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Night sky telescopeDr. Gerry Santoro, one of our most celebrated creative teachers in IST, and I share a mutual interest: we’re both amateur astronomers.  While Gerry is still an active observer, I’ve devoted little time in recent years to astronomy. But as I was growing up, I progressed from naked-eye observations of stars and constellations to making my own telescopes (grinding, polishing, and figuring six-inch mirrors for Newtonian telescopes in our kitchen – to the consternation of my mother) and, ultimately, going to graduate school and developing computer programs for modeling the structure and evolution of stars.

Although I never worked as a professional astronomer or astrophysicist, it strikes me that my personal evolution in the field mirrors the trajectory of many sciences affected by information technology. New sciences such as biology, botany, astronomy and physics began with amateur scientists collecting personal observations and collating and sorting the data, creating taxonomies, categorizations, and characterizations of the phenomena they observed. Subsequent efforts produced better data through the development of increasingly complex sensing devices: telescopes, microscopes, particle accelerators, and beyond. Ever-evolving computing technologies provide opportunities to develop mathematical models to represent data and to make predictions of phenomena. Finally, as I mentioned in the last post, amateur observers from around the world can take on the role “citizen scientists” to assist in data collection and analysis such as pattern recognition.

How does the role of the scientist evolve with the evolution of a science, particularly as it is impacted by changing information technology?  A modern scientist or student finds themselves in a unique situation.  First, rapid changes in sensing technology make it difficult for a single individual to contribute to a science by making yet another new instrument.  How can an individual student or scientist compete with the Hubble telescope or the CERN large Hadron accelerator?  These instruments are incredibly expensive and require national or multi-national cooperation to develop. Second, huge amounts of data are already available on the web, and advanced instruments can be tasked directly at your desk.  For example, the website slooh allows users to remotely command large size telescopes around the world and download the subsequent data. (Now you know where Gerry gets some of the cool astronomical pictures he puts on Facebook!)  Finally, the existence of cloud-based computing resources and existing mathematical tools such as Mathematica, MATLAB, Maplesoft, and others make it easy to apply complex analysis techniques to existing data.

If all of this is available and accessible to any armchair scientist, what is the role of the student or scientist? I suggest that a new emerging role for scientists is to determine what questions are worth asking and what data and models are pertinent to develop an answer. It is easy, for example, to access geographical information about countries and regions, and to apply statistical modeling methods to these data. But without understanding the types of questions worth asking, how to obtain and characterize pertinent data, and what methods are valid for the analysis, one can come up with blindingly obvious results such as, “There is not much vegetation in highly populated cities.”

One of our goals in IST is to develop skills and knowledge for this new era. Dr. Lee Gile’s expertise on search engines, Dr. Luke Zhang and Dr. Guoray Cai’s research on data visualization, and Dr. John Yen’s work on artificial intelligence, are just a few of the examples of ongoing IST research that seeks to develop, not only new techniques, but new ways of understanding how to access, interpret, and utilize data and models to answer meaningful questions.  Still other IST faculty members perform research to understand the human “landscape.”

This is not a new perspective.  In the early 1600s, Galileo wasn’t the only European astronomer who pointed newly constructed telescopes at the sky and observed the planet Jupiter apparently surrounded by four tiny stars.  But he was the first to ask himself why these tiny stars (which we now know as Jupiter’s four largest moons; Io, Europa, Ganymede, and Callisto) appeared to move about Jupiter, and what were the implications of this motion for the Earth relative to the sun.  Galileo’s observations and questions “dethroned” the Earth and mankind from the center of the universe.

With a universe of data, sensors, computing power, and models at your fingertips, what questions will you ask that may ultimately dethrone some of our current, firmly held beliefs?

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