.
Design/methodology/approach – 1. We use a multi-context systems based approach to infer the impacts that changes may cause in the models; and 2. We incrementally map components of business process models to ontologies.
Findings – Advantages of our framework include: 1. Identifying conflicts/inconsistencies across different business modelling layers; 2. Expressing rich information on the relations between two layers; 3. Calculating the impact of changes taking place in one layer to the rest of the layers; and 4. Selecting incrementally the most appropriate semantic models on which the transformations can be based.
Research limitations/implications – Extensive usability tests would enable to confirm further the findings of the paper. We consider this work as one of the foundational bricks that will enable further advances towards the governance of multi-layer business process modelling systems.
Practical implications – The approaches described here should improve the maintainability, reuse and clarity of business process models. This can improve data governance in large organisations and for large collections of processes by aiding various stakeholders to understand problems with process evolutions, changes and inconsistencies with business goals.
Originality/value – This paper fulfils an identified gap to enabling semantically-aided domain specific process modelling.