Database Reference
In-Depth Information
The current leadership, all the way down to the reporters, who are the reason
for existence of the company, is very curious about “the digital,” broadly con-
strued. And that means: How does journalism look when you divorce it from
the medium of communication? Even the word “newspaper” presumes that
there's going to be paper involved. And paper remains very important to The
New York Times not only in the way things are organized—the way even the
daily schedule is organized here— but also conceptually. At the same time, I
think there are a lot of very forward-looking people here, both journalists and
technologists, who are starting to diversify the way that The New York Times
communicates the news.
To do that, you are constantly doing experiments. And if you're doing experi-
ments, you need to measure something. And the way you measure things right
now, in 2014, is via the way people engage with their products. So from web
logs to every event when somebody interacts with the mobile app, there are
copious, copious data available to this company to figure out: What is it that
the readers want? What is it that they value? And, of course, that answer could
be dynamic. It could be that what readers want in 2014 is very different than
what they wanted in 2013 or 2004. So what we're trying to do in the Data
Science group is to learn from and make sense of the abundant data that The
New York Times gathers.
Gutierrez: When did you realize that you wanted to work with data as
a career?
Wiggins: That happened one day at graduate school while having lunch with
some other graduate students, mostly physicists working in biology. Another
graduate student walked in brandishing the cover of Science magazine, 3 which
had an image of the genome of Haemophilus influenzae. Haemophilus influenzae
is the first sequenced freely living organism. This is a pathogen that had been
identified on the order of 100 years earlier. But to sequence something means
that you go from having pictures of it and maybe experiments where you
pour something on it and maybe it turns blue, to having a phonebook's worth
of information. That information unfortunately is written in a language that
we did not choose, just a four-letter alphabet, imagine ACGT ACGT, over and
over again. You can just picture a phonebook's worth of that.
And there begins the question, which is both statistical and scientific: How do
you make sense of this abundant information? We have this organism. We've
studied it for 100 years. We know what it does, and now we're presented with
this entirely different way of understanding this organism. In some ways, it's
the entire manual for the pathogen, but it's written in a language that we didn't
choose. That was a real turning point in biology.
3 www.sciencemag.org/content/269/5223/496.abstract
 
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