armchair oceanography, “data science”, or stats is the new black
I cringe at the thought of calling myself an “armchair oceanographer” because in my mind it equates to less and less time spent in the field and more and more time spent in the confines of an office. At some point in our careers, there comes a time when we face the music. From a fellow colleague and well seasoned oceanographer in the field, I’ve been told there isn’t anything wrong with doing armchair science. What this all means to those of you not familiar with this terminology is that rather than being a field-based ecologist with manipulative experiments or extensive survey plots to count, I spend my days in front of large data sets and experiment with a vast array of working hypotheses to test associations and relationships within my data.
This branch of computational science or biology is now being termed “data science”. A recent NYT article discussed the future job prospects of this field and from what I’ve seen it seems data scientists are going to be a hot commodity in the marketplace. I should be happy right? The immediate answer to this question is both yes and no.
An interesting “infographic” from Wikibon.org presents the application of data science to various fields from social networking to time series. While I agree that data science is the new black, I would urge caution about how it is applied. The mechanics of how data science is carried out are fascinating and involve everything from cloud computing to hacking, programming and high level statistics. This part is the “science” in my opinion. The other side of this equation is the why, or experimental approach if you will. Why do data science? What does it tell us? Do you really want to data mine every facebook profile and related tweet to find out what the next generation is thinking, buying and saying? The philosophical side of me thinks this new branch of science should be grounded in a guiding approach to manage not only the accumulation of data but whether it’s truly worth our data-mining efforts.
Regardless of the ethics, data science is the new sexy. Now, let’s test the significance of this statement… off to the reality of science!