数据与计算发展前沿 ›› 2024, Vol. 6 ›› Issue (1): 136-149.

CSTR: 32002.14.jfdc.CN10-1649/TP.2024.01.013

doi: 10.11871/jfdc.issn.2096-742X.2024.01.013

• 技术与应用 • 上一篇    下一篇

TSPVS：时序学者画像可视化系统

余敏槠1,2(),王杨1,顾睿琪1,单桂华1,*(),金钟1   

  1. 1.中国科学院计算机网络信息中心，北京 100190
    2.中国科学院大学，北京 100049
  • 收稿日期:2023-10-18 出版日期:2024-02-20 发布日期:2024-02-21
  • 通讯作者: * 单桂华（E-mail:sgh@cnic.cn）
  • 作者简介:余敏槠，中国科学院计算机网络信息中心，博士研究生，主要研究方向为大数据分析、数据可视化、自然语言处理。
    本文承担工作为：数据处理与分析、可视化方法设计、系统设计、论文撰写。
    YU Minzhu is a doctoral student at Computer Network Information Center, Chinese Academy of Sciences. Her main research interests are big data analysis, data visualization, natural language processing.
    In this paper, she undertakes the following tasks: data processing and analysis, visual design, system design and paper writing.
    E-mail: ymz1124@sina.cn|单桂华，中国科学院计算机网络信息中心，研究员，博士，主要研究方向为可视化与可视分析、智能交互。
    本文承担工作为：工作为整体规划和可视化设计指导。
    SHAN Guihua is a professor in Computer Network Information Center, Chinese Academy of Sciences. Her main research interests are visualization and visual analysis, intelligent interaction.
    In this paper, she undertakes the following tasks: the overall planning and visual design guidance.
    E-mail: sgh@cnic.cn
  • 基金资助:
    中国科学院战略性先导科技专项（B类）(XDB38030300)

TSPVS: A Temporal Scholar Profile Visualization System

YU Minzhu1,2(),WANG Yang1,GU Ruiqi1,SHAN Guihua1,*(),JIN Zhong1   

  1. 1. Computer Network Information Center, Chinese Academy of Science, Beijing 100190, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2023-10-18 Online:2024-02-20 Published:2024-02-21

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摘要：

【目的】为全面、直观、高效地刻画、对比学者科研活动特性，本文提出了一套支持对比分析的时序学者画像可视化方法。【方法】时序学者画像可视化方法基于太阳隐喻和引文网络，以时间维度为主线，将学者历年发表论文的数量、学者所属机构、论文主题、论文影响力、合作学者、合作机构等基本信息与研究兴趣变化、研究主题的广度和深度等深层次信息有机结合，使决策者可以通过一个页面快速、全面地掌握不同学者的异同。【结果】本文使用可视化领域的论文数据集，设计并实现了时序学者画像可视化系统TSPVS。【局限】目前系统仅包含可视化领域的论文数据，后续将进一步引入其他领域的论文数据。【结论】通过可视化领域论文数据中的3个案例说明TSPVS可以满足分析需求，可以在一个页面中刻画学者研究生涯中的重要特征和重大变化，并支持不同学者主要特征异同点的对比分析。

关键词: 学者画像, 时序性叙事, 可视化, 隐喻

Abstract:

[Objective] To comprehensively, intuitively, and efficiently depict and compare the characteristics of scholars' scientific research activities, this article proposes a temporal scholar portrait visualization method that supports comparative analysis. [Method] The visualization method of temporal scholars' portraits is based on the Sun metaphor and citation network, with a time dimension as the main thread. It combines basic information such as the number of scholars' published papers over the years, the affiliation of the scholars, the topic of the papers, the influence of the papers, cooperative scholars, and cooperative institutions with deep-seated information such as changes in research interests, the breadth and depth of the research topic, etc., enabling decision-makers to quickly and comprehensively grasp the similarities and differences of different scholars. [Results] This article uses a dataset from the field of visualization to design and implement a temporal scholar portrait visualization system TSPVS. [Limitation] However, currently the system only includes paper data from the visualization field, and further introduction of paper data from other fields will be made in the future. [Conclusion] Through three cases in the visualization field paper data, it is demonstrated that TSPVS can meet the analysis needs, depict important features and significant changes in scholars' research careers in one page, and support comparative analysis of the main characteristics of different scholars.

Key words: scholar profile, temporal narrative, visualization, metaphor