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CommentSpace: structured support for collaborative visual analysis

Authors:

Wesley Willett,

Joseph Hellerstein,

Maneesh AgrawalaAuthors Info & Claims

CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 3131 - 3140

https://doi.org/10.1145/1978942.1979407

Published: 07 May 2011 Publication History

Abstract

Collaborative visual analysis tools can enhance sensemaking by facilitating social interpretation and parallelization of effort. These systems enable distributed exploration and evidence gathering, allowing many users to pool their effort as they discuss and analyze the data. We explore how adding lightweight tag and link structure to comments can aid this analysis process. We present CommentSpace, a collaborative system in which analysts comment on visualizations and websites and then use tags and links to organize findings and identify others'" contributions. In a pair of studies comparing CommentSpace to a system without support for tags and links, we find that a small, fixed vocabulary of tags (question, hypothesis, to-do) and links (evidence-for, evidence-against) helps analysts more consistently and accurately classify evidence and establish common ground. We also find that managing and incentivizing participation is important for analysts to progress from exploratory analysis to deeper analytical tasks. Finally, we demonstrate that tags and links can help teams complete evidence gathering and synthesis tasks and that organizing comments using tags and links improves analytic results.

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Cited By

Kauer TAkbaba DDörk MBach B(2025)Discursive Patinas: Anchoring Discussions in Data VisualizationsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345633431:1(1246-1256)Online publication date: Jan-2025
https://doi.org/10.1109/TVCG.2024.3456334
Braga DSilva MLima RBarbosa GBarbosa S(2024)VisStoryMaker: supporting non-expert analysts in visually exploring datasets and communicating insights with visual annotations and data storiesProceedings of the XXIII Brazilian Symposium on Human Factors in Computing Systems10.1145/3702038.3702113(1-15)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3702038.3702113
Kim HLe KLim GKim DHong YKim J(2024)DataDive: Supporting Readers' Contextualization of Statistical Statements with Data ExplorationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645155(623-639)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645155
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Index Terms

CommentSpace: structured support for collaborative visual analysis
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Computer supported cooperative work
2. Social and professional topics
  1. Professional topics
    1. Computing and business
      1. Computer supported cooperative work

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM Conferences

CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

May 2011

3530 pages

ISBN:9781450302289

DOI:10.1145/1978942

General Chair:
Desney Tan
Microsoft Research
,
Program Chairs:
Geraldine Fitzpatrick
Vienna University of Technology
,
Carl Gutwin
University of Saskatchewan
,
Bo Begole
PARC
,
Wendy A. Kellogg
IBM Research

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

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Published: 07 May 2011

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CHI '11

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CHI '11: CHI Conference on Human Factors in Computing Systems

May 7 - 12, 2011

BC, Vancouver, Canada

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CHI '11 Paper Acceptance Rate 410 of 1,532 submissions, 27%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

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https://doi.org/10.1109/TVCG.2024.3456334
Braga DSilva MLima RBarbosa GBarbosa S(2024)VisStoryMaker: supporting non-expert analysts in visually exploring datasets and communicating insights with visual annotations and data storiesProceedings of the XXIII Brazilian Symposium on Human Factors in Computing Systems10.1145/3702038.3702113(1-15)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3702038.3702113
Kim HLe KLim GKim DHong YKim J(2024)DataDive: Supporting Readers' Contextualization of Statistical Statements with Data ExplorationProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645155(623-639)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645155
Kim HSrinivasan ABrehmer M(2024)Bringing Data into the Conversation: Adapting Content from Business Intelligence Dashboards for Threaded Collaboration Platforms2024 IEEE Visualization and Visual Analytics (VIS)10.1109/VIS55277.2024.00024(81-85)Online publication date: 13-Oct-2024
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Warner JPavel ANguyen TAgrawala MHartmann B(2023)SlideSpecs: Automatic and Interactive Presentation Feedback CollationProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584035(695-709)Online publication date: 27-Mar-2023
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Yen CCheng HXia YHuang Y(2023)CrowdIDEA: Blending Crowd Intelligence and Data Analytics to Empower Causal ReasoningProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581021(1-17)Online publication date: 19-Apr-2023
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Battle LOttley A(2023)What Exactly is an Insight? A Literature Review2023 IEEE Visualization and Visual Analytics (VIS)10.1109/VIS54172.2023.00027(91-95)Online publication date: 21-Oct-2023
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