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Today, almost every aspect of our lives is "rendered" in data.
New data collection technologies have made it easy to record continuous,
high-resolution measurements of our physical environment
(weather patterns, seismic events, the human genome).
We're also constantly monitoring our movements through and
interactions with our physical surroundings (automobile and
air traffic, large-scale land use, advanced manufacturing facilities).
In computer-mediated settings, our activities either depend crucially
on or consist entirely of complex digital data (networked games,
peer-to-peer technologies, Web site and Internet usage).
As a result of our improved abilities to "observe," professional and
research practices are becoming increasingly dependent on data and
data processing, on drawing conclusions from or in some way adapting
to rich flows of measurements taken from the physical or virtual
worlds. These professional demands have given rise to a host of new
analysis tools, new methodologies and new software, for uncovering
significant structures in data.
In parallel, we have seen the (inevitable?)
migration of these
technologies from labs and specialized deployments into widespread
usage by the general public.
As information technologies have brought "the network"
into our homes and personal spaces, new kinds of non-professional data
collection and analysis practices have developed, practices that
invite participation and data sharing.
In this new expanded field of
statistics, computing, and specifically computing with data,
is transformed. It is a medium for scientific investigation, for
advocacy, for cultural expression.
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