SCIENTIFIC NETWORKING AND COLLABORATIONS - Collaborative Computational Technologies for Biomedical Research - page 153

Static
Web page

New content
shared peer to peer

New content
in background

Web 1.0 Web 2.0 Web 3.0

Figure 10.1 Evolution of client - server confi gurations from Web 1.0 to Semantic Web.
The static links on a Web page give way to a two-way communication process between
the client (laptop) and server that feeds in information through AJAX and RDF
systems.

physical infrastructure that allows data transfer and manipulation at the pet-
abyte level (see Section 10.3.2). Incidentally, the name eScience (unhyphen-
ated) has been adopted by the Chemical Abstracts Service as part of its
information portal and is a registered trademark of the American Chemical
Society ( http://www.escience.org/ ).
A wide-ranging and visionary description of e-science has been offered by
the late Jim Gray of Microsoft Research, who coined the term “the fourth
paradigm ” [11] . The word paradigm , originally used by Thomas Kuhn in his
seminal book The Structure of Scientifi c Revolutions [12], is widely used and
abused in scientifi c (and other) circles. Kuhn's defi nition is based on the idea
that scientifi c progress occurs in a nonlinear fashion, with infrequent paradigm
shifts that challenge and supersede existing dogma. Thus the paradigm of an
earth-centered universe was overthrown as a result of the discoveries of
Galileo, Copernicus, Kepler, and others. The paradigm described by Gray is
not really the same, since he refers to a process or theme central to the way
science works. Nevertheless, it offers a useful description of how scientifi c
research has evolved in distinct phases. The fi rst paradigm is the bedrock of
the discipline, experimental science, followed by the second, theory. The third
paradigm is simulation, an area that has only been possible through the devel-
opment of computer science over the last few decades. Finally, the fourth para-
digm can be summed up as data-intensive science which involves capture,
curation, and analysis of experimental data, from the output of stars to signals
from gene chips. Here, enormous data sets generated from many different
types of experiment are distributed globally and analyzed using the mature
computational technologies brought about by Web 2.0 and Web 3.0. The
required exponential increase in computing power is delivered by new hard-
ware. Some examples of e-science/the fourth paradigm in action are to be seen
in astronomy, oceanography, and high-energy physics as well as the life sci-
ences to be covered in this chapter [13]. The astronomy community, for