article

Survey of Surveys SoS - Mapping The Landscape of Survey Papers in Information Visualization

Authors:

Robert S. LarameeAuthors Info & Claims

Computer Graphics Forum, Volume 36, Issue 3

Pages 589 - 617

https://doi.org/10.1111/cgf.13212

Published: 01 June 2017 Publication History

Abstract

Information visualization as a field is growing rapidly in popularity since the first information visualization conference in 1995. However, as a consequence of its growth, it is increasingly difficult to follow the growing body of literature within the field. Survey papers and literature reviews are valuable tools for managing the great volume of previously published research papers, and the quantity of survey papers in visualization has reached a critical mass. To this end, this survey paper takes a quantum step forward by surveying and classifying literature survey papers in order to help researchers understand the current landscape of Information Visualization. It is, to our knowledge, the first survey of survey papers SoS in Information Visualization. This paper classifies survey papers into natural topic clusters which enables readers to find relevant literature and develops the first classification of classifications. The paper also enables researchers to identify both mature and less developed research directions as well as identify future directions. It is a valuable resource for both newcomers and experienced researchers in and outside the field of Information Visualization and Visual Analytics.

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cover image Computer Graphics Forum

Computer Graphics Forum Volume 36, Issue 3

June 2017

639 pages

ISSN:0167-7055

EISSN:1467-8659

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The Eurographs Association & John Wiley & Sons, Ltd.

Chichester, United Kingdom

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Published: 01 June 2017

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Li HWang YQu H(2024)Where Are We So Far? Understanding Data Storytelling Tools from the Perspective of Human-AI CollaborationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642726(1-19)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642726
Shen LShen ELuo YYang XHu XZhang XTai ZWang J(2023)Towards Natural Language Interfaces for Data Visualization: A SurveyIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.314800729:6(3121-3144)Online publication date: 1-Jun-2023
https://dl.acm.org/doi/10.1109/TVCG.2022.3148007
Alharbi MLaramee RCheesman T(2022)TransVis: Integrated Distant and Close Reading of Othello TranslationsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.301277828:2(1397-1414)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1109/TVCG.2020.3012778
Rahman SBendre MLiu YZhu SSu ZKarahalios KParameswaran A(2021)NOAHProceedings of the VLDB Endowment10.14778/3447689.344770114:6(970-983)Online publication date: 12-Apr-2021
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Fiedler CScheibel WLimberger DTrapp MDöllner JBurch MWestenberg MNguyen QZhao Y(2020)Survey on user studies on the effectiveness of treemapsProceedings of the 13th International Symposium on Visual Information Communication and Interaction10.1145/3430036.3430054(1-10)Online publication date: 8-Dec-2020
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Chotisarn NMerino LZheng XLonapalawong SZhang TXu MChen W(2020)A systematic literature review of modern software visualizationJournal of Visualization10.1007/s12650-020-00647-w23:4(539-558)Online publication date: 1-Aug-2020
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Kim SPost FZara J(2018)Incorporating visualization research in introductory programming courseProceedings of the 39th Annual European Association for Computer Graphics Conference: Education Papers10.5555/3297765.3297768(9-16)Online publication date: 16-Apr-2018
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