University Libraries & Learning Sciences Faculty Publications

Document Type

Book Chapter

Publication Date

2017

Abstract

Metadata may be generally understood to support discovery and performance of bibliographic functions against a given resource or set of resources. For example, a limited set of basic descriptive metadata can be used to index sets of items, group or otherwise associate similar items through shared metadata values, or to establish means of defining and enforcing relevance or other ranking systems. Within the context of curating research data, descriptive and other types of metadata (notably those defined the CCSDS Reference Model for an Open Archival Information System) may be more broadly applied to administer access and reuse policies, define system requirements, or perform quality assurance and control functions. However, whereas domain repositories such as the Long Term Ecological Research (LTER) Network Data Portal may capitalize on complex metadata schema such as the Ecological Metadata Language (EML) to perform an array of descriptive, technical, provenance, other repository functions, transferring data between these and more general, domain agnostic preservation systems such as university institutional repositories (IR) can result in a loss of features or services when descriptive metadata alone are crosswalked into the (typically Dublin Core) IR metadata schema. By way of exploring methods for maximizing the service and feature potential of complex metadata as harvested form a domain repository for archiving within an IR, a recent collaboration between the University of New Mexico Libraries and the Sevilleta LTER station demonstrates the application of EML at multiple stage in the data lifecycle as a means of performing quality assurance and control functions.

Publisher

Association of College and Research Libraries

Publication Title

Curating Research Data

Volume

2

First Page

184

Last Page

187

Keywords

metadata, data curation, quality control

Comments

This case study was first published in volume 2 of the ACRL publication, Curating Research Data, edited by Lisa Johnston. Please see the included front matter for more information.

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