I can’t tell you how many times I’ve wandered, somewhat aimlessly, on websites like Google Scholar, perpetually overwhelmed by the extraordinary expanse of information that’s available on any topic you’d care to keyword. Pages upon pages of professional articles and books brought up before your eyes within seconds solely by the prompt of one or a few words. How can any person, scientist or layperson alike, hope to read through it all?
Even though I am a young scientist, with much green behind my exuberant ears, I have already started noticing a big problem in science: THERE IS TOO MUCH INFORMATION. Don’t get me wrong, on some level one would think that more equals better, and having a vast array of information potentially at one’s finger tips is an extraordinary boon which these manied fields have rarely had before the advent of the internet. However, it’s impossible for a single scientist or even group of scientists to stay up to date on all publications potentially relating to their topics of interest, let alone those topics which may prove unexpectedly relevant in a translational sense.
There’s tons of data just sitting there, doing absolutely nothing beyond what its original investigators prefer to do with it. (Let’s face it: articles are often cited more by their own authors than researchers unaffiliated with the original study.) But that means there’s vast amounts of money wasted, gobs of time and energy spent for little return, and while there are currently efforts to build better databases to enhance data sharing, etc., the one thing I haven’t heard mention is the need for more PEOPLE to go sifting through all this data to try and make some organizational sense of it.
We need synthesizers, actual humans, who sit down, read, and connect the dots. While computers are an extraordinary invention of our modern times and are changing how we live and interact, we still need the human brain to put the proverbial 2 and 2 together. Big data just won’t make do.
For the present moment, I’m going to call these people “Research Synthesists”– for want of an accepted term. I could foresee them holding faculty positions, such that they do all that the typical researcher does except they don’t perform the labwork but instead read, write, and publish what they’ve synthesized. Or perhaps they’re hired by private business. They could also expand upon a bioinformatic repertoire, combining brain power with computer power to relate disparate nodes. In addition, I could foresee lower level synthesists being hired by individual labs to do more thorough legwork when it comes to combing the literature for relevant information to their topic of interest. Wouldn’t it be wonderful, as a PI, to have a dedicated personnel whose sole purpose is to read and provide you insight?
There is so much research that has already been done that’s just sitting there. And yet there’s such heavy focus in the research communities on constantly producing more information, and not making use of what we’ve already got. –In first world countries, we have a terrible habit of wasting food. A recent stat I heard on tv said we throw approximately a third of our food away. But how much research are we throwing away by the fact that so much of it is left to sit, relatively unused?
It’s a waste of science, a waste of man-power, and a blindness to an obvious wealth of information which lies dormant, untapped, but ready for use with the proper legwork. While it’s vital that we perform experiments to test ideas, I am also a big believer in Armchair Science, perhaps because I am pragmatically lazy: Why do all this labwork when you could let your fingers do the walking instead?
Repetition is vital to science, but redundancy is wasteful. No successful business could survive the way our system currently works. The waste of such a vast amount of product would cripple and drive it into bankruptcy. And yet we’re still afloat because we are not judged solely by product alone– which is a good thing to some extent. As a scientist who is passionate about knowledge and the search for it, I would deplore a business-model approach to science, which would be so prone to quashing creativity and ingenuity. BUT having a romanticized notion of truthseeking does not prevent us from pragmatism. And it doesn’t prevent us from savoring each morsel of hard-fought information to its fullest extent.
We are so focused on doing work, designing and performing experiments, and constantly churning out more and more data, that sometimes I think we don’t think enough.