Exploring the utility of metadata record graphs and network analysis for metadata quality evaluation and augmentation

Abstract

Our study explores the possible uses and effectiveness of network analysis, including Metadata Record Graphs, for evaluating collections of metadata records at scale. We present the results of an experiment applying these methods to records in the University of North Texas (UNT) Digital Library and two sub-collections of different compositions: the UNT Scholarly Works collection, which functions as an institutional repository, and a collection of architectural slide images. The data includes count-and value-based statistics with network metrics for every Dublin Core element in each set. The study finds that network analysis provides useful information that supplements other metrics, for example by identifying records that are completely unconnected to other items through the subject, creator, or other field values. Additionally, network density may help managers identify collections or records that could benefit from enhancement. We also discuss the constraints of these metrics and suggest possible future applications.

Organization of Knowledge and Information in Digital Archives of Language Materials

“…13 However, the metrics used in OLAC's language archive metadata quality evaluations are based on completeness of metadata records only after their conversion from their native format to Simple Dublin Core. The automated quality rating in the OLAC system is based on the inclusion of specific metadata elements (title, 5 description, subject, date and identifier) in item-level metadata records (Hughes, 2005) similar to the completeness metrics used in other repositories (e.g., Tarver et al, 2014). OLAC's automated metadata quality ranking also considers the use of OLAC controlled vocabularies (OLAC Discourse Type, OLAC Role Vocabulary) (Hughes, 2005).…”

A Text Mining Approach to Uncover the Structure of Subject Metadata in the Biodiversity Heritage Library

“…In a large‐scale digital environment, metadata records are expected to be reliable access points for users to retrieve relevant online collections (Lu et al, 2010; Walsh, 2011). However, the involvement of multiple metadata providers for a large digital library may result in confusion in the practice of how subject headings are assigned (Tarver et al, 2015). For instance, the Digital Public Library of America (DPLA) contains metadata from 23 providers with differing practices for assigning subject headings.…”