Biology Reference
In-Depth Information
May 2008 and shut down January 2013) for managing personal health
records, and Microsoft has HealthVault (launched in October 2007).
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Google also offers “universal search in life sciences organizations”—
“All the information you need to be productive at work should be
available through a single search box—including all the content within
your enterprise fi rewall, on your desktop, and on the World Wide Web.”
Google's search technology, the company promises, will be embedded
seamlessly in the research and development effort, saving time and
money.
From one point of view, Google's foray into the life sciences is un-
surprising: it has designed tools to search and manage large amounts of
information, and the proliferation of biological data offers it a natural
market. On the other hand, seeing these two distinct kinds of objects
(websites and biological data) as essentially similar is a nontrivial step:
Why should information from genomes be similar enough in organiza-
tion to the information from the World Wide Web that the same tools
can apply to both? Why should “Googling your genome” be a thinkable
practice? I am suggesting here that it is because biology and the web
share both a history and a set of problems—because they are entangled
with one another to such an extent that understanding the future of
biology requires understanding where the Internet is headed as well.
As biological knowledge is increasingly produced in and through the
web, biological objects are increasingly online objects—the web repre-
sentation of a genome or a cell becomes the way it is understood. Goo-
gling your genome becomes an obvious practice because one's genome
is—fi rst and foremost—data. Google's solutions to problems of data
management are also solutions to biological and biomedical problems.
Biology 3.0
In 2006, the
New York Times
journalist John Markoff coined the term
“Web 3.0” to refer to a collection of “third generation” web technolo-
gies, such as the Semantic Web, natural language searching, and ma-
chine learning, that he predicted would take over the Internet between
2010 and 2020. Although the terms are fuzzy and contested, Web 0.0 is
usually understood as the predigital network of direct human-to-human
interaction, unmediated by technology, and Web 1.0 as the fi rst itera-
tion of large-scale data sharing, mostly using HTML, in the 1990s. The
fi rst decade of the twenty-fi rst century became dominated by Web 2.0,
the use of the Internet for social networking, wikis, and media sharing.
Web 3.0, in contrast, promises an “intelligent Web,” in which data will
