A Multi-criteria Evaluation Approach for Selecting a Sensitive Business Process Modeling Language for Knowledge Management

• Published in: Journal on data semantics Vol. 8; no. 3; pp. 157 - 202
• Main Authors: Ben Hassen, Mariam, Turki, Mohamed, Gargouri, Faïez
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2019; Springer Nature B.V
• Subjects: Artificial Intelligence; Business process engineering; Business process management; Complexity; Computer Science; Database Management; Information sources; Information Storage and Retrieval; Information Systems Applications (incl.Internet); IT in Business; Knowledge management; Knowledge representation; Languages; Modelling; Multiple criterion; Ontology; Organizational aspects; Original Article; Specifications; Sensitive business process; Knowledge management; Business process modeling; Multi-criteria decision-making approach; Modeling languages; Core ontologies
• ISSN: 1861-2032; 1861-2040
• DOI: 10.1007/s13740-019-00103-5

In an organizational context, the modeling and representation of sensitive business processes (SBPs) have become an effective way of managing and developing organization’s knowledge that needs to be capitalized. These processes are characterized by a high complexity and dynamism in their execution, high number of critical activities with intensive acquisition, sharing, storage and (re)use of very specific crucial knowledge, large diversity of heterogeneous knowledge and information sources, high number of knowledge conversion actions and high degree of collaboration among experts. Thus, the specification of a precise conceptualization for SBPs, and the selection of an appropriate SBP modeling language that adequately characterizes and integrates all their relevant dimensions are of prime importance. We aim at improving the localization and identification of the crucial knowledge that are mobilized by and created by these processes. This paper proposes a multi-criteria-based approach for evaluating and comparing currently widely used modeling languages (process oriented and knowledge oriented) for the representation of SBPs, taking into account their specific modeling requirements. We consider guiding and justifying the choice of the most suitable SBP modeling language for knowledge identification purposes. The different modeling languages are originally assessed according to the ontological completeness of SBP modeling aspects (i.e., the coverage of the functional, organizational, behavioral, informational, intentional and knowledge dimensions) based on the BPM4KI meta-model (as an SBP specification based on core ontologies). Secondly, they are evaluated according to several key requirement indicators (e.g., understandability, expressibility, complexity, level of adoption, tools availability and extendibility). Results show that none of the studied languages, individually, satisfies all the SBP modeling requirements. In this study, we choose the better one positioned nowadays, BPMN 2.0, as the best suited standard for SBP representation. Moreover, we develop a valid extension of BPMN 2.0 «BPMN4SBP» for integrating and implementing all relevant SBP modeling dimensions (the six BPM4KI dimensions), exploring the dynamic, interaction and knowledge aspects. The extension is then used to illustrate the representation of SBPs in a real case study in the healthcare domain.