Information Technology Reference
In-Depth Information
between the technology of writing on paper, demanding separate descrip-
tion, and computation that enables automatically generated syntactic
descriptions is fully incorporated into the schema developed. Human
description labor includes interpretation as well as apparently more sim-
ple forms of description, classically understood as embodied in the activi-
ties of both classification and cataloging.
Description labor is understood ostensively and empirically as the
work involved in processes such as cataloging, classification, indexing,
and database description. More analytically, although still consistently,
description labor is conceived as the work involved in transforming
objects (documents, images, or people) into searchable descriptions that
will assist subsequent retrieval.
1
Two aspects of the transformation of
objects for description can be distinguished: the description of objects and
the assembling of these descriptions into searchable lists or indexes. These
aspects may merge into each other in practice, but they can be separated
analytically. Description labor aims implicitly to increase selection power
and can have the further effect of reducing labor expended in searching.
The object for description (see figure 3.2) is both physical document
and ideational text—information as both object and potential knowledge
(Buckland 1991; Blair 2002). As text, the object for description is the
product of an extended period of human mental labor, with periods of
high intensity: “writing a topic is a horrible, exhausting struggle” (Orwell
1946/1970, 29). The purchase price of the document may not fully reflect
the duration, intensity, and real costs of that labor.
The separation of syntax from semantics with the advent of written
language (Warner 2005a, 557-563) may have continuing implications for
the relative effectiveness of applying syntactic, or pattern-transforming,
procedures to verbal and nonverbal graphic signs. Nonverbal signs can
be subjected to syntactic or pattern-based transformations, with those
transformations realized as labor or as machine process, but it has been
difficult to endow transformations with semantic significance, either for
similarity and difference between signs or for establishing orders for dis-
play. Technically, it would not be difficult to transform a digital photo-
graph into a searchable description (for instance, Google's advanced
image search function enables searching by a range of colors and file types
[Google 2007b]) and to establish measures of similarity between images.
