Semantic Model-based Systems Engineering based on KARMA: A Research and Practice Roadmap 2025

Jinzhi Lu (EPFL)
Dimitris Kiritsis (EPFL, Switzerland)
Yves Keraron (ISADEUS)
Junda Ma (Beijing Institute of Technology)
Martin Torngren (KTH Royal Institute of Technology)
Michel Reniers (Eindhoven University of Technology)
Huisheng Zhang (Shanghai Jiaotong University)
Jian Tang (COMAC BATRI)
Junjie Tang (Beijing Institute of Aerospace Systems Engineering)
Jian Wang (University of Science and Technology of China)
Xijin Tang (CAS Academy of Mathematics and Systems Science)
Yangyang Zhang (China Electronics Standardization Institute)
Feng Lei (KTH Royal Institute of Technology)
David Cameron (UIO)
Yan Yan, Guoxin Wang, Shouxuan Wu (Beijing Institute of Technology)

Keywords
MBSE;Semantic modeling;ontology
Abstract

Model-based Systems Engineering is proposed as a graphical approach to support for-malism of system artifacts across system lifecycle based on models since 1993. The previous moti-vation of graphical specification is to provide a unified graphical description on the perspective of systems engineering in order to formalize system architectural views, to promote communications among stakeholders and to support system analysis and verification. However, when different modeling tools are developed based on such graphical specifications, model and data interoperability across modeling tool is a biggest challenge faced by the tool venders and MBSE practitioner. Thus, semantic specification is proposed again to enhance data interoperability, such as SysML 2.0. In this paper, we propose a new semantic MBSE language and framework aiming to support complex sys-tem development using a two-core mechanism: KARMA language and Industrial Ontologies Foundry (IOF) SE and MBSE ontology. Then, we introduce the KARMA Roadmap 2025 including technical vision, organizational views and standardization. A new KARMA open-source environ-ment is planned to create in order to provide MBSE application for more MBSE practitioners.