This study aims to understand the development status of public data utilization policies for research needs in the USA, UK and China. By comparing the content structure of policies, it proposes policy optimization strategies to strengthen the ability of public data to drive scientific advancements.
Based on the Open Data Barometer rankings, this study selects the USA, UK, and China as representative cases from high-, medium-, and low-tier countries. Using a three-dimensional framework (policy tools, data lifecycle, policy objectives), it conducts a textual quantitative analysis of 154 policies through systematic coding.
Post-2016, policies have increasingly addressed research needs, primarily through implementation plans and operational guidelines (44.16%). Cross-national trends reveal overreliance on environmental-side policy tools. Data lifecycle management prioritizes preliminary planning through environmental tools while neglecting post-utilization monitoring. Policy objectives balance data openness and security using environmental and supply-side tools, whereas demand-side tools focus on value creation but inadequately protect the rights of subject. The study reveals distinct national policy characteristics: the USA adopts an “open-first, ecosystem-driven” approach, the UK implements a “governance-first, trusted-access” authorization mechanism, while China demonstrates a “policy-guided, pilot-based” progressive model of data utilization.
Theoretically, this study delineates the policy logic of public data utilization for research through policy tools, providing the research perspective of the relationship between public data and research innovation. Practically, research findings offer insights for policymakers to optimize policy.
