Meeting name

2019 Conference Of Inter-Mountain Archivists & Society Of Southwest Archivists Joint Annual Meeting

Meeting location

Tucson, AZ

Document Type

Presentation

Publication Date

5-18-2019

Abstract

Metadata remediation is inevitable – at some point or another all institutions need to clean-up legacy metadata of their digital collections so it conforms to new standards and to updated metadata application profile, or simply to prepare it for migration. Optimized metadata is vital for improved search experience and easy discovery of digital objects. This session will demonstrate how Excel can be a very handy tool for manipulating and cleaning up exported non-MARC metadata from ContentDM. The presenter will manipulate a metadata spreadsheet from a real digital collection demonstrating the following:

  • Data remediation using some advanced Excel functions that allow cleaning up at scale

    • Data Filter

    • TRIM

    • CONCATENATE

    • TEXTJOIN (insert module with VBA code)

    • Duplicate Values (look up and remove)

    • INDEX and MATCH

    • Find and Replace

    • MID, LEFT, RIGHT (break text/numeric string)

    • CHAR(10) insert line break

    • remove end punctuation [;]

    • Date clean up (clean messed up copy-pasted dates)

  • Mapping old fields to new fields

Attendees will learn the fundamentals of data remediation and some helpful Excel functions. They will add some practical skills in their toolbox and will leave the session with confidence that they can immediately apply their new skills in real-life projects. The metadata file is uploaded at http://bit.ly/CIMAdataSession and distributed among attendees. They are welcome to bring laptops to get their feet wet and play with the data, testing out some of the demoed Excel functions. Alternatively, attendees are welcome to simply watch how stress-free metadata clean up can be.

Link to session handout: http://bit.ly/CIMA2019handout
Link to session materials: http://bit.ly/CIMAdataSession

Keywords

Metadata clean up; Metadata remediation; Metadata clean up tools; Excel, clean data; Large data sets; Large-scale metadata cleaning

Disciplines

Library and Information Science

File Format

pdf

File Size

2.019 KB

Language

English


Share

COinS