Meaning Engineering - beyond the Dictionary Fallacy in Industrial Interoperability

Position paper proposing “Meaning Engineering” as a framework for addressing semantic and operational interoperability in complex industrial environments. In modern industry, continuous operational interoperability across extended virtual enterprises remains a persistent bottleneck. Despite widespread deployment of information technologies—ranging from data lakes and knowledge graphs to enterprise architecture frameworks and Large Language Models (LLMs)—systems routinely exchange syntactically compliant data that leads to operational failures. This position paper addresses the conflation of vocabulary compliance with operational truth. By examining how meaning is constructed across natural language, visual modeling languages (SysML, ArchiMate), and semantic web standards (SKOS, RDF/OWL), it argues that dictionary-first and data-centric paradigms alone cannot guarantee truth or semantic alignment. It proposes Meaning Engineering, a pragmatically grounded framework integrating semiotics, model-based systems engineering (MBSE), and formal Verification and Validation (V&V), establishing an epistemic continuum from raw tokens and structured information to verified knowledge and actionable operational practice.