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to show that their inventions are measurably better than the existing state of
the art.
In broad analytic fields, of which we include InfoVis as a member, the exis-
tence of a ground truth for a problem can greatly facilitate evaluations of value.
For instance, consider the field of computer vision and algorithms for identifying
objects from scenes. It is very easy to create a library of images upon which new
algorithms can be tested. From that, one can measure how well each algorithm
performs and compare results precisely. The TREC [29] and MUC [3] Contests
are examples of this type of evaluation.
Even with a human in the loop, certain fields lend themselves very well to
quantifiable evaluations. Consider systems that support search for particular
documents or facts. Even though different people will perform differently using
a system, researchers can run repeated search trials and measure how often a
person is able to find the target and how long the search took. Averaged over a
large number of human participants, this task yields quantifiable results that can
be measured and communicated quite easily. People or organizations then using
the technology can make well-informed judgments about the value of new tools.
So why is identifying the value of InfoVis so dicult? To help answer that
question, let us turn to what is probably the most accepted definition of InfoVis,
one that comes from Card, Mackinlay, and Shneiderman and that actually is
their definition for “visualization.” They describe visualization as “the use of
computer-supported, interactive visual representations of data to amplify cog-
nition.” [2] The last three words of their definition communicate the ultimate
purpose of visualization, to amplify cognition. So, returning to our discussion
above, is the amplification of cognition something with a ground truth that is
easily and precisely measurable? Clearly it is not and so results the key challenge
in communicating the value of InfoVis.
Further examining the use and purpose of InfoVis helps understand why
communicating its value is so dicult. InfoVis systems are best applied for ex-
ploratory tasks, ones that involve browsing a large information space. Frequently,
the person using the InfoVis system may not have a specific goal or question in
mind. Instead, the person simply may be examining the data to learn more about
it, to make new discoveries, or to gain insight about it. The exploratory process
itself may influence the questions and tasks that arise.
Conversely, one might argue that when a person does have a specific question
to be answered, InfoVis systems are often not the best tools to use. Instead, the
person may formulate his or her question into a query that can be dispatched
to a database or to a search engine that is likely to provide the answer to that
precise question quickly and accurately.
InfoVis systems, on the other hand, appear to be most useful when a person
simply does not know what questions to ask about the data or when the person
wants to ask better, more meaningful questions. InfoVis systems help people to
rapidly narrow in from a large space and find parts of the data to study more
carefully.
Unfortunately, however, activities like exploration, browsing, gaining insight,
and asking better questions are not ones that are easily amenable to establishing
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