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4.3 Summary
In this section, we introduce an emerging use of interactive visualization: collab-
orative visual analysis across space and time. The Web has opened up new possi-
bilities for large-scale collaboration around visualizations and holds the potential
for improved analysis and dissemination of complex data sets. A new class of
systems explores these possibilities, enabling web-based data access, exploration,
view sharing, and discussion around both static and interactive visualizations.
Already, these systems exhibit the promise of web-based collaboration, provid-
ing examples of collective data analysis in which group members combine their
knowledge to make sense of observed data trends and disseminate their findings.
Still, many research questions remain on how to structure collaboration. For
example, how can we move beyond simple textual comments to better scale and
integrate diverse contributions? Interested readers may wish to consult [96,46,43]
for further discussions on this topic. As described in section 2, another open
question is how to design for particular audiences. Different scenarios - includ-
ing scientific collaboration, business intelligence, and public data consumption -
involve different skill sets, scales of collaboration, and standards of quality. Going
forward, case studies in these scenarios are crucial to better tailoring visualiza-
tion tools to such varied audiences. By enabling users to collectively explore
data, share views and findings, and debate competing hypotheses, the resulting
collaborative visual analysis systems hold the potential to improve the number
and quality of insights gained from our ever-increasing collections of data.
5Conluon
The adoption of visualization technologies by people from different walks of life
has important implications for visualization research and development. Visual-
ization construction tools are lowering barriers to entry, resulting in end-user
created visualizations of every kind of data set imaginable. Concurrently, new
technologies enabling collaborative use of visualizations in both physical and
online settings hold the potential to change the way we explore, analyze, and
communicate. In this paper, we have sought to identify these emerging trends
and provide preliminary design considerations for advancing the state-of-the-art
of visualization and visual analytic tools.
As a parting comment, we note that the release of visualization tools “into
the wild” will undoubtedly result in a plethora of unexpected developments.
Equipped with new creation and collaboration tools, users will almost certainly
re-appropriate these technologies for unexpected purposes. Already, use of sys-
tems like Many-Eyes has revealed new genres of data-oriented play and self-
expression that complement more traditional analytic activities.
As researchers, it is imperative that we interface with these developments
in a productive fashion. It is likely that visualization tools will not only be
used in unexpected ways, but in ways we actively dislike. As new audiences
are exposed to visualization technologies, “bad” or “chart junk” visualizations
will be generated. Furthermore, visualizations will be used to support actions
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