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I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability
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I Bet You Clean Up Real Nice: Makeover Your Metadata for Maximum Interoperability

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  • 1. Heather Gilbert Digital Scholarship Librarian, College of Charleston SCLA/SELA Joint Conference, Greenville, SC November 13, 2013
  • 2. South Carolina Digital Library • SCDL Aggregates Content from Across the State • Over 50 Partner Institutions • 3 Major Regions: Coastal, Midlands & Upstate • 200,000 items • Provides Metadata Templates, Documentation, Digitization Standards and Best Practices
  • 3. SCDL & the DPLA • Asked to be One of the First 6 DPLA Service Hubs • DPLA Required Legacy Metadata Correction • 200,000 Items Across Three Major Regions and a Variety of Platforms = A Lot of Potential for Correction
  • 4. Our Messy Metadata • The Importance of Controlled Vocabularies – Format (Internet Media Type) = MIME Type – Media Type, Type = Local CV & DCMI Type – Subject & SC County = LOC please! • Standardize Your Formats – Date Fields = ISO 8601 This means no circa dates
  • 5. Why Clean It Up? • Polished Metadata: – Increased Interoperability – Facets Nicely = Browses Better – Higher Results Accuracy – Relevant Nationally • DPLA Compliant
  • 6. Open Refine Your Data http://openrefine.org/ Free, web-based, open source application for cleaning up, transforming and using APIs to extend your data Documentation Aplenty Using Open Refine (Verborgh, De Wilde) http://openrefine.org/documentation.html https://github.com/OpenRefine/OpenRefine/wiki
  • 7. Open Refine - Create
  • 8. Open Refine - Create
  • 9. Open Refine - Edit
  • 10. Open Refine - Edit
  • 11. Open Refine - Edit
  • 12. Open Refine - Edit
  • 13. Open Refine - Export
  • 14. Heather Gilbert Digital Scholarship Librarian, College of Charleston Project Coordinator, Lowcountry Digital Library

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