"Assessing the Impact of Science Funding," by Julia Lane, from the June 5 Science, ends with a gratifying shout-out to visualization as an essential part of the scientific process:
A related intellectual investment is to advance understanding of how to convey complex answers about the impact of science investments to the public. Emerging visualization techniques seem to be more effective than tables and digital slide presentations at communicating the ways in which science investments bear fruit across a range of topics and disciplines. However, although visual representations are intuitively appealing, it is not clear what they convey: The scientific foundations upon which they are based are not fully developed. U.S.-funded research is thus moving beyond the science of simple mapping to leverage the science of visual analytics which has hitherto been used to "make sense" and describe the impact of terrorist, rather than scientific, networks. Just as John Snow used maps in 1854 to identify the waterborne source of cholera, researchers in the field are combining "the art of human intuition and the science of mathematical deduction to perceive patterns and derive knowledge and insight from them."
This follows nicely on yestoday's State of the Innovation Summit, especially the comments of presenter Ben Fry, who noted the importance of finding effective ways to visualize the modern information glut - not only for relatively straightforward data like ocean temperature or population density, but for nonintuitive data sets on huge scales, like the economy.
Lane's full article, which is mainly about the science of innovation policy, is here.
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I was having a discussion with some colleagues the other day about this very topic, in the context of the absolutely staggering amounts of data that come out of "next generation" nucleic acid sequencing machines. One experimental run yields between 0.5 and 1 terabyte of sequence data. How the fuck do you make any sense of it?
We're entering a scientific era where identifying and filtering out unneeded or insignificant data is more important and difficult than gathering data in the first place. It's kind of scary, because a lot of people don't really think past data collection to how they are going to find meaningful patterns.
It's about time the scientific mind opens up! I have always been heavily involved in scientific research and data collection and I have always encountered a deep frustration with my colleagues and especially with my superiors who would have blatant evidence of "para-normal" occurrences right in front of their eyes only to shove it aside requesting more proof. Inductive reasoning is not not being used in its optimal form and as science "progresses" we regularly seem to be taking steps back!
There's a book I read recently that was passed to me by a good friend entitled "The Evolutionary Glitch". It's not well known but you can Google it if you want to get it. This book not only helped me understand why the people around me were so closed-minded but also helped me learn to use my personal intuitive capacities to my benefit. Since then, I have stepped away from the lab in which I worked and have initiated my own research in which the art of human intuition is embraced for initial insights (then the hard research come in).