Metadata quality for federated collections

This paper presents early results from our empirical studies of metadata quality
in large corpuses of metadata harvested under Open Archives Initiative (OAI) protocols. Along with some discussion of why and how metadata quality is important, an approach to conceptualizing, measuring, and assessing metadata quality is presented. The approach given in this paper is based on a more general model of information quality (IQ) for many kinds of information beyond just metadata. A key feature of the general model is its ability to condition quality assessments by context of information use, such as the types of activities that use the information, and the typified norms and values of relevant information-using communities. The paper presents a number of statistical characterizations of analyzed samples of metadata from a large corpus built as part of the Institute of Museum and Library Services Digital Collections and Contents (IMLS DCC)2 project containing OAI-harvested metadata and links these statistical assessments to the quality measures, and interprets them. Finally the paper discusses several approaches to quality improvement for metadata based on the study findings.