TY - JOUR
T1 - Insights into ontology-based model-based systems engineering
T2 - state of the art and enabling framework
AU - Dong, Mengru
AU - Wang, Guoxin
AU - Lu, Jinzhi
AU - Wu, Shouxuan
AU - Gong, Yihui
AU - Yan, Yan
AU - Kiritsis, Dimitris
N1 - Publisher Copyright:
Copyright © 2026. Published by Elsevier Ltd.
PY - 2026/11
Y1 - 2026/11
N2 - Ontology offers a formalized framework for knowledge representation and reasoning in complex systems, enabling the development of model-based systems engineering (MBSE). This study conducts a systematic bibliometric analysis of 566 papers on ontology in MBSE from 2008 to 2024, complemented by a qualitative literature review. The findings reveal a marked upward trajectory in research activities, characterized by small-scale collaboration networks predominantly led by core scholars. The research topics converge on several key topics related to the subject of ontology in MBSE, including modeling language, decision-making and knowledge management, life cycle integration, architecture modeling, and interoperability. From the perspective of these key topics, in this study, a systematic literature review was conducted to propose an ontology-based MBSE enabling framework. This framework consists of: (1) an ontology-based MBSE paradigm that reconfigures MBSE processes through enhanced semantic interoperability, optimized life cycle management, and dynamic decision support mechanisms; (2) a reference architecture that integrates MBSE models with ontology; and (3) key technologies that address semantic consistency verification and multidomain integration. Finally, the industrial applications are discussed as illustrative, preliminary, and qualitative evidence, suggesting the potential applicability of the proposed ontology-based MBSE framework in real-world engineering scenarios, particularly in the aviation industry. This work offers a structured overview of the current state, research hotspots, future trajectories, and enabling framework of ontology in MBSE. Future work can further investigate standardized evaluation metrics and benchmarking methods to quantitatively assess the effectiveness and performance of the OBMBSE framework in industrial applications.
AB - Ontology offers a formalized framework for knowledge representation and reasoning in complex systems, enabling the development of model-based systems engineering (MBSE). This study conducts a systematic bibliometric analysis of 566 papers on ontology in MBSE from 2008 to 2024, complemented by a qualitative literature review. The findings reveal a marked upward trajectory in research activities, characterized by small-scale collaboration networks predominantly led by core scholars. The research topics converge on several key topics related to the subject of ontology in MBSE, including modeling language, decision-making and knowledge management, life cycle integration, architecture modeling, and interoperability. From the perspective of these key topics, in this study, a systematic literature review was conducted to propose an ontology-based MBSE enabling framework. This framework consists of: (1) an ontology-based MBSE paradigm that reconfigures MBSE processes through enhanced semantic interoperability, optimized life cycle management, and dynamic decision support mechanisms; (2) a reference architecture that integrates MBSE models with ontology; and (3) key technologies that address semantic consistency verification and multidomain integration. Finally, the industrial applications are discussed as illustrative, preliminary, and qualitative evidence, suggesting the potential applicability of the proposed ontology-based MBSE framework in real-world engineering scenarios, particularly in the aviation industry. This work offers a structured overview of the current state, research hotspots, future trajectories, and enabling framework of ontology in MBSE. Future work can further investigate standardized evaluation metrics and benchmarking methods to quantitatively assess the effectiveness and performance of the OBMBSE framework in industrial applications.
KW - Bibliometric analysis
KW - Enabling framework
KW - Industrial applications
KW - Ontology-based model-based systems engineering
KW - Systematic literature review
UR - https://www.scopus.com/pages/publications/105041222744
U2 - 10.1016/j.aei.2026.104947
DO - 10.1016/j.aei.2026.104947
M3 - Article
AN - SCOPUS:105041222744
SN - 1474-0346
VL - 76
JO - Advanced Engineering Informatics
JF - Advanced Engineering Informatics
M1 - 104947
ER -