About

The successful application of ontological modeling and analysis requires further research and development to unlock its truepotential, and find further impact in academia, industry, and government. This is increasingly important for the engineering of today’scomplex systems, their digital twins, and the addition of advanced AI and ML approaches such as LLMs. These software and systemengineering approaches require the capturing, integration, and analysis over heterogeneous domain knowledge, which is well-suitedto ontological approaches.The second onto:Nexus workshop builds momentum by bringing together a rich set of researchers, practitioners, and tool-builders focused on ontological modeling and analysis, as applied to model-based software and systems engineering. The primaryobjective is to facilitate discussions and spark ideas, especially between participants from different domains.The secondary objective is to highlight novel and ongoing work in ontological modeling and analysis. With the resurgence ofontological techniques across domains and disciplines, our workshop promotes early-stage novel research, fundamental contribu-tions, and applications to case studies.

Important Dates

• Friday June 26, 2026 Abstract submission
• Friday July 3, 2026 Paper submission
• Friday July 31, 2026 Notification of acceptance
• Friday August 14, 2026 Camera-ready submission

Topics of Interest

• Ontological modeling methods / methodologies, analysis tools, and processes for model-based software or systems engineering
• Ontological modeling best practices and guidelines, case studies, and benchmarks
• Creation of ontologies through collaboration, machine learning techniques, or other approaches
• Tooling for ontological modeling and analysis
• Empirical studies on the use of ontologies in MBSE
• Intersections between ontologies and formal methods
• Organizational and governance aspects of ontological modeling
• Semantic interoperability in software and/or systems
• AI for ontological modeling/analysis, and ontological modeling/analysis for AI
• Human-in-the-Loop: integrating human behavior into ontological modeling