I remember my first brush with data science at Colby.
It was 1976, and I was an English major taking an ecology course, partly to meet my distribution requirement, but also because I was interested. The course required us to do a crude (by today’s standards) piece of analysis using the computer.
I ventured from my usual Miller Library haunt to find this singular piece of space-age equipment and located it in a hallway in the spanking new Mudd Science Building. The computer was the size of a chest freezer with a tiny keyboard and a roll of paper that would spew out as it hammered out the data. If only you could figure out how to turn it on.
Standing alone before this mysterious machine, I searched for a switch. Or a button. Or a lever. I tapped it in random places hoping it would magically whir to life. It did not. I crouched to peer into its nooks and crannies. Nothing. The computer remained cold and silent, like a treasure-guarding door baffling Indiana Jones.
Stymied, I had to resort to problem-solving skills that any Professor Benbow-trained Shakespeare student of the time would understand. I waited for a science major to show up.
One eventually did. I watched discreetly as she found the hidden button and started the machine humming. Stepping up after her, I tapped out the assignment, which, if memory serves, involved lots of 1s and 0s. Task completed, I scurried back to familiar territory. Hamlet never looked so good.
Oh, how the world—and Colby—has changed. The relationship between data and scholarship, nascent in my student days, has been a long and fruitful one. Today we have more processing speed in a phone than you could harness with 10,000 of those chest freezers. And we have a universe of data at our fingertips. Being able to convert that data to knowledge is a skill needed and embraced by students of every discipline.
I point this out to make sure you read about the just-announced Data Science Initiative and consider this moment in time. As Professor of Computer Science Bruce Maxwell will tell you, his rapidly expanding department is no longer only for majors. With the new initiative, more students from across disciplines will be trained in coding languages. Faculty in multiple departments will receive funding for new data science courses. All of this will produce graduates who know what data can tell us, whether they’re studying English or art history or economics or genomics—or ecology.
So many questions will be asked, and so many answers will be considered from so many perspectives. And no longer will an English major have to stalk a science student to join the discussion.
We’re all in it together now. Hang on to your hat.
Gerry Boyle ’78, P’06