面向新质生产力发展的科技人才数据底座建设
[目的/意义]通过科技人才数据底座建设，助力人才发展决策科学化，促进新质科技人才引育精准化，推动科技人才评价改革落地，推进新质生产力人才体系建设。[方法/过程]通过剖析科技人才数据底座建设的现实要求和意义，研究和分析科技人才数据底座助力新质生产力发展的内在逻辑，针对当前科技人才数据底座建设面临的挑战，提出科技人才数据底座的建设思路，开展研究探索与应用实践。[结果/结论]科技人才数据底座建设是数智时代发展的客观要求，也是新质生产力形成的必然要求。构建科技人才大数据，数智赋能人才工作流程，构筑科技人才数据底座，有助于激活数据在人才资源配置中的作用，加速科技创新，推动新质生产力发展。...
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| Published in | 农业图书情报学报 Vol. 36; no. 2; pp. 15 - 25 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国农业科学院农业信息研究所
05.02.2024
中国科学院文献情报中心,北京 100190%中国科学院文献情报中心,北京 100190 中国科学院大学经济与管理学院信息资源管理系,北京 100190 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-1248 |
| DOI | 10.13998/j.cnki.issn1002-1248.24-0175 |
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| Abstract | [目的/意义]通过科技人才数据底座建设，助力人才发展决策科学化，促进新质科技人才引育精准化，推动科技人才评价改革落地，推进新质生产力人才体系建设。[方法/过程]通过剖析科技人才数据底座建设的现实要求和意义，研究和分析科技人才数据底座助力新质生产力发展的内在逻辑，针对当前科技人才数据底座建设面临的挑战，提出科技人才数据底座的建设思路，开展研究探索与应用实践。[结果/结论]科技人才数据底座建设是数智时代发展的客观要求，也是新质生产力形成的必然要求。构建科技人才大数据，数智赋能人才工作流程，构筑科技人才数据底座，有助于激活数据在人才资源配置中的作用，加速科技创新，推动新质生产力发展。 |
|---|---|
| AbstractList | [目的/意义]通过科技人才数据底座建设，助力人才发展决策科学化，促进新质科技人才引育精准化，推动科技人才评价改革落地，推进新质生产力人才体系建设。[方法/过程]通过剖析科技人才数据底座建设的现实要求和意义，研究和分析科技人才数据底座助力新质生产力发展的内在逻辑，针对当前科技人才数据底座建设面临的挑战，提出科技人才数据底座的建设思路，开展研究探索与应用实践。[结果/结论]科技人才数据底座建设是数智时代发展的客观要求，也是新质生产力形成的必然要求。构建科技人才大数据，数智赋能人才工作流程，构筑科技人才数据底座，有助于激活数据在人才资源配置中的作用，加速科技创新，推动新质生产力发展。 G353%TP391%C96; [目的/意义]通过科技人才数据底座建设,助力人才发展决策科学化,促进新质科技人才引育精准化,推动科技人才评价改革落地,推进新质生产力人才体系建设.[方法/过程]通过剖析科技人才数据底座建设的现实要求和意义,研究和分析科技人才数据底座助力新质生产力发展的内在逻辑,针对当前科技人才数据底座建设面临的挑战,提出科技人才数据底座的建设思路,开展研究探索与应用实践.[结果/结论]科技人才数据底座建设是数智时代发展的客观要求,也是新质生产力形成的必然要求.构建科技人才大数据,数智赋能人才工作流程,构筑科技人才数据底座,有助于激活数据在人才资源配置中的作用,加速科技创新,推动新质生产力发展. |
| Abstract_FL | [Purpose/Significance]Talent data have become the most important production factor and strategic resource.Building a scientific and technological(S&T)talent database has become an inevitable way to narrow the digital divide and accelerate the digital and intelligent transformation of talent work.Therefore,this study builds an S&T talent database to promote scientific decision-making for talent development,precision in attracting new quality technical talent,reform in evaluating S&T talents,and building talent system for new quality productive forces.[Method/Process]By analyzing the practical requirements and significance of building an S&T talent database,this study first explores and analyzes the intrinsic logic of promoting the development of new quality productive forces through an S&T talent database.It then summarizes the challenges facing the current construction of a S&T talent database,including the scattering and concealment of S&T talent data,the lack of policies and standardized systems for S&T talent data,the inadequate exploration of value-added S&T talent data,the need to expand the application of digital technology in talent work,and the security risks of S&T talent data.In response to these challenges,this paper finally proposes the idea of building an S&T talents database,and introduces the research exploration and application practice on it,including the construction of big data database for S&T talent aimed at the development of new quality productive forces,the development of AI-powered talent data computing engine,research into the system for profiling new quality technical talent,the analysis of talent growth paths for the training of new quality technical talent,the identification method of new quality talented professionals based on big data,the development of an efficient digital platform for talent management,and the development of a strategic analysis platform for technical talent.[Results/Conclusions]The construction of S&T talent database is an objective requirement for the development of the digital era and an inevitable requirement for the formation of new quality productive forces.Building big data for S&T talent,empowering talent workflow with big data and artificial intelligence technology can help empower talent workflow,release the enormous energy contained in digitalization,effectively activate the internal momentum of talented professionals,institutions,society,and government,and then continuously improve the efficiency of talent resource allocation,the operational efficiency of talent work,the overall effectiveness of talent development governance,and promote the development of new quality productive forces. |
| Author | 钱力 常志军 贾海青 李猛力 王颖 谢靖 |
| AuthorAffiliation | 中国科学院文献情报中心,北京 100190%中国科学院文献情报中心,北京 100190;中国科学院大学经济与管理学院信息资源管理系,北京 100190 |
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| Author_FL | QIAN Li CHANG Zhijun JIA Haiqing XIE Jing LI Mengli WANG Ying |
| Author_FL_xml | – sequence: 1 fullname: LI Mengli – sequence: 2 fullname: WANG Ying – sequence: 3 fullname: QIAN Li – sequence: 4 fullname: XIE Jing – sequence: 5 fullname: CHANG Zhijun – sequence: 6 fullname: JIA Haiqing |
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| Keywords | 人工智能 新质生产力 大模型 人才识别 大数据 人才画像 large model talent profile talent identification big data new quality productive forces artificial intelligence |
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