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An approach to business process models repository development

A. Kopp, D. Orlovskyi
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Description: The problem of storing and sharing the organizational knowledge, represented by the collection of business process models, has been considered. The definition of repository, its reference architecture, the requirements for the business process models repository design, basic features and shortcomings of the existing solutions have been considered. The approach to development of the repository, which allows to analyze business process models, formulate recommendations for their enhancement, define semantic similarity between business process models in order to provide their further reusing for design new or improve existing organizational business processes, has been proposed. The problem of definition the semantic similarity between business process models is based on the considered similarity measure between Resource Description Framework graphs, which are build based on the business process models, and also on the Fuzzy Classifier Means method. To provide a repository user with the results of business process models analysis and enhancement, the event processing of repository activities (e.g. upload, analysis, update of business process models) and further visualization of the obtained metrics using dashboard has been proposed. The example set of metrics, used in the previous studies to measure process models, described using the Data Flow Diagram methodology, has been outlined. Thus, the requirements and features of the existing solutions have been augmented; the structure and conceptual data model, according to the proposed approach to development of the business process models repository, have been considered.


Keywords: business process model, repository, organizational knowledge, analysis, enhancement, semantic similarity, reusing

Reference:
 Kopp, A.M. and Orlovskyi, D.L. (2018), “Podkhod k postroenyiu repozytoryia modelei byznes-protsessov” [An approach to business process models repository development], Information Processing Systems, Vol. 2(153), pp. 60-68. https://doi.org/10.30748/soi.2018.153.07.