Abstract: In the current era of digital intelligence, the data-intensive disciplinary paradigm has facilitated the rise of data- and computation-driven research in Science of Science (SoS). The increasing abundance of big data in sciences and powerful data analytics has brought unprecedented development opportunities and challenges to SoS. Based on a review of the domestic literature in the last five years in meta-research on SoS and theoretical SoS, the latest research progress in SoS is explored. It is found that the current domestic meta-research on SoS mainly focuses on the change of the research paradigm as well as the construction and development of the disciplines of SoS.The research paradigm of SoS in China goes through four stages: speculation, mathematical statistics, scientific knowledge mapping, and SoS under digital intelligence. In terms of construction and development of the disciplines, the discipline of SoS is now in the second spring, after the first spring, a cold winter, and the renaissance. Theoretical sciences research focuses on the law of scientific development,scientists' career, and the mode of scientific collaboration.For scientific development, the recombination and integration of knowledge units is one of the key drivers of scientific development and scientific innovation. The flourishing of scientific development and the emergence of new large-scale scientific achievements are necessary conditions. Regarding the scientists' career, there are three paths in domestic research: the portrayal and regularization of the academic rhythms of a scientist's life, the drawing of academic genealogy of scientists, and combing and summarizing scientists' thoughts. Domestic research on scientific collaboration can be divided into three areas: collaboration behavior, collaboration influencing factors, and collaboration network structure and evolution. When it comes to collaboration behavior, Chinese scientists are more cooperative-centric than foreign scientists. In terms of collaboration influencing factors, scientific cooperation has differences in individual attributes (gender, age, culture/ethnicity), address attributes (institution, geography, international collaboration), professional attributes (subject area, knowledge background), and relational attributes (cooperation members, cooperation network). In terms of collaboration network structure and evolution, there are weak, strong, and super-relationships among scientists. In the face of new development opportunities, the real problems that need to be solved in China's SoS research mainly include insufficient theoretical systems, insufficiently perfect big data infrastructure construction, and insufficiently mature research paradigms. With the arrival of the era of digital intelligence, China's SoS needs to return to the tradition of Bernard's science and achieve a breakthrough in the research paradigm. The development of SoS should change from discipline-oriented to problem- and demand-oriented, and continuously promote the high-quality development of society and economy.

摘要： 当前数智化时代，数据密集型的学科范式促进了数据和计算驱动的科学学研究的兴起。科学学的大数据越来越丰富，加之强大的数据分析技术，为科学学带来了前所未有的发展机遇和挑战。基于对国内近五年在科学学元研究和理论科学学方面的文献进行综述，探讨科学学的最新研究进展。研究发现，当前国内科学学元研究主要集中在科学学研究范式的变革以及科学学的学科建设与发展等主题领域。理论科学学研究集中在科学发展规律、科学家生涯规律、科学合作规律及模式等方面。面对新的发展机遇，我国科学学研究亟待解决的现实问题主要包括学科理论体系不够健全、大数据基础设施建设不够完善和研究范式不够成熟等方面。随着数智化时代的到来，我国科学学研究需回归贝尔纳科学学传统，并实现研究范式的新突破。科学学发展应从学科导向转变为问题和需求导向，不断推动社会和经济的高质量发展。