Document Type

Article

Publication Date

4-16-2021

Publication Title

Against the Grain

Volume

33

Issue

1

First page number:

1

Last page number:

4

Abstract

Metadata remediation of digital collections is inevitable. At some point, each repository faces the need to clean-up digital collections legacy metadata so that it conforms to new standards. Typically, this need emerges either as a response to an updated metadata application profile, or as preparation for migration to a new digital asset management system (DAMS). Normalized metadata is critical for an improved search experience and easy discovery of digital objects.

This case study focuses on the University of Nevada, Las Vegas’ (UNLV) experience of cleaning up and preparing non-MARC metadata for migration to a new DAMS. The author shares her experience on cleaning up over 50,000 records in Excel for slightly over six months. Excel is a convenient, easily accessible tool with hundreds of free tutorials online. The remediation work utilizes various functions and formulas that are used to manipulate and optimize the metadata consistency.

Keywords

Metadata clean up; Metadata remediation; Metadata clean up tool; Excel, clean data; Large data sets; Large-scale metadata cleaning; Legacy digital collections

Disciplines

Cataloging and Metadata | Library and Information Science

File Format

pdf

File Size

319 KB

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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