Academic journal article Library Resources & Technical Services

Toward Releasing the Metadata Bottleneck: A Baseline Evaluation of Contributor-Supplied Metadata

Academic journal article Library Resources & Technical Services

Toward Releasing the Metadata Bottleneck: A Baseline Evaluation of Contributor-Supplied Metadata

Article excerpt

Metadata creation is one of the most expensive components of digital projects. Organizational expertise (the correct structure, syntax, and use of metadata elements) and subject expertise (the appropriate semantic description of a resource's content for users) are both needed to create a high-quality metadata record. Resource creators are frequently considered good metadata generators. Contributors or subject enthusiasts in a discipline are another population that may be good candidates for metadata creation. In this study, the quality of contributor-supplied metadata is evaluated. Metadata records submitted through a Web form are compared to the final published version of the record. Structural and semantic errors are noted throughout the records evaluated. Overall, semantic quality was good, reflecting subject expertise. The appearance and type of structural errors suggests that improvements in the interface can reduce contributors' need to have organizational expertise to create high-quality metadata records.

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In the life cycle of digital projects such as repositories, databases, registries, and collections, one of the most expensive initial components is metadata creation for each digital resource. (1) Metadata creation requires both organizational and subject expertise to describe an object and its context for use. In this paper, organization expertise refers to the ability to apply the correct structure, syntax, and use of metadata elements, while subject expertise refers to the ability to generate appropriate semantic (or meaningful) description of a resource's content for users. High-quality metadata utilizing both expertise types is an integral part of effective searching, retrieval, use, and preservation of digital resources. Metadata professionals tend to be proficient both in organizational and subject expertise; however, they are too few to provide sufficient metadata in a timely, efficient manner for the abundance of digital resources, creating a bottleneck in a digital-project's workflow.

Rather than sacrifice the quality of metadata in digital projects, recent research to alleviate the bottleneck has explored several methods to reduce the need for either organizational or subject expertise in metadata creation, including use of creators as metadata suppliers and automatic metadata-generation processes. (2) Currently, creators seldom provide sufficient metadata for their digital resources, and scalable automatic metadata-generation techniques that produce acceptable metadata are still in development. (3) This paper explores another group outside of metadata professionals and resource creators for human metadata generation: subject enthusiasts, or those with a significant background in any discipline. (4)

One primary benefit of enlisting contributors to provide metadata in digital projects is that the pool of potential metadata creators immediately increases. The potential for collaborative metadata generation, or "the joint production of Web resource metadata," also increases. (5) While resource authors are the primary focus of current research in human metadata generation, the purpose of this paper is to serve as a baseline study of the contributor-supplied metadata using RILM Abstracts of Music Literature (RILM), an international database of scholarly works about music. (6) RILM uses authors and subject enthusiasts (volunteers from the international music community) to create basic metadata records that are then reviewed and enhanced by metadata professionals before the final resources are published in the database. Secondarily, this paper evaluates the quality of contributor-supplied metadata when specific content guidelines for elements are available.

Literature Review

Metadata-quality evaluation is closely related to the extensive research conducted on all aspects of data quality. One of Orr's six laws of data quality states that "[the] laws of data quality apply equally to data and metadata. …

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