The digital transformation of education has increased the need for interoperable and machine-interpretable frameworks that can support competency-based teacher professional development in STEM-oriented environments. This study proposes an ontology-driven semantic framework for transparent competency mapping and explainable assessment in digital STEM teacher professional development systems. The model was implemented using the Web Ontology Language in the Protégé environment and validated through