Despite the growing prominence of Open Innovation (OI) in business and policy, National Innovation Metrics (NIM) remain largely rooted in traditional, firm-centric models, failing to capture ecosystem-wide collaboration and knowledge exchange This study critically examines how OI is integrated - or overlooked - within major Innovation Measurement Frameworks (IMF), particularly the European Innovation Scoreboard (EIS), Global Innovation Index (GII), and Bloomberg Innovation Index (BII). Findings reveal that existing innovation scoreboards prioritize input-output indicators (e.g., R&D expenditure, patenting) while neglecting systemic, network-driven innovation dynamics. The continued absence of OI-specific metrics reinforces a "black box" effect, where national innovation success is assessed without visibility into knowledge flows and collaborative innovation mechanisms. This study contributes to rethinking NIM by advocating for a shift from closed-system assessments to dynamic, network-based measurement models. By bridging innovation policy, measurement theory, and OI research, it provides a foundation for future empirical studies on integrating OI indicators into national benchmarking frameworks, ensuring more accurate assessments of Innovation Ecosystem (IE) performance.