The Data Problem in Scientific Research

A lot of us who are not academicians make assumptions about science in general that are not at all accurate. Unlike our assumed belief that science is organized and well structured, it is not. In fact, the vast majority of data that has been gathered has not even been reviewed, much less studied. Even that data that has been incorporated into papers is far from being understood. 

"As the neurobiologist Steven Rose observed in 1998 (and nothing much has changed), neuroscience had generated oceans of data but no theory to make sense of them." and this is only one sub-specialty of one of literally dozens of fields of study. We have lots of data/information but neither understand it nor do we have any idea of what to actually do with it. 

The problem (again making assumptions) should be a priority in the sciences. It is intuitive that if we are engaged in an activity supposedly aimed at generating knowledge and more importantly, understanding and objective benefits, that endpoint should be the focus of at least the bulk of scientific activity. It is not. 

The bulk of academic activity produces degrees, and not much more. While everything we view as important today is generally due to scientific breakthroughs, such breakthroughs are not happening nor making much of a dent on the problems we face today, nor are they seriously changing our perceptions or activity in a day to day world. This is not an acceptable situation. 

Money is scarce in today's academic environment, and almost nothing is being spent on generating any new theories or approaches to already gathered data to organize it into usable theories and structures to both analyze and handle the mountain of data that is literally "just sitting there". Most all resources go toward gathering new data, not looking over (again) the data we have lying around. One does not usually get a desired doctorate or graduate degree looking at someone else's hard won data. 

This has to change and the idea of an uber-librarian whose entire career is reviewing , categorizing and organizing this latent data into usable and coherent formats that researchers can actually use seems to have some merit. Our schools need to develop the skills of  intuitive logic and critical analysis of data. We push for people to get new data, but fail then to do anything with it. We need to train people in archival science, data analysis and just plain secretarial filing skill in a scientific/ technical concentrated career path. 

There are literally thousands of potential scientific breakthroughs sitting in record files that no one is actually looking at. Think of it as siting on a goldmine that nobody is mining, because they are looking for new mines. 

And so it goes.....