数据与计算发展前沿 ›› 2023, Vol. 5 ›› Issue (6): 9-19.

CSTR: 32002.14.jfdc.CN10-1649/TP.2023.06.002

doi: 10.11871/jfdc.issn.2096-742X.2023.06.002

• • 上一篇    下一篇

基础研究竞争力平台构建方法研究

李贞贞1,2,*(),钟永恒1,2,王辉1,2,刘佳1,2,孙源1,2   

  1. 1.中国科学院武汉文献情报中心，湖北 武汉 430071
    2.科技大数据湖北省重点实验室，湖北 武汉 430071
  • 收稿日期:2022-06-15 出版日期:2023-12-20 发布日期:2023-12-25
  • 通讯作者: 李贞贞（E-mail: lizz@mail.whlib.ac.cn）
  • 作者简介:李贞贞，中国科学院武汉文献情报中心，馆员，研究领域为科技和产业大数据分析方法与技术。
    文本中负责论文思路设计、系统设计与实现、论文撰写。
    LI Zhenzhen is a librarian at the Wuhan Library of the Chinese Academy of Sciences. Her research fields include technology and industry big data analysis methods and techniques.
    In this paper, she is responsible for the design of ideas, system design and implementation, and the writing of this paper.
    E-mail:lizz@mail.whlib.ac.cn
  • 基金资助:
    湖北省技术创新专项软科学研究类重大项目(2021EDA036);湖北省技术创新专项软科学研究类重点项目(2022EDA010)

Research on the Construction Method of Basic Research Competitiveness Platform

LI Zhenzhen1,2,*(),ZHONG Yongheng1,2,WANG Hui1,2,LIU Jia1,2,SUN Yuan1,2   

  1. 1. Wuhan Library of Chinese Academy of Sciences, Wuhan, Hubei 430071, China
    2. Hubei Key Laboratory of Big Data in Science and Technology, Wuhan, Hubei 430071, China
  • Received:2022-06-15 Online:2023-12-20 Published:2023-12-25

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摘要：

【背景】 基础研究竞争力是体现国家、地区、机构、学科以及人才科技创新能力的核心要素。【目的】 为追踪、研判我国基础研究竞争力，设计基础研究竞争力平台，发现中国各地区、各机构基础研究竞争力发展轨迹。【方法】 平台总体架构包括基础设施层、数据体系层、数据分析层和应用服务层，数据体系层建立了基于国家自然科学基金、学术论文、基本科学指标、发明专利、创新平台、国家科技奖励和高端人才七大资源的数据体系与评价指标；数据分析层构建了基础研究竞争力指数，对我国基础研究竞争力进行总体分析、省域分析和机构分析，并采用自然语言处理技术实现语义层面的知识服务；应用服务层建设了基础研究竞争力平台，提供交互式检索、全方位数据展示、专题研究、分析评价、研究报告和个人中心六大功能服务模块。【结果】 基础研究竞争力平台利用基础研究竞争力指数模型和数据挖掘方法，较好地组织了海量多源异构科技数据，直观地展现了我国各地区、各机构基础研究竞争力发展现状及趋势，为我国基础研究精准决策提供支撑与辅助。

关键词: 基础研究, 基础研究竞争力指数, 数据体系, 评价指标, 知识服务, 国家自然科学基金

Abstract:

[Background] The competitiveness of basic research is the core element reflecting the scientific and technological innovation ability of countries, regions, institutions, disciplines, and talents. [Objective] In order to track and judge the competitiveness of basic research in China, we design a basic research competitiveness platform, and find the development track of the competitiveness of basic research in various regions and institutions in China. [Methods] The overall architecture of the platform includes infrastructure layer, data system layer, data analysis layer, and application service layer. The data system layer has established a data system and evaluation indicators based on NSFC fundings, academic papers, ESI, invention patents, innovation platforms, national science and technology awards, and high-end talents. The data analysis layer constructs the Basic Research Competitive Index, carries out overall analysis, provincial analysis, and institutional analysis of China's basic research competitiveness, and uses natural language processing technology to achieve semantic knowledge services. The application service layer has built a basic research competitiveness platform, which provides six functional service modules, including interactive retrieval, all-around data display, special research, analysis and evaluation, research report, and personal center. [Results] The basic research competitiveness platform uses the BRCI model and data mining methods to better organize a large number of multi-source heterogeneous scientific and technological data, to intuitively show the development status and trend of the basic research competitiveness of various regions and institutions in China, and to provide support and assistance for the accurate decision-making of basic research in China.

Key words: basic research, basic research competitive index, data system, evaluation index, knowledge service, NSFC