Key points are not available for this paper at this time.
The management and protection of data-based intellectual property have attracted increasing attention in the academic community due to the rapid development of digital technologies and data-driven industries. However, a comprehensive and multidimensional examination of the research landscape is still required to better understand its structure and evolution. Using CiteSpace software, this study conducts a bibliometric analysis, revealing key trends and patterns in collaboration, co-citation, and keyword co-occurrence in the field of data-based intellectual property. Our findings show a growing body of literature on data IP management, with a significant increase in publications since 2013. We identify that collaboration between regions, especially the United States, China, and the United Kingdom, leads global efforts, but institutional collaboration remains underdeveloped. In terms of co-citation, seminal works by Jaffe, Hall, and Samuelson form the foundation of the current research, while emerging research focuses on technological innovations like blockchain and AI. The analysis further reveals that future research is likely to explore the intersections of data privacy, innovation, and legal frameworks. Compared with previous studies, this paper builds a knowledge framework for data-based intellectual property management from a holistic perspective of bibliometrics, analyses the current challenges, and outlines future research directions, which is of significant reference value to both scholars and practitioners.
Sun et al. (Thu,) studied this question.