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Journal of Library and Information Science in Agriculture ›› 2024, Vol. 36 ›› Issue (2): 15-25.doi: 10.13998/j.cnki.issn1002-1248.24-0175

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Building an Scientific and Technological Talent Database for New Quality Productive Forces

LI Mengli1, WANG Ying1,2,*, QIAN Li1,2,*, XIE Jing1,2, CHANG Zhijun1,2, JIA Haiqing1   

  1. 1. National Science Library, Chinese Academy of Sciences, Beijing 100190;
    2. Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190
  • Received:2024-01-05 Online:2024-02-05 Published:2024-04-30

Abstract: [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.

Key words: new quality productive forces, artificial intelligence, big data, talent profile, large model, talent identification

CLC Number: 

  • G353
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