This study develops a utility-oriented framework for valuing research data and validates its applicability through a national R&D case study. Based on three principles—objectivity (reproducible quantitative measures), scalability (cross-disciplinary reuse and dissemination), and practicality (linkage to R&D performance management)—we propose ten valuation indicators: metadata completeness, quality consistency, timeliness, ethical/legal compliance, reusability, standardization compliance, openness/accessibility, infrastructure interoperability, contribution to utilization, and scholarly originality. Each indicator is operationalized with check items, required evidence, and scoring rules to ensure reproducibility. The framework was applied in an NTIS–NRDP environment using the “Infection Control Convergence Research Center” case, scoring indicators based on evidence such as standard metadata, licensing, DOI/API availability, usage statistics, and links to outputs (papers, patents, technology transfer). Results showed strong evidence for standards-based documentation, quality control, update history, and compliance, while CC licensing, multiple formats, DOI, and REST APIs supported scalability. The study suggests research data can function as a core performance-management asset and highlights governance needs regarding recency interpretation, standard tags/codebooks, and transparent access conditions.