|
Items in cart [1] |
Questions? Call 888-624-8373 |
| Copyright © 2009. National Academy of Sciences. All rights reserved. Terms of Use and Privacy Statement |
Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 402
402 THE LIFE SCIENCES
TABLE 62 Computing Costs Funded by Different Sources for Selected Research
Areas
COMPUTING COSTS, BY SOURCE
(PERCENTAGE OF B-HOURS)
RESEARCH AREA Federal Funds
Own Life Sciences Funds of
All Research Computing Non-Life- Other Unknown
Sources Grant Center Sciences Funds Funds Source
AVERAGE ALL BIOLOGY 100 42 29 9 11
Behavioral Biology 100 49 39 5 6 1
Cellular Biology 100 72 13 2 11 2
Developmental Biology 100 28 13 1 57 1
Disease Mechanisms 100 31 58 2 6 3
Ecology 100 40 19 11 3 26
Evolutionary and
Systematic Biology 100 34 4 42 6 14
Genetics 100 50 26 1 12 8
Molecular Biology
and Biochemistry 100 38 30 7 14 8
Morphology 100 51 14 15 16 4
Nutrition 100 32 12 12 19 24
Pharmacology 100 68 11 1 11 9
Physiology 100 44 24 5 9 13
Source: Survey of Individual Life Scientists, National Academy of Sciences Committee on Research in the Life
Sciences.
~.xamnle almost all the computing of the cellular biologists is supported
r 7 ~ ~ _ ~ A
from research grants, while a much smaller fraction is thus funded In the
areas of ecology, and evolutionary and systematic biology. Biologists in the
latter two areas reported a large percentage of unknown support, which
probably implies the receipt of "free" computation at a university computa-
tion center.
CONCLUSIONS AND RECOMMENDATIONS
When this picture of computing in the life sciences in 1967 is combined
with the basic lessons about the evolution of the computer industry and
of computer use in any field, the following conclusions and recommenda-
tions emerge.
1. Basic continuing support. Computers are now an integral part of
the life sciences, through all its subdomains. Computing costs must be
OCR for page 403
DIGITAL COMPUTERS IN THE LIFE SCIF,NCES
added to space, personnel, and instruments as basic continuing support
items. As with these other resources, computing time should be awarded
to the individual investigator or research project according to the merits
of the research, through the regular funding channels. If funds permit,
computing will continue to increase during the coming years as a fairly
predictable increased percentage of life scientists (now probably of the
order of 10-15 percent new scientists per year) come to use computers,
and there is an unknown increase in the number of the already heavy users.
The increased use by the new scientists will slow toward the base growth
rate of the field in about five years, but the proportion of medium and heavy
users will continue to increase for a long time. Offsetting the expense of
this growth, while at the same time tending to increase its rate, is the
decreasing cost of computation.
The emphasis on funding computation in relation to the quality and
significance of the research to which it will contribute, is not meant to
ignore the need for stability that large facilities require. Indeed the need
for stability constitutes the main pressure for block funding of facilities.
However, the experience with block funding of computer facilities (e.g.,
at the National Institutes of Health) makes it clear that one must move as
rapidly as possible to associate with each research effort the cost of its
computing and then assign to investigators both the freedom and the xe-
sponsibility to obtain computing funds appropriate to their research.
2. Multiplicity of facilities and decentralization of control. The extreme
diversity of uses of computers implies need for an equal diversity of
computing facilities. As we have said, the generality of the computer is
that it can be shaped (configured and programmed) for almost any type of
information-processing task, but it cannot simultaneously be all things to
all users. In fact, all computer facilities become highly specialized, the
large university computing center being no exception. A part of the history
of computing in the life sciences is written in the struggle of research groups
to obtain computers of their own, which can be shaped to their own uses-
as laboratory instruments or as data-retrieval and display systems, for
example.
A second reason for decentralization of the selection, development, and
control of computers is that only through the parallel attempt of many life
scientists to adapt the computer to their needs will the computer play its
appropriate role in life science research. If the technical development is
isolated in a relatively few centralized centers, this assimilation will be
substantially retarded.
3. Development. The life sciences can rely on the computer industry
to continue to produce cheaper, more powerful technology. They cannot,
however, look to anyone else for their development-that is, to assimilate
403
OCR for page 404
404
THE LIFE SCIENCES
the computer into work on life science problems. Development is expensive
and unsatisfactory, in that initial goals are seldom met. It is frustrating, in
that frontier projects always have troubles that later projects (often ex-
ploiting better and cheaper technology) seem to avoid, making it appear
that originally the wrong approach was taken. But this is characteristic of
development, and is the price of getting the computer fully assimilated into
particular fields.
There are no special "computer areas" in the life sciences. All subareas
are assimilating the computer, though in somewhat different ways and,
currently, at different rates. Every subarea has its unique forms of symbolic
processing, which, as it is successfully developed, can make large differences
in the progress of research in the subarea. For example: image processing.
generally in microscopy, but also in ecology; large-scale simulations in
ecology; laboratory computerized instruments in physiology and biochem-
istry; taxonomic retrieval systems in systematics. Almost all the heavy
users in our census would reveal somewhat special developments.
The projects in the life sciences noted above have analogues in other
fields, which may short-circuit the research effort but not the development
effort. However, life scientists have some symbolic functions in common
with all other scientists and all other technologically oriented professionals.
The best example is small numerical calculations analogous to engineering
calculations. The computer field can be relied on for development relating
to these for instance, in the multitude of time-consuming mathematical
calculations necessary to untangle and to understand complex biochemical
reactions. Another example is the development of time-sharing, which is
of immense importance in getting the computer widely assimilated.
Massive development efforts repeatedly produce wedges that open up new
technology. The life sciences must support such efforts for themselves. The
amounts of money spent on such projects may often seem out of proportion
to what the same amounts, distributed otherwise, could yield, but this is an
illusion, for there is no other way to gain entry into new areas other than
by paying the apparently "excessive" costs of large development efforts.
Representative terms from entire chapter:
heavy users
