图书情报知识 ›› 2023, Vol. 40 ›› Issue (5): 28-38,126.doi: 10.13366/j.dik.2023.05.028

• 专题·AI 时代的数字学术基础设施 • 上一篇    下一篇

AIGC时代的科研工作流:协同与AI赋能视角下的数字学术工具应用及其未来

王树义, 张庆薇, 张晋   

  1. 天津师范大学管理学院,天津 ,300387
  • 出版日期:2023-09-10 发布日期:2023-10-22
  • 通讯作者: 王树义(ORCID:0000-0001-5595-4416),博士,副教授,研究方向:人工智能应用、复杂知识网络管理,Email:nkwshuyi@gmail.com。
  • 作者简介:张庆薇(ORCID:0009-0005-7778-1444),硕士研究生,研究方向:人工智能应用,Email:qingwei812@foxmail.com;张晋(ORCID:0000-0001-6823-8697),硕士研究生,研究方向:人工智能应用,Email:zj1998106@163.com。
  • 基金资助:
    本文系天津师范大学教学改革项目“适应创新人才培养的教学形式与教学方法改革与实践”(JG01222051)研究成果之一。

Research Workflow in the Era of AIGC: Application and Future of Digital Academic Tools from the Perspectives of Collaboration and AI Empowerment

WANG Shuyi, ZHANG Qingwei, ZHANG Jin   

  1. Management School of Tianjin Normal University, Tianjin, 300387
  • Online:2023-09-10 Published:2023-10-22
  • Contact: Correspondence should be addressed to WANG Shuyi, Email:nkwshuyi@gmail.com, ORCID: 0000-0001-5595-4416
  • Supported by:
    This is an outcome of the Teaching Reform Project "Reform and Practice of Teaching Forms and Methods for Cultivating Innovative Talents"(JG01222051)supported by Tianjin Normal University.

摘要: [目的/意义]从“协同能力”和“AI赋能”的视角,研究科研活动中软件工具的选择,并提出科研工作流构建的建议。[研究设计/方法]根据科研流程,通过网站与用户调研等方式,收集有关科研工具的信息,考虑功能特色和用户评价。以协同能力和AI赋能作为标准,对主流科研工具进行对比筛选。[结论/发现] 科研软件应用的协同能力存在显著不同,与AIGC技术结合的程度也有显著差异。通过对科研工具进行优选后所构造的科研工作流,可以在不同科研过程中、不同设备上和不同用户之间实现更为有效的协同,提升科研人员的知识管理与知识生产效率。[创新/价值]为科研人员的软件选择提供参考,促进更多优秀科研工具协同和AIGC能力的提升,以及科研活动整体效率的提高。

关键词: 科研工具, 科研工作流, 协同能力, AIGC

Abstract: [Purpose/Significance] This study aims to examine the selection of software tools in scientific research activities from the perspectives of "collaborative ability" and "AI empowerment", and propose suggestions for constructing scientific research workflows. [Design/Methodology] Based on the scientific research process, through website surveys and user feedback, we collected information of scientific research tools considering their functional characteristics and user evaluations. Using collaborative ability and AI empowerment as criteria, we compared and selected mainstream scientific research tools. [Findings/Conclusion] There are significant differences in the collaborative abilities of different scientific research software applications, as well as in the degree to which these softwares are integrated with AIGC technology. By constructing optimized workflows through screening scientific research tools, more effective collaboration can be achieved among different stages of scientific research processes, devices, and users to enhance knowledge management and production efficiency of researchers. [Originality/Value] This study provides references for the software choices of researchers and promotes more excellent research tools selected to collaborate in scientific research and improve AIGC capabilities and the overall efficiency of research activities.

Key words: Research tools, Research workflow, Collaborative capabilities, AIGC(Aitificial Intelligence Generated Content)