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Please direct questions to
thought-provoking panel, organized by Theresa-
Marie Rhyne, at IEEE Visualization 2004
addressed the top unsolved problems of visualization.
Two of the invited panelists, Bill Hibbard and Chris
Johnson, addressed scientific visualization problems.
Steve Eick and I identified information visualization
problems. The following top 10 unsolved problems list
is a revised and extended version of the information
visualization problems I outlined on the panel. These
problems are not necessarily imposed by technical bar-
riers; rather, they are problems that might hinder the
growth of information visualization as a field. The first
three problems highlight issues from a user-centered
perspective. The fifth, sixth, and seventh problems are
technical challenges in nature. The last three are the
ones that need tackling at the disciplinary level.
In this article, I broadly define information visualiza-
tion as visual representations of the semantics, or mean-
ing, of information. In contrast to scientific visualization,
information visualization typically deals with non-
numeric, nonspatial, and high-dimensional data.
1. Usability
The usability issue is critical to everyone, especially
in light of successful commercialization stories such as
Spotfire (http://www.spotfire.com/) and Inspire
(http://in-spire.pnl.gov/). Although the overall growth
of information visualization is accelerating, the growth
of usability studies and empirical evaluations has been
relatively slow. Furthermore, usability issues still tend to
be addressed in an ad hoc manner and limited to the
particular systems at hand.
The complexity of the underlying analytic process
involved in most information visualization systems is a
major obstacle; end users cannot see how their raw data
is magically turned into colorful images. The first col-
lection of empirical studies is the 2000 special issue in
International Journal of Human–Computer Studies
Although the number of empirical studies of informa-
tion visualization systems is increasing, designers and
users still need to find empirical evidence that is both
generic and specific enough to inform their decision-
making processes.
Empirical studies tend to use open source and freely
available systems.
A prolonged lack of low-cost, ready-
to-use, and reconfigurable information visualization sys-
tems will have an adverse impact on cultivating the
critical user population. A balanced portfolio of general-
purpose, fully functional information visualization sys-
tems is essential from user- and learning-centered
We need new evaluative methodologies. The major-
ity of existing usability studies heavily relied on method-
ologies that predated information visualization. Such
methodologies are limited because
we cannot expect them to address
critical details specific to informa-
tion visualization needs.
There might be an even more pro-
found reason for the shortage of
usability studies. Information visu-
alization is a visual exploration tool
that enables the user to interact with
the visualized content and compre-
hend its meaning. The comprehen-
sion process is often exploratory in
nature. For example, users can inter-
act with many possible cognitive
paths in the network visualization
shown in Figure 1 and interpret
what they see.
Usability studies
need to address whether users can
recognize the intended patterns.
Chaomei Chen
Drexel University
Top 10 Unsolved Information Visualization Problems
Visualization Viewpoints
Editor: Theresa-Marie Rhyne
July/August 2005
Published by the IEEE Computer Society 0272-1716/05/$20.00 © 2005 IEEE
paths in this
network visual-
ization high-
light how
research topics
are connected
in research on
Because this involves interrelated perceptual–cognitive
tasks, existing methodologies for empirical studies
might not be readily applicable. This observation leads
to the next challenging problem.
2. Understanding elementary
perceptual–cognitive tasks
Understanding elementary and secondary perceptu-
al–cognitive tasks is a fundamental step toward engi-
neering information visualization systems. The general
understanding of elementary perceptual–cognitive
tasks must be substantially revised and updated in the
context of information visualization.
Information retrieval has had a profound impact on
the evolution of information visualization as a field.
Many task analysis and user studies framed interacting
with information visualization as an information
retrieval or an open-ended browsing problem. However,
using browsing and search tasks to study users’ percep-
tual and cognitive needs in the process of interacting
with information visualization is likely to miss the tar-
get. Tasks such as browsing and searching, and even
judging the relevance of information, require a level of
cognitive activities higher than that of identifying and
decoding visualized objects. In this sense, a mismatch
exists between studying the high-level user tasks and
evaluating the usefulness of visualization components.
Studies of elementary perceptual–cognitive tasks
appear in the earlier psychology and statistical graph-
ics literature, including the Cleveland–McGill study and
the work of Treisman on preattentive perceptual tasks.
In the context of information visualization, while
researchers have done considerable work, notably
through Ware’s work in characterizing motion and
stereo depth perception tasks in visualization, we have
a great deal more to accomplish.
Above the elementary perceptual–cognitive task
level, we need to collect a substantial amount of empir-
ical evidence from the new generation of information
visualization systems. The secondary level perceptu-
al–cognitive tasks include the recognition of a cluster of
dots based on their proximity, the identification of a
trend based on a time series of values, or the discovery
of a previously unknown connection. This would echo
the moment of “aha!” when an insightful discovery is
made. For example, what perceptual–cognitive tasks are
in play when we see animated visualizations such as the
one in Figure 2? Studies of individuals’ spatial ability
and fixations of eye movements are approaching this
secondary level.
3. Prior knowledge
This seemingly philosophical problem has many prac-
tical implications. As a vehicle for communicating
abstract information, information visualization and its
users must have a common ground. This is consistent
with the user-centered design tradition in human–com-
puter interaction (HCI). A thought-provoking example
of prior knowledge is the visual message carried by the
Pioneer spacecraft (http://spaceprojects.arc.nasa.gov/
Space_Projects/pioneer/PN10&11.html#plaque). The
intended extraterrestrial audience is assumed to know
modern physics and our solar system. The alien is also
expected to figure out from the line drawings of a man
and woman that the Pioneer is coming in peace from a
small planet. Research in preattentive perception also
studies the role of prior knowledge.
In general, users need two types of prior knowledge
to understand the intended message in visualized
the knowledge of how to operate the device, such as
a telescope, a microscope, or, in our case, an infor-
mation visualization system, and
the domain knowledge of how to interpret the content.
Therefore, design decisions must be made up front in
terms of the level of prior knowledge necessary to under-
stand the visualized information. The prior knowledge
problem can be seen as a need for adaptive information
visualization systems in response to accumulated knowl-
edge of their users.
Solutions to the first two challenges discussed earlier
can reduce the dependence on the first type of prior
knowledge, but they cannot replace the need for the
domain knowledge. In the Pioneer example, if the alien
does not have the expected knowledge of physics and
the ability to make various bold connections, then the
Pioneer’s message is meaningless.
4. Education and training
The education problem is the fourth user-centered
challenge. We are facing the challenge internally and
externally. The internal aspect of the challenge refers to
the need for researchers and practitioners within the
field of information visualization to learn and share var-
ious principles and skills of visual communication and
semiotics. To reach a critical mass, the language of infor-
mation visualization must become comprehensible to its
potential users. Universities should connect undergrad-
uate and graduate programs to more advanced research
programs and development efforts. Regularly revising
existing taxonomies in light of new systems and exem-
plars will consolidate the field’s theoretical foundations.
The external aspect of the challenge refers to the need
for potential beneficiaries outside the immediate field of
information visualization to see the value of information
visualization and how it might contribute to their work
in an innovative way. To insiders, the value of informa-
tion visualization might seem obvious. However,
IEEE Computer Graphics and Applications
3D animated
visualization of
the evolution of
research in mad
cow disease
showing the
importance of
secondary level
cognitive tasks.