ACM Journal on Computing and Cultural Heritage
JOCCH publishes papers of
significant and lasting value in
all areas relating to the use of IC T
in support of Cultural Heritage,
seeking to combine the best of
computing science with real
attention to any aspect of the
cultural heritage sector.
information processes—natural or
constructed processes that transform
information. They can be discrete or
Computing represents information processes as “expressions that do
work.” An expression is a description of
the steps of a process in the form of an
(often large) accumulation of instructions. Expressions can be artifacts, such
as programs designed and created by
people, or descriptions of natural occurrences, such as DNA and DNA transcription in biology. Expressions are not only
representational, they are generative:
they create actions when interpreted
(executed) by appropriate machines.
Since expressions are not directly
constrained by natural laws, we have
evolved various methods that enable us
to have confidence that the behaviors
generated do useful work and do not
create unwanted side effects. Some of
these methods rely on formal mathematics to prove that the actions generated by an expression meet specifications.
Many more rely on experiments to validate hypotheses about the behavior of
actions and discover the limits of their
Table 2 summarizes the computing
paradigm with this focus. While it contains echoes of engineering, science,
and mathematics, it is distinctively different because of its central focus on
5 It allows engineering and science to be present together without having to choose.
There is an interesting distinction
between computational expressions
and the normal language of engineering, science, and mathematics. Engineers, scientists, and mathematicians
endeavor to position themselves as outside observers of the objects or systems
they build or study. Outside observers
are purely representational. Thus, traditional blueprints, scientific models, and
mathematical models are not executable. (However, when combined with
computational systems, they give automatic fabricators, simulators of models, and mathematical software libraries.) Computational expressions are not
constrained to be outside the systems
they represent. The possibility of self-reference makes for very powerful computational schemes based on recursive
designs and executions, and also for
very powerful limitations on comput-
ing, such as the noncomputability of
halting problems. Self-reference is common in natural information processes;
the cell, for example, contains its own
The interpretation “computational
12 embeds nicely into this
paradigm. The paradigm describes not
only a way of thinking, but a system of
The distinctions discussed here offer
a distinctive and coherent higher-level
description of what we do, permitting
us to better understand and improve
our work and better interact with people in other fields. The engineering-science debates present a confusing
picture that adversely affects policies
on innovation, science, and technology,
the flow of funds into various fields for
education and research, the public perception of computing, and the choices
young people make about careers.
We are well aware that the computing paradigm statement needs to be
discussed widely. We offer this as an
opening statement in a very important
and much needed discussion.
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Peter J. Denning ( firstname.lastname@example.org) is the director of the
Cebrowski institute for information innovation and
Superiority at the Naval Postgraduate School in Monterey,
CA, and is a past president of ACM.
Peter A. Freeman ( email@example.com) is
emeritus Founding Dean and Professor at Georgia Tech
and Former Assistant Director of NSF for CiSe.