AI4VIS: Survey on Artificial Intelligence Approaches for Data Visualization

被引:67
作者
Wu, Aoyu [1 ]
Wang, Yun [2 ]
Shu, Xinhuan [1 ]
Moritz, Dominik [3 ]
Cui, Weiwei [2 ]
Zhang, Haidong [2 ]
Zhang, Dongmei [2 ]
Qu, Huamin [1 ]
机构
[1] Hong Kong Univ Sci & Technol, Hong Kong, Peoples R China
[2] Microsoft Res Asia, Beijing 100080, Peoples R China
[3] Carnegie Mellon Univ, HumanComp Interact Inst, Pittsburgh, PA USA
关键词
Data visualization; Task analysis; Artificial intelligence; Taxonomy; Data mining; Computers; Vocabulary; Survey; data visualization; artificial intelligence; data format; machine learning; CHART IMAGES; VISUAL INFORMATION; DATA EXPLORATION; GENERATION; INFOGRAPHICS; GRAMMAR;
D O I
10.1109/TVCG.2021.3099002
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Visualizations themselves have become a data format. Akin to other data formats such as text and images, visualizations are increasingly created, stored, shared, and (re-)used with artificial intelligence (AI) techniques. In this survey, we probe the underlying vision of formalizing visualizations as an emerging data format and review the recent advance in applying AI techniques to visualization data (AI4VIS). We define visualization data as the digital representations of visualizations in computers and focus on data visualization (e.g., charts and infographics). We build our survey upon a corpus spanning ten different fields in computer science with an eye toward identifying important common interests. Our resulting taxonomy is organized around WHAT is visualization data and its representation, WHY and HOW to apply AI to visualization data. We highlight a set of common tasks that researchers apply to the visualization data and present a detailed discussion of AI approaches developed to accomplish those tasks. Drawing upon our literature review, we discuss several important research questions surrounding the management and exploitation of visualization data, as well as the role of AI in support of those processes. We make the list of surveyed papers and related material available online at.
引用
收藏
页码:5049 / 5070
页数:22
相关论文
共 147 条
  • [1] Al-Zaidy RA, 2016, WORKSH 30 AAAI C ART, P29
  • [2] Al-Zaidy RA, 2017, AAAI CONF ARTIF INTE, P4644
  • [3] DataVizard: Recommending Visual Presentations for Structured Data
    Ananthanarayanan, Rema
    Lohia, Pranay K.
    Bedathur, Srikanta
    [J]. PROCEEDINGS OF THE 21ST WORKSHOP ON THE WEB AND DATABASES (WEBDB 2018), 2018,
  • [4] [Anonymous], COMP VIS
  • [5] [Anonymous], 2017, J OPEN SOURCE SOFTW, DOI DOI 10.21105/JOSS.00235
  • [6] [Anonymous], VIS MEETS AI WORKSH
  • [7] Beagle: Automated Extraction and Interpretation of Visualizations from the Web
    Battle, Leilani
    Duan, Peitong
    Miranda, Zachery
    Mukusheva, Dana
    Chang, Remco
    Stonebraker, Michael
    [J]. PROCEEDINGS OF THE 2018 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2018), 2018,
  • [8] Quality Metrics for Information Visualization
    Behrisch, M.
    Blumenschein, M.
    Kim, N. W.
    Shao, L.
    El-Assady, M.
    Fuchs, J.
    Seebacher, D.
    Diehl, A.
    Brandes, U.
    Pfister, H.
    Schreck, T.
    Weiskopf, D.
    Keim, D. A.
    [J]. COMPUTER GRAPHICS FORUM, 2018, 37 (03) : 625 - 662
  • [9] Representation Learning: A Review and New Perspectives
    Bengio, Yoshua
    Courville, Aaron
    Vincent, Pascal
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (08) : 1798 - 1828
  • [10] Vis-a-Vis: Visual Exploration of Visualization Source Code Evolution
    Bolte, Fabian
    Bruckner, Stefan
    [J]. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2021, 27 (07) : 3153 - 3167