(Please forward at will)
"The process of harvesting, sequencing and mapping the human genome has
been described as that of a group of people in a dark room fumbling around
not knowing what is in the room, how the room looks or what they are
looking for. Someone bumps into a thing with four sharp corners and starts
to look for other things with four sharp corners. Someone else decides to
move along what seem to be walls and feel their texture, yet another sits
still and waits for the others in the room to pass by, taking notes on
their activities or maybe on their scents."
- Lisa Jevbratt, curatorial notes, Mapping the Web Infome
I have been invited by YLEM (www.ylem.org) to guest edit an issue of their
print publication, the YLEM journal: Artists Using Science and Technology.
The topic of this issue will be, roughly, artists working with large data.
We all know Moore's law, the famous and prescient prediction that the
speed of CPUs doubles approximately every 18 months. What is less well
understood is the exponential growth of scientific data, and the
relationship between its collection and our ability to process and
understand it. Genomic data is not the only large data set that is
presenting both processing and conceptual challenges to science and
information technology; we can also point to astrophysics, geography,
geology, fusion energy, climatology, nanotechnology and many branches of
materials science as areas of study that are producing quantities of data
that challenge the technical limits of super computers, distributed
computing, grid computing, and superscalar simulation techniques. Even
given Moore's law, semiconductor advances, fast networks, and cheap mass
storage, "The Problem of Large Data" is nevertheless looming larger as our
ability to collect data begins to outpace our ability to process and
If you are an artist who is working with extremely large data sets,
particularly those relating to scientific endeavor, we invite you to
submit abstracts for papers to be considered for publication in an
upcoming issue of the YLEM journal. Of particular interest are papers
relating to projects that demonstrate the strategies, traditions, and
practices common to or employed within the practice of art (and
art/science collaboration), that might inform productive and innovative
approaches to "The problem of Large Data".
Please send Abstracts or proposals to:
Brett Stalbaum (firstname.lastname@example.org)
Deadline: Not really, but review will begin in early March, 2003, for
expected publication during 2003. Average articles run around 1500-2000
words, depending on the number and size of images.