New directions of digitally driven S&T evaluation  

作　　者：Yunwei Chen Xuyi Zhang Jorge Gulin-Gonzalez 

机构地区：[1]Scientometrics&Evaluation Research Center(SERC),Chengdu Library and Information Center of Chinese Academy of Sciences,Chengdu,China [2]Department of Information Resources Management,School of Economics and Management,University of Chinese Academy of Sciences,Beijing,China [3]Centro de Estudios de Matematica Computacional(CEMC),Universidad de las Ciencias Informaticas(UCl).Carretera a San A.de los Banos,Km 2/1/2.Torrens,La Lisa,La Habana,Cuba

出　　处：《Data Science and Informetrics》2023年第2期53-66,共14页数据科学与信息计量学（英文）

摘　　要：Science and Technology(S&T)evaluation plays a baton role in developing science and technology innovation.However,traditional S&T evaluation indicators and methods are difficult to apply effectively in S&T evaluation practice.This paper analyzes the transformation of the S&T evaluation paradigm in the digital environment.Theories,methods,and tools of S&T evaluation research are continuously innovated and optimized;big data becomes the driving force of S&T evaluation development;the role played by S&T evaluation is shifting from a provider of statistical data and information to a participant in S&T decision-making activities.S&T evaluation research should focus on improving data retrieval and organization,knowledge mining and knowledge discovery,and intelligent evaluation models.Moreover,we suggest that scientists carry out S&T evaluation in agreement with the needs of S&T development:1)monitoring and sensing the development of science and technology in real-time with the help of emerging digital technologies;2)exploring solutions to major concerns such as technical project management mechanisms,utilizing advanced data science and digital technologies to identify important scientific frontiers,and leveraging big data in science of science to reveal patterns and characteristics of scientific structures and activities;3)carrying out problem-oriented evaluation research practice focused on four aspects,including intelligent project evaluation,evaluation of the critical technology competitiveness,talent assessment,and diagnostic evaluation of the research entity competitiveness.

关 键 词：Digital development S&T evaluation Digital technology Big Data in Science of Science Data science 

分 类 号：G301[文化科学]