Metadata Quality Control in Digital Repositories and Collections: Criteria, Semantics, and Mechanisms

Abstract

This article evaluates practices on metadata quality control in digital repositories and collections using an online survey of cataloging and metadata professionals in the United States. The study examines (1) the perceived importance of metadata quality, (2) metadata quality evaluation criteria and issues, and (3) mechanisms for building quality assurance into the metadata creation process. The survey finds wide recognition of the essential role of metadata quality assurance. Accuracy and consistency are prioritized as the main criteria for metadata quality evaluation. Metadata semantics greatly affects consistent and accurate metadata application. Strong awareness of metadata quality correlates with the widespread adoption of various quality control mechanisms, such as staff training, manual review, metadata guidelines, and metadata generation tools. And yet, metadata guidelines are used less frequently as a quality assurance mechanism in digital collections involving multiple institutions.