Scaling Trust in Industrial Semantic Ecosystems: An Integrated Validation Framework for Interoperable Modeling and Tagging

The aerospace industry is undergoing a paradigm shift toward data-centric digital continuity, necessitating seamless interoperability between diverse processes and tools. Although previous work has established simplified methodologies to empower Subject Matter Experts (SMEs) to create semantic models, this democratization introduces significant risks in terms of data quality and trust. Without a robust validation strategy, decentralized modeling efforts threaten to generate incoherent "semantic silos", undermining the potential value of the ecosystem. To address this challenge, this paper introduces an integrated validation framework designed to secure the entire semantic lifecycle, defined by three key stages: Modeling, Tagging, and Federation. We specifically detail the validation methodologies for the first two stages. For Modeling, we propose a dual approach: a "Live Verification & Validation" (Live V&V) providing proactive, educational guidance during the creation process, and a "Final V&V" serving as a normative quality gate. For Tagging, we present a rigorous criteria-based method (covering Context, Accuracy, and Specificity) to ensure unambiguous alignment with a Common Language based on ISO 81346. The application of this framework is demonstrated through an industrial use case involving the compliance of A350 cabin layout configurations with EASA regulations. Finally, we discuss the necessity of extending this validation logic to the third stage, Federation, and the role of future AI-assisted tooling in scaling trusted semantic ecosystems.