skip to main content
10.1145/1978942.1979407acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
research-article

CommentSpace: structured support for collaborative visual analysis

Authors Info & Claims
Published:07 May 2011Publication 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.

Skip Supplemental Material Section

Supplemental Material

paper310.mov

mov

86 MB

References

  1. A. D. Balakrishnan, S. R. Fussell, and S. Kiesler. Do visualizations improve synchronous remote collaboration? In ACM CHI, pages 1227--"1236, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Y. Benkler. Coase's penguin, or, linux and the nature of the firm. Yale Law Journal, 112:369, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  3. D. Billman, G. Convertino, J. Shrager, P. Pirolli, and J. Massar. Collaborative intelligence analysis with cache and its effects on information gathering and cognitive bias. In HCI Consortium Workshop, 2006.Google ScholarGoogle Scholar
  4. M. Bloch, S. Carter, J. Corum, A. Cox, and M. Ericson. Jacksons billboard rankings over time (interactive graphic). New York Times interactive graphic, June 2009.Google ScholarGoogle Scholar
  5. What's your college degree worth? Bloomberg Businessweek interactive table, June 2010.Google ScholarGoogle Scholar
  6. J.Carroll, M.Rosson, G.Convertino, and C.Ganoe.Awareness and teamwork in computer-supported collaborations. Interacting with Computers, 18(1):21--"46, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. E. Chi and T. Mytkowicz. Understanding the efficiency of social tagging systems using information theory. In ACM Hypertext, pages 81--"88, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. T. Chklovski, V. Ratnakar, and Y. Gil. User interfaces with semi-formal representations: a study of designing argumentation structures. In ACM IUI, pages 130--"136, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. H. Clark and S. Brennan. Grounding in communication. Perspectives on socially shared cognition, 13:127--"149, 1991.Google ScholarGoogle Scholar
  10. Data360. http://data360.org.Google ScholarGoogle Scholar
  11. N. Diakopoulos, S. Goldenberg, and I. Essa. Videolyzer: quality analysis of online informational video for bloggers and journalists. In ACM CHI, pages 799--"808, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. P.DourishandV. Bellotti. Awareness and coordination in shared workspaces. In ACM CSCW, page 114, 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. R.Eccles, T.Kapler, R.Harper, and W.Wright. Stories in GeoTime. Information Visualization, 7(1):3--"17, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. D.Gergle, R.Kraut, and S.Fussell. Language efficiency and visual technology: Minimizing collaborative effort with visual information. Journal of Language and Social Psychology, 23(4):491, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  15. S.Golder and B.Huberman. Usage patterns of collaborative tagging systems. Journal of Information Science, 32(2):198, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Google Public Data Explorer.http://www.google.com/publicdata/.Google ScholarGoogle Scholar
  17. T.Gordon and N.Karacapilidis. The Zeno argument at ion framework. In ACM ICIAL, pages 10--"18, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. J.Heer and M.Agrawala. Design considerations for collaborative visual analytics. Information Visualization, 7(1):49--"62, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. J.Heer, F.Viegas, and M.Wattenberg. Voyagers and voyeurs: Supporting asynchronous collaborative visualization. Communications of the ACM, 52(1):87--"97, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. N.Kong and M.Agrawala. Perceptual interpretation of ink annotations on line charts. In ACM UIST, pages 233--"236, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. K.Luther, S.Counts, K.Stecher, A.Hoff, and P.Johns. Pathfinder:an online collaboration environment for citizen scientists. In ACM CHI, pages 239--"248, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. M. McKeon. Harnessing the Web Information Ecosystem with Wiki-based Visualization Dashboards. IEEE TVCG, pages 1081--"1088, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. I.Mistrik, B.P.Springer, S.J.B.Shum, S.J.B.Shum, A.M.Selvin, A. M. Selvin, M. Sierhuis, M. Sierhuis, J. Conklin, J. Conklin, C. B. Haley, C. B. Haley, B. Nuseibeh, and B. Nuseibeh. Hypermedia support for argumentation-based rationale. In 15 Years on from gIBIS and QOC. In: Rationale Management in Software Engineering (Eds, pages 111--"132. Springer-Verlag: Berlin, 2006.Google ScholarGoogle Scholar
  24. K. Neuendorf. The content analysis guidebook. Sage Publications, Inc, 2002.Google ScholarGoogle Scholar
  25. A. Perer and B. Shneiderman. Systematic yet flexible discovery: guiding domain experts through exploratory data analysis. In ACM IUI, pages 109--"118, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. N. J. Pioch and J. O. Everett. Polestar: collaborative knowledge management and sensemaking tools for intelligence analysts. In ACM CIKM, pages 513--"521, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. P. Pirolli. Information foraging theory: Adaptive interaction with information. Oxford University Press, USA, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. TIBCO Spotfire Decision Site. http://spotfire.tibco.com.Google ScholarGoogle Scholar
  29. TableauServer.http://tableausoftware.com.Google ScholarGoogle Scholar
  30. J. Thomas and K. Cook. Illuminating the path: The research and development agenda for visual analytics. IEEE Computer Society, 2005.Google ScholarGoogle Scholar
  31. F. Viégas, M. Wattenberg, M. McKeon, F. Van Ham, and J. Kriss. Harry potter and the meat-filled freezer: A case study of spontaneous usage of visualization tools. In Proc. HICSS, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. F.Viégas, M.Wattenberg, F.VanHam, J.Kriss, and M.McKeon. Manyeyes: a site for visualization at internet scale. IEEE TVCG, 13(6):1121--"1128, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. M. Wattenberg, F. Viégas, and K. Hollenbach. Visualizing activity on wikipedia with chromograms. Human-Computer Interaction--"INTERACT 2007, pages 272--"287, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. W. Wright, D. Schroh, P. Proulx, A. Skaburskis, and B. Cort. The Sandbox for analysis: concepts and methods. In ACM CHI, page 810, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. CommentSpace: structured support for collaborative visual analysis
      Index terms have been assigned to the content through auto-classification.

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • 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

        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]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 7 May 2011

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        CHI '11 Paper Acceptance Rate410of1,532submissions,27%Overall Acceptance Rate6,199of26,314submissions,24%

        Upcoming Conference

        CHI '24
        CHI Conference on Human Factors in Computing Systems
        May 11 - 16, 2024
        Honolulu , HI , USA

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader