The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Collaborative visualization: Definition, challenges, and research agenda
Open accessAbstract
The conflux of two growing areas of technology – collaboration and visualization – into a new research direction, collaborative visualization, provides new research challenges. Technology now allows us to easily connect and collaborate with one another – in settings as diverse as over networked computers, across mobile devices, or using shared displays such as interactive walls and tabletop surfaces. Digital information is now regularly accessed by multiple people in order to share information, to view it together, to analyze it, or to form decisions. Visualizations are used to deal more effectively with large amounts of information while interactive visualizations allow users to explore the underlying data. While researchers face many challenges in collaboration and in visualization, the emergence of collaborative visualization poses additional challenges, but it is also an exciting opportunity to reach new audiences and applications for visualization tools and techniques. The purpose of this article is (1) to provide a definition, clear scope, and overview of the evolving field of collaborative visualization, (2) to help pinpoint the unique focus of collaborative visualization with its specific aspects, challenges, and requirements within the intersection of general computer-supported cooperative work and visualization research, and (3) to draw attention to important future research questions to be addressed by the community. We conclude by discussing a research agenda for future work on collaborative visualization and urge for a new generation of visualization tools that are designed with collaboration in mind from their very inception.
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(1999) · Cited by 28,356
Hutchins, E. (1995) · doi:10.7551/mitpress/1881.001.0001 · Cited by 10,801 · cited 2×
“For example, the theory of Group Cognition 13 describes collaborative knowledge building for small groups by focusing on linguistic analysis, Distributed Cognition 14 focuses on social aspects of cognition by analyzing the coordination between individuals and artifacts, and Communities of Practice 15 describe learning…”
Background(2013) · Encyclopedia of Creativity, Invention, Innovation and Entrepreneurship · doi:10.1007/978-1-4614-3858-8_100431 · Cited by 4,799
Clark, H. H., & Brennan, S. E. (1991) · Perspectives on socially shared cognition. · doi:10.1037/10096-006 · Cited by 4,555
Readings in Information Visualization: Using Vision to Think
Card, S. K., Mackinlay, J. D., & Shneiderman, B. (1999) · Cited by 3,935
Illuminating the Path: The Research and Development Agenda for Visual Analytics
Thomas, J. J., & Cook, K. A. (2005) · Cited by 1,770
Collaborative Learning: Cognitive and Computational Approaches
Jones, A. (2000) · Computers & Education · doi:10.1016/s0360-1315(00)00011-7 · Cited by 1,497
Interacting with paper on the DigitalDesk
Wellner, P. (1993) · Communications of the ACM · doi:10.1145/159544.159630 · Cited by 1,074
Cooperstock, J. R. (2009) · Wiley Encyclopedia of Computer Science and Engineering · doi:10.1002/9780470050118.ecse524 · Cited by 802
The Interactive Workspaces project: experiences with ubiquitous computing rooms
Johanson, B., Fox, A., & Winograd, T. (2002) · IEEE Pervasive Computing · doi:10.1109/mprv.2002.1012339 · Cited by 733
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Human-AI Collaboration for UX Evaluation: Effects of Explanation and Synchronization
Fan, M., Yang, X., Yu, T., Liao, Q. V., & Zhao, J. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3512943 · Cited by 81
Han, C., & Isaacs, K. E. (2025) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2024.3456351 · Cited by 8
Metadata
- Authors
- Isenberg, P., Elmqvist, N., Scholtz, J., Cernea, D., Ma, K.-L., & Hagen, H.
- Venue
- Information Visualization
- Publisher
- SAGE Publications
- Published
- 2011-07-29
- Volume
- 10
- Issue
- 4
- Pages
- 310-326
- ISSN
- 1473-8716 (ISSN-L)
- 1473-8724
- OpenAlex
- W2135577168
- Cited by
- 299
- References
- 52
- FWCI
- 18.29
- Type
- journal article
- Language
- en
- Open access
- green
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