An original Data, Information and Knowledge management approach for model-based engineering projects. Issue 10 (2022)

• Record Type: Journal Article
• Authors: Alaoui, M. El; Rabah, S.; Chapurlat, V.; Richet, V.; Plana, R.
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 10(2022)
• Page Start: 3262
• Page End: 3267
• Publication Date: 2022
• Subjects: System Engineering -- Model Based System Engineering (MBSE) -- Knowledge management -- SE Ontology -- Large engineering projects -- data -- information -- knowledge -- model; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.10.135
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Data, Information and Knowledge (DIK) problematics are of undeniable growing actuality; many efforts were made to explore and make progress in this domain. Therefore, these DIK have been defined by several characteristics conventionally studied such as volume, variety, variability… and a few solutions have been uncovered and revealed. In parallel, the systems Engineering (SE) and specifically Model-Based Systems Engineering (MBSE) approaches, that encourage, among other things, the use of models instead of documents in critical infrastructure engineering namely in the energy infrastructure domain, participate in the growing volume and complexity of DIK. In this particular context, it is important to enrich MBSE by adapting the existing DIK advances to the MBSE needs, which is initiated in this paper, first by providing DIK definition, second, by checking what are the main issues that shall be solved in order to help stakeholders use and manage them in large MBSE-driven projects, involving various business actors during more or less long periods. At last, this article proposes a methodological contribution bridging the supposed gap between MBSE and so-called data management fields of research.