Biology Reference
In-Depth Information
alternative splicing tool, hoped—upon gaining her PhD—to fi nd a posi-
tion working on visualization tools, rather than in a traditional biologi-
cal laboratory. In an interview, she described her view of visualization
tools in biology:
I kinda believe that if people could explore their data in an un-
biased fashion they might fi nd interesting things. Often how we
work as scientists is that you create some hypothesis, . . . and
then we go look for statistical evidence of that. But if you could
go and look at your data, you might actually see patterns . . .
that you didn't have before. . . . What I am talking about is a
tool that would facilitate people's discovery and facilitate people
being actually able to explore and navigate their data.
For Monica, this was a new and exciting fi eld, since the need to use
such tools had arisen from the massive growth of biological data in the
last few decades. Moreover, in her view, visualization was not about
presenting or communicating data—making pretty pictures—but about
creating images in a way that would help directly with research. Indeed,
it had the potential to create an “unbiased” and hypothesis-free way of
doing biology. Once again, this notion of “objectivity” is not based on
using a computer to make a true-to-nature image, or “mechanical ob-
jectivity”; rather, it is about using visualization tools to create a kind of
“free play” in which objects fall into juxtapositions that produce sur-
prising but insightful results.
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The images produced may be consid-
ered “unbiased” because they place objects in new structures and new
relationships with one another. This sort of objectivity is based on the
notion that the user-biologist can use the images to navigate around and
connect up his or her data in an unconstrained way and hence be led
toward perceiving true relationships.
Through Monica, I was introduced to a small group of people who
circulated between biology and art, between the Broad Institute and the
MIT Media Lab. They were all thinking about how to use images to
represent biological data and solve biological problems. One of them,
Benjamin Fry, completed his dissertation at the MIT Media Lab in 2004
and continued to work on problems of representing scientifi c data. His
thesis, “Computational Information Design,” called for the foundation
of a new fi eld that would bring together information visualization, data
mining, and graphic design to address problems in the visualization of
complex data.
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In Fry's view, the need for images is a direct product of
the growing volume of biological data:
