September 24-25, 1996. Seventy practitioners in the area of networked image description attended a two day workshop sponsored by the Coalition for Networked Information (CNI) and the OCLC Online Computer Library Center in Dublin, Ohio. This third in the series of metadata workshops addressed the application of the Dublin Core element set to image resource description (see the Dublin Core Homepage for more detailed information about this workshop and others in the series).
The two day workshop reached consensus, supporting the notion that the Dublin Core, within the context of the Warwick Framework, affords a foundation for the development of a simple resource description model to support network-based discovery of images. As Charles Rhyne, Chair of Art History at Reed College observed: "I was not especially surprised that we concluded that the elements needed to discover text and images on the internet are similar. The text and the images themselves are radically different and require different types of expertise to study and interpret them, but most of the primary categories under which we classify and search for them are similar."
Given the original objective of the Dublin Core element set -- to define a simple, easily understood semantic core for network resource discovery -- satisfying core description requirements for both textual and visual information with a single element set is attractive indeed. The enthusiasm for settling on a single set was modulated with a strong recommendation to make the labels for existing elements more amenable to the dual purpose of text and image description.
Is an image a document-like-object?The abstraction of a document-like-object emerged in the first workshop as a way of sidestepping differences in individual notions of what constitutes a discrete object worthy of separate description. One of the first issues addressed in the Image Metadata Workshop was whether an image is a document-like-object or is it so different that an alternative framework for description is required?Consensus emerged around the idea that images are not so different from the document-like-objects of the first workshop. The expectation that a set of image-specific elements (an Image-Core) would emerge from the workshop gave way to the idea that the application of a slightly modified Dublin Core element set might serve as well. As Jennifer Trant, of the Arts and Humanities Data Service in the UK, wrote after the workshop: "That images are 'document-like' was to me one of the more significant contributions of the meeting. We went into the discussion assuming that there would be an 'image core', expressed as a separate box within . . . the initial model for our discussions.
"We emerged from our two days of discussion with only one, slightly extended, set of core elements to support the discovery process, a set which seems to me to reflect the various conceptual categories researchers bring to their search for information. These categories did not change based on the media of the information resource (visual or otherwise) that might satisfy the query.
"After spending so long thinking that images were 'special' [to use museum-like assumptions] it was fascinating for me to have a group of image specialists say that in most content terms fixed/static/bounded images really are a lot like text-based document-like objects."
The single, slightly extended, set of core elements for image discovery emerged from two days of discussion as a set which seems to reflect the various conceptual categories researchers bring to their search for information. These categories were judged by the image specialists in attendance not to differ significantly based on the media (visual or otherwise) of the information resources that might satisfy the query.
The defining characteristic of a document-like-object is not its textual versus graphical content, but rather whether or not the resource is bounded, or fixed, in the sense that the resource looks the same to all users. Thus, images, movies, musical performances, speeches and other information objects which are characterized by being fixed (i.e., having identical content for each user) can also be thought of as document-like-objects.
Non-document-like objects, on the other hand, include such resources as virtual experiences, databases (including ones that generate document-like outputs), business graphics, CAD/CAM or geographic information generated from database values, and interactive applications which might have different content for each user. In the context of image discovery, these sources do not "contain" images as much as they "generate" images. The images they generate may be described as fixed document-like objects, but the metadata required to describe them (the systems doing the generating) are distinct.
Consider the example of the Visible Human Project (described in a workshop plenary talk by Earl Henderson of the National Institutes of Health). More than a collection of fixed images, the Visible Human Project at the National Library of Medicine is a collection of applications unified by a data set that is nothing if not visual in character. The scope of the project itself is dynamic and evolving rapidly, and the character of the visual outputs of any of the many applications growing up around this data set defy simple description and certainly are not bounded in the sense understood in this workshop. Such applications are systems, rather than collections of images.
A Model for Metadata
Much of the consensus-building surrounding the Dublin Core has involved accommodating pragmatic stakeholder concerns borne of long standing experience with legacy description models. It is helpful to have a conceptual model to guide this pragmatism, and just such a model developed in the course of the workshop. This model is an outgrowth of previous work of Bearman (see A Reference Model for Business Acceptable Communications) and provides conceptual support for both the Dublin Core and Warwick Framework by illustrating the transactional relationship of metadata and the research process.
The research process can be thought of as a series of interactive processes, which can provisionally be described as including: * Discovery: the identification of relevant resources
* Retrieval: the transfer of resources to a local site
* Collation: the aggregation and organization of selected resources
* Analysis: the intellectual and/or computational analysis of resources
* Re-presentation: the formulation of derivative intellectual artifacts based on the resources and previous processes in the sequence
These processes involve events and resources distributed among institutions, machines, networks, and the minds of individuals. Metadata, then, become any one set of elements drawn from the many kinds of information necessary for decision-making within this matrix of minds, machines, and networks.
For example, access to discovery metadata may lead to the return of terms and conditions elements, necessary for retrieval. Retrieval metadata might include the network address of a resolver from which the resource may be accessed or the publisher of an item with whom a usage agreement must be transacted. Collation metadata might include data about an image collection schema or the provenance of an item. Analysis might require a color map for the item. Re-presentation could involve information validating credit to rights holders, and might well require a link to update use history of the source object.
A variety of metadata will be needed to satisfy the requirements of each stage, and hence the functional requirements of metadata packages might well be defined by these requirements. To be used effectively, elements of metadata must be readily available as required by each stage in the research process in which the user is engaged (though different implementations might deliver some metadata at stages prior to its being needed). It is recognized that the pragmatics of collection and management of metadata will likely compromise this ideal, but the model can nonetheless inform our thinking and design.
One need not imagine all possible linkages to recognize the complexity of such a model, nor is it necessary to accommodate at the outset all possible elements, packages, and necessary infrastructure. But in the search for appropriate compromises, it is helpful to see the larger picture that this model attempts to capture. What is necessary, though, is an agreement as to the notion of assembling sets of descriptive elements, which enables extensibility and forward compatibility.
Like the Warwick Framework, this model explicitly recognizes that metadata will be created and managed by a variety of agents, for different reasons, at different times in the life of the object. This implies an infrastructure and architecture that does not now exist, but that will evolve, driven by the marketplace of information access. The modest achievement of this workshop is to reaffirm the semantic characteristics of but a single variety of metadata package -- the core elements of a resource discovery element set--and to assert its suitability for both textual and visual resources.
How are Images Different?It is gratifying that the workshop reached agreement that text and images could be classified using similar categories, but just as clearly, images offer a number of technological and descriptive challenges peculiar to themselves.
Textual materials can be indexed, often simplifying or partially automating the task of description, whereas most of the descriptive elements of images are extrinsic to the work (or are not easily extracted from the work).
Encoding schemes are critical for using images. This can be true for textual materials as well, but there are fewer varieties of textual representation, an |