[Purpose/Significance] This study employs the BERTopic model to analyze the core themes, evolutionary pathways, and frontier dynamics of data element valorization in China, providing a macro perspective and objective foundation for advancing theoretical exploration and guiding practical applications. [Method/Process] Having used 1735 articles published in CNKI from 2019 to the present as the dataset, this research had applied the BERTopic topic modeling approach. First, a semantic embedding space had been constructed using a pre-trained language model, and UMAP had been applied for dimensionality reduction, combined with HDBSCAN for density-based clustering, to have initially generated the incorporation of a temporal analysis method to trace the dynamic evolution of research topics. [Result/Conclusion] The findings reveal that: ① Current research themes focus on five key areas: "Enterprise Innovation and Data Element Market Cultivation", "Data Infrastructure Systems and Industrial Digital Transformation", "Element Marketization Allocation and Institutional Reform", "Data Transaction Systems and Market Competition Mechanisms", and "Data Empowerment for Productivity Improvement and Regulatory Balance". ② Data element valorization exhibits multidimensional collaborative characteristics and forms a dynamic evolutionary mechanism.