This paper conducts an in-depth analysis of the content of current data intellectual property registration policies to provide reference suggestions for future policy improvement. Based on the basic logic of policy formulation and implementation, a collaborative analysis framework of "subject-tool-theme-effectiveness" is constructed. 29 policies were collected according to the specified search formula, and tools such as NVivo20 software, LDA model, and PMC index model were used to analyze policy subjects, policy tools, policy themes, and policy effectiveness. The analysis found that existing data intellectual property registration policies have four major problems: inconsistent registration institutions, unbalanced policy tools, incomplete policy objectives, and imperfect policy flexibility mechanisms. Accordingly, the following suggestions are proposed: establish a national data intellectual property registration platform to limit arbitrary authorization; improve the quality of data intellectual property registration and balance policy tools; combine central evaluation with local exploration to expand the factual effectiveness of registration certificates; reduce the rigidity of data intellectual property registration policies and coordinate operational mechanisms.
关键词
数据知识产权/登记政策/政策量化/PMC指数模型/LDA模型/政策工具
Key words
Data Intellectual Property/Registration Policy/Policy Quantification/PMC Index Model/LDA Model/Policy Tool
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