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Cleaning data is often the primary job of the data scientist, and not necessarily the one they signed up for.  While getting the "words" right with computers is important, it is not fraught with the nuance that getting words right with humans is. Across disciplines the same word can have entirely different meanings and this miscommunication is only one aspect of team building that can go awry.

Have you ever read the book Travels with Charley by John Steinbeck? The first part of the book is John Steinbeck talking about his lifelong affliction with wanderlust. I spent a few years living out of a VW camper van, indulging my own wanderlust affliction, so the book quickly claimed a special place in my heart. Steinbeck is such a skilled writer, and he describes the feeling -

James Verdier: Hi, I'm James Verdier and welcome to the American Institute of Biological Sciences’ BioScience Talks which is a forum for integrating the life sciences. On the second Wednesday of each month we discuss the latest bioscience publications. And as a reminder if you'd like to read more point your browser to academic.oup.com/bioscience.

“Good ideas are getting harder to find,” Exaptive CEO Dave King quotes from a recent paper by MIT and Stanford researchers. He points to the skyrocketing number of researchers employed in the U.S. and contrasts it with the inverse slope on a chart monitoring efficiency of researchers along the same timeline. “Those growing number of researchers are failing to produce value that outpaces what we’re spending to innovate.”

Since Exaptive launched in 2011, we’ve worked with many researchers, particularly in medicine and the natural sciences. PubMed®, a medical journal database, pops up repeatedly as a key tool for these researchers to develop hypotheses. It’s a tool built in a search-and-find paradigm with which we’re all familiar. Execute a keyword search. Get a list of results. Visualization can make search - and, therefore, research - much more meaningful.

Faster is different. It sounds strange at first because we expect faster to be better. We expect faster to be more. If we can analyze data faster, we can analyze more data. If we can network faster, we can network with more people. Faster is more, which is better, but more is different.