When Science and Journalism Collide
In this era of big data, each and every one of us is the source, and some would argue – owner, of reams of data. Where we live, how much we exercise, what kind of healthcare we get, what we’ve bought and read online, all could end up as part of a massive database somewhere, ripe for the picking.
That can be cause for concern, or excitement, depending on your point of view and who’s doing the picking.
It could be an internet provider trying to place the right ads for you to see, or a scientist trying to cure cancer, or a journalist trying to root out corruption.
Journalists are increasingly doing their own number-crunching and reporting on it, rather than asking scientists to tell them what they’ve found. Call it data journalism, or computational journalism, or knowledge-base journalism, it’s a hot field these days, with top journalism schools offering dual degrees and specialized training in computer programming and statistical analysis.
Some journalists have also begun calling for the adoption of aspects of the scientific method, particularly the practices of collaborating, sharing data, citing reference sources, and aiming for reproducibility. There are fundamental differences between science and journalism that make complete co-option of scientific method infeasible, even undesirable.
But if journalists are analyzing data, drawing conclusions, and doing so in a scientifically rigorous way, it begs the question: where is the line between scientist and journalist? And does it matter if we blur it?
Elizabeth Bruce, co-founder and executive director of the Big Data Initiative at MIT.
Nathan Wilson, Director of the Center for Library and Informatics at the Marine Biological Laboratory and Director of the Biodiversity Informatics Component of the Encyclopedia of Life.
Dan Kennedy - assistant professor at Northeastern University’s School of Journalism, author of the Media Nation blog and “The Wired City: Reimagining Journalism and Civic Life in the Post-Newspaper Age.”
Jonathan Stray - computer scientist, professional journalist, teaches computational journalism at Columbia University and leads the Overview Project – an open-source tool to help journalists organize and analyze large collections of documents.