Shaping new models of scholarly communication in the era of open science and AI
[Purposes]In the era of open science and AI,this paper provides reference and inspiration for participants in the construction of scholarly communication systems such as scientific journals,publishing groups,and literature and information institutions to shape new scholarly communication models.[Methods]This paper sorted out the functions and responsibilities of the scholarly communication system,analyzed the changes and impacts of open science and AI technology on scholarly communication model,and summarized the relevant efforts taken by the National Science Library,Chinese Academy of Sciences to promote the construction of a new scholarly communication system in the era of open science and AI.[Findings]The impact of open science on the scholarly communication system is mainly reflected in the rise of preprint communication,open review,and copyright reform.The impact of AI on the scholarly communication system is mainly reflected in the AI-assisted scientific research and submission process,the AI-promoted automated and intelligent process of scholarly publishing,and the AI-promoted dissemination of scholarly journals.The related initiatives of the National Science Library,Chinese Academy of Sciences in promoting the construction of the new type of scholarly communication system are to launch the PubScholar public welfare academic platform,build the"pre-registration+preprint+open review+formal release"open field academic communication system based on ChinaXiv preprint platform,construct SciAIEngine to support the intelligent mining and utilization of scientific and technological literature content,and cooperate with leading enterprises to build and release a large model of scientific and technological literature and Starfire Research Assistant.[Conclusions]Participants in the construction of scholarly communication systems should actively participate in shaping new scholarly communication models in the era of open science and AI.
NETL
NSTL
万方数据
