Biology Reference
In-Depth Information
The examples of “centralizing” and “democratizing” regimes I have
described here entail particular political and technical visions of biology.
Each recognizes the need for maintaining a balance between fl exibility
(in order to promote scientifi c innovation) and structure (in order to al-
low data sharing). Where they crucially differ is in their visions of how
biological expertise should be distributed in space. Ontologies imagine
a grand unifi cation of biology powered by a reduction of language to a
universal and machine-readable form—one of the aims of the ontolo-
gists is making the GO and other bio-ontologies compatible with OWL
(Web Ontology Language). Biological knowledge will be produced
largely from the resources of the Semantic Web, guided by a few ex-
perts in central locations.
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The alternative, as exemplifi ed here by DAS,
is a wiki-biology—multiple visions and multiple languages will be al-
lowed to fl ourish and compete for attention and certifi cation. Biological
knowledge will be distributed and heavily reliant on local expertise.
The GO attempts to constrain the shape and form of bioinformatic
objects—it tries to determine the kinds of things that can exist in digital
biology. But it also polices the relationships between them—it has con-
sequences for biological knowledge because it establishes structures and
hierarchies through which biological things can relate to one another.
As we will see with respect to databases in the next chapter, the struc-
tures of information technologies exert powerful forces on the ways in
which biologists think about organisms. Simultaneously, the GO has
consequences for the disciplinary structure of biology—it establishes
hierarchies among different groups of biologists. The GO shows (as we
have seen elsewhere) that bioinformatics is a transformation of objects,
knowledge, and the organization of biological work.
In the short term, biology will continue to rely on ontologies to pro-
mote data sharing. My aim here has been less to criticize such ontologies
than to show how specifi c technical solutions determine specifi c struc-
tures within which biologists must talk and act. Not only the move-
ment of data, but ultimately the authorization of bioinformatic knowl-
edge, depends on the organization and hierarchies within the biological
community. But the DAS is an alternative techno-social solution to the
problem of data sharing. It suggests that the structures imposed by on-
tologies are not necessary but contingent—they are built by practicing
biologists. Indeed, much of the work of bioinformatics is in generating
these ways and means of allowing data to move around frictionlessly.
Another important example of this type of standardization is the
work of the Genomic Standards Consortium (GSC). Since 2005, the
GSC has attempted to extend the reach of standard vocabularies to cover
