Meaning and Metadata: Managing Information in a Visual Resource Reference Collection

Meaning and Metadata: Managing Information in a Visual
Resource Reference Collection

Judith
Thomas
Digital Media Center Clemons Library University of Virginia
judith@virginia.edu

1999

University of Virginia

Charlottesville, VA

ACH/ALLC 1999

editor

encoder

Sara
A.
Schmidt

The University of Virginia Library is in the process of building a reference
collection of visual images to support research in the humanities.On
the nature of library support for digital image collection: Lynch, Clifford
"The Uncertain Future for Digital Visual Collections in the University,"
Archives and Museum Informatics 11(1997):
5-13. The means and methods of creating, managing, and distributing
this kind of electronic information are still under debate in the visual
resource community, where the alphabet soup that characterizes the image
standards environment is thick with metadata possibilities. This presentation
will focus on identifying a semantic standard and defining a syntactic model for
the description of images.
Image metadata creators must make both syntactic and semantic choices to organize
and describe their data; these choices reflect their understanding of the scope,
function, and usage patterns of a collection and are based on underlying
assumptions for scholarly inquiry in a specific discipline.For an
ethnographic analysis of the application of standards in a mixed
physical-digital visual resources collection, see: Marshall, Catherine C.,
"Making Metadata: a study of metadata creation for a mixed physical-digital
collection, Digital Libraries 98: the Third ACM Conference
on Digital Libraries, ed. Ian Witten. New York: Association for
Computing Machinery, 1981. Metadata creators must be prepared to act
as interpreters of content and context, assigning meaning within a chosen frame
of reference.
The interpretive role given to creators of both the syntax and semantics of
image description is supported by the very framework for presentation and
analysis of visual material that has developed over centuries of art historical
inquiry.Panofsky, Erwin, Meaning in the Visual
Arts. New York: Penguin Books, 1955, p. 30. In
traditional analysis, the language of form is re-expressed through the spoken or
written word: the act of description confers meaning to the object.
Defining descriptive standards for works or art does reinforce this reliance on
text-based interpretationsThe very phenomenon of thumbnails as
metadata has the potential to reduce the reliance on words to explain
images. The presentation of large amounts of visual data into a scholarly
Gestalt will bypass semantic associations
and offer a more unmediated recognition of form.: and implies an
understanding of the verbal codings of the 'subject' of a work, its "of-ness" or
"about-ness."Layne, Sara Shatford, "Some Issues in the Indexing
of Images," Journal of the American Society for Information
Science 45,8 (1994): 585-588. Ambiguities and
inconsistencies are inevitable when description depends on so many layers of
individual interpretation of meaning.Stephenson, Christie, and
Patricia McClung, Delivering Digital Images: Cultural
Heritage Resources for Education. Los Angeles: The Getty
Information Institute, 1998. The challenge remains to design a
descriptive model that is based on standards yet is flexible enough to allow the
tying together of seemingly disparate elements with the thread of a unifying
idea.On "Analogy in an Age of Difference," see Stafford, Barbara
Jane, Good Looking, Cambridge, MA: The MIT Press,
1996. pp. 200ff.
Image description does present considerable challenges in defining an appropriate
and inclusive model. Issues of organization, hierarchy, relation, and surrogacy
are critical to defining content and context and must be considered when
deciding whether or how to give access to individual media objects as well as to
'natural' groupings of materials.On the creation of a shared
knowledge model to bridge descriptive differences, see Bearman, David, and
Jennifer Trant, "Unifying our Cultural Memory ," July 1, 1998, UKOLN;
available at <>.

Several different electronic encoding schemes are currently used to describe
image collections, with varying degress of success,The work of McRae
and White is notable for their attempts to adapt MARC to the description of
images of architecture. McRae, Linda, and Lynda S. White, eds., ArtMARC Soucebook: Cataloging Art, Architecture and Their
Digital Images. Chicago: American Library Association,
1998 and this paper will briefly review such efforts as the
Categories for the Description of Works of Art <>, the ICOM-CIDOC
model, CIMI's standardization efforts <>,
the VRA Core <>,
and others. Important to our effort is the Dublin Core, a metadata set designed
to support resource discovery in a networked environment, which has been adapted
for the description of image collections in several projects <>.For
a fascinating article on reconciling metadata requirements from the Dublin
Core and INDECS/DOI communities see Bearman, David, et.al., "A Common Model
to Support Interoperable Metadata," D-Lib Magazine
5, 1 (January 1999); <>.
So, useful semantics for image description do exist. Although the Dublin Core is
intended for resource discovery, the development of qualifiers to the simple
15-element set makes it a powerful and flexible metadata set for images. CIMI's
Dublin Core Metadata Testbed Working Group has demonstrated the feasibility of
this element set to the world of museum objects. What's missing then from the
picture is the syntactic model that gives expression to these elements and to
the relationships among the elements and to other information sources.
The descriptive model for images that we have developed at UVa is one building
block in the digital library architecture being designed under the direction of
Thornton Staples, the Director of Digital Library Research and Development. It
is intended from the outset to be expressed in SGML/XML, since its multi-level
hierarchy and system of inheritances would be denied complete expression in a
relational database. The image description model embeds in each level of the
hierarchy a full Dublin Core element set, defining each level as a "logical
cluster of metadata" and thus adhering to the 1:1 principle of description in
the Dublin Core (DC).Bearman, "A Common Model to Support
Interoperable Metadata,", p. 16.

At the top level of the hierarchy is a Work. This Work can be expressed as a core
(DC), and, at the next level down in the hierarchy, can contain one or more
components. Each component of the model must itself contain a descriptive DC
core - and/or other components. Components themselves can be targets to other
works, or to components or elements in the same or different work. The semantics
of the Dublin Core allow for description of the agents involved in the creation
or production of the work, its components, the surrogates, or even the
metadata.

The system of inheritances is such that the values of the elements of any level
of the hierarchy are carried to the levels below it unlesss they are explicitly
replaced by new values.
This model solves many of the troublesome problems of image description. A
building can have multiple building dates with various architects responsible
for different portions; a polyptypch can be attributed to several artists and
its panels distributed among different museums. Both can be adequately described
according to this scheme. Best practices will include recommendations for data
entry, standard vocabularies and schemes for the different elements, but the
modular nature of the information structure will allow for extensibility and
flexibility in terms of granularity and collection groupings, and ultimately,
points of view.