Information Technology Reference
In-Depth Information
as just the kind of conceptual grab bag that its opponents accused it
of being.
In 1965, the ACM Curriculum Committee attempted to bring unity
to computer science by defi ning it in terms of a single fundamental unit
of analysis: computer science “is concerned with
information
in much
the same sense that physics is concerned with energy; it is devoted to the
representation, storage, manipulation
, and
presentation
of informa-
tion.”
60
This redefi nition of computer science around the study of infor-
mation offered several immediate benefi ts. Not only did it lay claim to
the valuable intellectual territory suggested by the commonsense under-
standing of information as knowledge or data but it also linked the dis-
cipline to the specifi c formulation of information developed in the late
1940s by the mathematician Claude Shannon. In his seminal topic with
Warren Weaver from 1949,
A Mathematical Theory of Communication
,
Shannon had defi ned information in terms of the physical concept of
negative entropy.
61
His information theory appealed to scientists in a
wide variety of disciplines, and for a time it appeared as if information
might serve as a broadly unifying concept in the sciences.
62
But despite
its intellectual appeal, Shannon's mathematical defi nition of information
was never widely applicable outside of communications engineering. And
as for more commonsense notions of information, there already seemed
to be claimants to that problem domain. Librarians were already experts
at classifi cation, storage, and data retrieval. Statisticians specialized in
numerical data. Most academic disciplines, to a certain degree, were
devoted to the management and analysis of information. In Europe,
various versions of the German word
informatik
(including the French
informatique
, the Spanish
informatica
, and the English informatics) had
been successfully mobilized to organize the emerging “computing sci-
ences” (a minor but signifi cant difference in terminology) around the
study of information, rather than computers per se, but in the United
States such efforts achieved much traction.
63
In the end, though, it would not be information that emerged as
the foundational concept of modern computer science but rather the
algorithm.
Fundamental Algorithms
A revolution in science can only be considered complete, according to
the infl uential philosopher of science Thomas Kuhn, when it has written
its own textbook history. Textbook histories are the short, celebratory
