Metadata Quality Problems in Federated Collections
Besiki Stvilia (University of Illinois-Urbana-Champaign, USA), Les Gasser (University of Illinois-Urbana-Champaign, USA) and Michael B. Twidale (Florida State University, USA)
Copyright: © 2007
This chapter presents results from our empirical studies of metadata quality in large corpuses of metadata harvested under Open Archives Initiative (OAI) protocols. Along with a discussion of why and how metadata quality is important, an approach to conceptualizing, assessing metadata quality is presented. The approach is based on a more general model of information quality 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 chapter presents a number of statistical characterizations of samples of metadata from a large corpus built as part of the Institute of Museum and Library Services Digital Collections and Contents project containing OAI-harvested metadata, interprets these statistical assessments and links to the quality measures. Finally the chapter discusses several approaches to quality improvement for metadata based on the study findings.