MAINTAINING QUALITY METADATA: TOWARD EFFECTIVE DIGITAL RESOURCE LIFECYCLE MANAGEMENT

MAINTAINING QUALITY METADATA: TOWARD EFFECTIVE DIGITAL

RESOURCE LIFECYCLE MANAGEMENT

Daniel Gelaw AlemnehUniversity of North Texas

ICKM 2008

University of North Texas (UNT) Libraries Digital Initiatives

Collaborative Initiatives• CyberCemetery

• GPO• NARA – Affiliated Archive

• Texas Register Archive• Secretary of State’s Office

• Texas Laws and Resolutions Archive• Secretary of State’s Office

• The Portal to Texas History• 45 Libraries & Museums

• Web-at-Risk Project• California Digital Library• New York University

• National Digital Newspaper Program (NDNP)• Between 1836 and 1922.

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University of North Texas (UNT) Libraries Digital Initiatives

Library Digital Collections: • Congressional Research Service Archive

• 10,000+ CRS Reports• World War Poster Collection

• 500 WWI and WWII Posters• Advisory Commission on Intergovernmental Relations

• 408 reports = 47,874 pages• Federal Communications Commission (FCC) Record

• 136 issues = 43,115 pages (6 of 21 volumes completed)• Electronic Theses and Dissertations (ETDs)

• 3000+ more in queue• Jean-Baptiste Lully (Music) Collection

• 27 scores = 10,000 pages• Other digitization projects

• http://www.library.unt.edu/libraries-and-collections/digital-collections

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Metadata Environment

• Metadata-based digital resource management activities

• UNT Libraries metadata locally qualified Dublin Core based descriptive metadata.

• Detailed technical and preservation metadata elements• Web based metadata creation and editing

• Interoperability

• Metadata Crosswalks• Mods• Marc• oai_dc• PREMIS

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Metadata Quality

• The two aspects of digital library data quality:

• The quality of the data in the objects themselves• The quality of the metadata associated with the objects

• Poor metadata quality:

• Ambiguities • Poor recall• Poor precision • Inconsistency of search results

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Metadata Quality …

• Most Common errors:

• Incorrect Data: • Letter transposition• Letter omission• Letter insertion• Letter substitution or misstrokes

• Missing Data

• Elements and values not present at all (null) • Insufficient or incomplete data

• Ambiguous Data • Confusing or inconsistent data e.g. multiple spellings, multiple

possible meanings, mixed cases, initials, etc.

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Factors Influencing Metadata Quality

• Local Requirements:

• Objects Heterogeneity

• What type of objects will the repository contain?

• Granularity

• How will they be described?

• Functionality

• What functionality is required? • How will it be interfaced?

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Factors Influencing Metadata Quality …

• Collaborative Requirements:

• Diversity of Users

• How best diverse information-seeking behaviors can be met?

• Interoperability

• Will metadata be meaningful within aggregations of various kinds? • What is required for interoperability? (Structure, semantics, & syntax)

• Digital rights issues

• Will access restrictions be imposed? • Are requirements formal or informal? • Are there other access and associated digital rights issues?

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Factors Influencing Metadata Quality…

• Training Issues

• Necessary expertise to create and manage rigorous metadata

• Metadata quality can be determined to a great extent by:• knowledge of the source, and • knowledge of the methodology used to create the statement

• Cost • Rigorous metadata is resource intensive and too costly

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UNT Metadata Quality Assurance Mechanisms & Tools

• The two main stages of metadata qualities assurances:

• Pre-injust

• 1. Metadata Creation tools (Templates)

• Post-injust

• 2. Metadata Analysis tools (Web-based tools)

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Quality Assurance Mechanisms and Tools: Templates

1. Metadata Creation Tools (Templates)

• Validates Mandatory elements

• Metadata Template Creator

• Template Reader

• Controlled vocabularies (UNTLBS)

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UNT Metadata Quality Assurance Mechanisms & Tools…

2. Metadata Analysis Tools • NULL Values

• List/Browse All Values (by each qualifiers and elements)

• List Authorities Values

• Graphical reports and other fun stuff

• Clickable Maps by Institution and Collection

• Word Clouds by elements

• Records added overtime and other graphical reports

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Summary• Determine level of quality required

• Partners may have much in common, but they have diverse and sometimes conflicting metadata requirements.

• Determine nature of gap and how to close it • effectiveness, efficiency, practicability, scalability

• Machine verses human error handling • How much of the process can be automated? • Human review of results is still essential (e.g. highlighted items)

• Compromise • One size does not fit all!

• Prioritize • Resources very unlikely to be available to meet all requirements

• Test the workflow • Test, retest, and evaluate the quality cycle continuously

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ICKM 2008

Questions?Daniel.alemneh@unt.edu

Thank You!