Voyagers and Voyeurs:
By Jeffrey Heer, Fernanda B. Viégas, and Martin Wattenberg
This article describes mechanisms for asynchronous collaboration in the context of information visualization, recasting
visualizations as not just analytic tools, but social spaces.
We contribute the design and implementation of
a Web site supporting asynchronous collaboration across a
variety of visualization types. The site supports view sharing,
discussion, graphical annotation, and social navigation and
includes novel interaction elements. We report the results
of user studies of the system, observing emergent patterns
of social data analysis, including cycles of observation and
hypothesis, and the complementary roles of social navigation and data-driven exploration.
Visual representations of information often lead to new
insights by enabling viewers to see data in context, observe
patterns, and make comparisons. In this way, visualizations
leverage the human visual system to improve our ability to
process large amounts of data. Card et al.
6 describe how
visualization supports the process of sensemaking, in which
information is collected, organized, and analyzed to form
new knowledge and inform further action. They emphasize
the ways visualization exploits an individual’s visual perception to facilitate cognition.
In practice, however, sensemaking is often also a social
process. People may disagree on how to interpret the data
and may contribute contextual knowledge that deepens
understanding. As participants build consensus or make
decisions they learn from their peers. Furthermore, some
data sets are so large that thorough exploration by a single
person is unlikely. This suggests that to fully support sensemaking, visualizations should also support social interaction. In this spirit, a recent report23 names the design of
collaborative visualization tools as a grand challenge for
These considerations are not just hypothetical. For
example, the manager of a business group in our company
described to us how quarterly reports are disseminated
within his organization via e-mail. Heated discussion
takes place around charts and graphs as the group debates
the causes of sales trends and considers possible future
actions. However, writing about particular trends or views
is difficult, involving awkward references to attached
spreadsheets from the e-mail text. Furthermore, the discussion is scattered and disconnected from the visualizations,
making it difficult for newcomers to catch up or others to
review and summarize the discussion thus far. According to
the manager of the group, the analysis process could benefit from a system for sharing, annotating, and discussing
the visualized data.
Similar scenarios appear in other domains. Moreover,
experiences with deployments of visualizations hint at
ways that social phenomena already occur around visualizations. Wattenberg and Kriss27 describe the response to
NameVoyager, an online visualization of historical baby
name trends. Playful yet often surprisingly deep analysis
appeared on numerous blogs as participants discussed their
insights and hypotheses. Observing the use of a physical
installation of the Vizster social network visualization, Heer18
noted that groups of users, spurred by storytelling of shared
memories, spent more time exploring and asked deeper
analysis questions than individuals. Similarly, Viégas et al.
found that users of the PostHistory e-mail archive visualization immediately wanted to share views with friends and
family and engage in storytelling.
While suggestive, these observations provide only a circumstantial understanding of the social aspects of asynchronous analysis around visualizations. In the case of the
NameVoyager and PostHistory, the findings were essentially
accidental. Vizster was designed for playful interaction, but
in a synchronous and less analytic context. It would therefore be valuable to replicate these findings to deepen our
understanding of this type of interaction.
Furthermore, if social interaction is an important accompaniment to data visualization, it is natural to look for ways
to support and encourage it. To address both these goals,
we designed and implemented a Web site,
at group exploration of demographic data. The site provides
a suite of interactive visualizations and facilitates collaboration through view bookmarking, doubly linked discussions,
graphical annotation, saved bookmark trails, and social
navigation through comment listings and user profiles. We
then conducted user studies to observe closely how people
engage in social data analysis. The studies also allowed us
to evaluate the new design elements in the site and suggest
directions for future work.
A previous version of this paper was published in the
Proceedings of the SIGCHI Conference on Human Factors in
Computing Systems, April 2007.