Crowdsourcing Digitization: Harnessing Workflows to Increase Output

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Crowdsourcing Digitization: Harnessing Workflows to Increase Output - Presentation Transcript

  1. Crowdsourcing Digitization Harnessing Workflows to Increase Output Gretchen Gueguen, East Carolina University Ann Hanlon, Marquette University LITA National Forum, 2008 Cincinnati, Ohio
  2. What is crowdsourcing?
    • Jeff Howe, Wired Magazine , 2006
      • “ distributed labor networks are using the Internet to exploit the spare processing power of millions of human brains” – best example, Wikipedia…
      • Any end achieved by harnessing the wisdom and labor of crowds
      • Distributing the burden of a large endeavor
    Howe, Jeff. “The Rise of Crowdsourcing”, Wired Magazine , Issue 14.06, June 2006
  3. Crowdsourcing Digitization
    • Crowd?
      • Patrons and Co-workers
    • Capturing digitization for patron request
      • Selection is driven by patron request
    • Centralized and Decentralized staffing for digitization
    • Object : Build robust digital collections
    • Online collections dense enough for systematic research (not just showcases)
  4. Crowdsourcing Digitization
    • The Wisdom of Crowds
      • How the project was conceived and developed: success story
    • The Madness of Crowds
      • How the project failed, why: bringing it back from the brink
    • Crowd Control
      • Methods used and lessons learned
    • Attracting a Crowd
      • Critical mass for the masses: why we digitize
  5. The Wisdom of Crowds
  6. The Wisdom of Crowds
    • Project Background: Archives and Special Collections
      • Digital image management for archives and special collections
      • Reducing redundancy – many items requested for digitization more than once, why not track them?
    • Digital Collections and Research (DCR)
      • New office to coordinate digitization efforts established
      • Establishing a digital repository
      • More ambitious than just image management
    Image management = capturing patron scanning workflow to populate the new repository
  7. The Wisdom of Crowds
    • Coordination between Archives and Digital Collections:
      • New metadata schema
      • New best practice guidelines
    • Developing Repository
      • Fedora required development
    Meanwhile, patron scanning continues to grow…
  8. The Wisdom of Crowds
    • Answer: Scanning Database
      • Microsoft Access database: “stop-gap measure” while digital repository was being built
      • Corresponded to newly created XML schema and metadata requirements for repository
  9. The Wisdom of Crowds
  10. The Wisdom of Crowds
    • Biggest beneficiary: University Archives
      • Receives the most scanning requests from patrons
      • Capture patron requests, as well as items scanned prior to implementation of Scanning Database
      • University celebrating 150 th anniversary
        • Documentary
        • “ Coffee table” book
        • Departmental histories
        • Nostalgic alumnae
  11. The Wisdom of Crowds
    • Collections created by crowdsourcing digitization:
      • University AlbUM
      • National Trust for Historic Preservation Postcard Collection
  12. The Madness of Crowds
  13. The Madness of Crowds
    • Evolution
      • Evolving standards for both metadata and imaging
    • Training/Quality
    • (dis)Organization
    • Backlog
    www.funnyfreepics.com
  14. The Madness of Crowds
    • Evolution
      • Quality of legacy scans
        • file types
        • spatial resolutions
        • Color profiles
        • Clipping, noise, and other “problems”
        • Flawed equipment
    • Training/Procedures
    • (dis)Organization
    • Backlog
  15. The Madness of Crowds Rotated 90º Rotated 180º 24-bit color 300 dpi tif 8-bit 600 dpi tif 48-bit color 600 dpi tif Bitonal EPS 16-bit 300 dpi JPEG indexed color 72 dpi gif PDF???
  16. The Madness of Crowds
    • Evolution
      • Metadata Quality
        • Lack of experience with controlled vocabularies and input standards
        • Changing metadata requirements
    • Training/Procedures
    • (dis)Organization
    • Backlog
    The Madness of Crowds It’s not quite wrong… but, it’s not quite right
    • Evolution
    • Training/Procedures
      • No standard guidelines for scanning procedures
      • No quality control procedures for images or metadata
      • No one to set them up anyway…
    • (dis)Organization
    • Backlog
    The Madness of Crowds
  17. The Madness of Crowds
  18. The Madness of Crowds
  19. The Madness of Crowds
    • Evolution
    • Training/Procedures
    • (dis)Organization
      • Does everything fit in a “collection?
    • Backlog
  20. The Madness of Crowds
    • Evolution
    • Training/Procedures
    • (dis)Organization
    • Backlog
      • Robust metadata standard to enable repurposing and “sharability”
      • Could take 10x more time to do metadata than scanning
      • Volume of scanning didn’t leave much time for metadata
  21. The Madness of Crowds
  22. Crowd Control
    • Create Documentation
    • “ Teachable” standard
    • Responsibility
    • Quality
    • Divide and Conquer?!?
    Crowd Control
  23. Crowd Control
    • Create Documentation
    • TEACH it
    • Responsibility
    • Quality: Live it, Learn it, Love it
    • Divide and Conquer
      • 6. file format
      • 3. straightness and placement
      • 1. resolution
      • 2. color
      • 4. reference points (targets)
      • 5. noise
  24. Crowd Control Puglia, 2007 Imaging Environment Defined Image State RAW Prepped for a specific output Output Referred - looks towards output Input Referred - looks towards sensor Original Referred - defined relationship between original and digital version Current Practice Emerging Practice More technical metadata is needed Should be able to get by with less technical metadata
    • Create documentation
    • TEACH it!
    • Quality: Live it, Learn it, Love it
      • Have curatorial staff check for accuracy and completeness
      • DCR staff follow up with a check of a statistically significant portion for style and consistency
      • Eventually, give curatorial staff to make corrections as they find them using the web-based administrative form
    • Responsibility
    • Divide and conquer?!?
    Crowd Control
    • Documentation
    • “ Teachable” standard
    • Quality: Live it, Learn it, Love it
    • Responsibility
      • Someone has to have some
      • But it doesn’t have to be an entire job
    • Divide and Conquer
    Crowd Control
    • Create documentation
    • TEACH it!
    • Quality: Live it, Learn it, Love it
    • Responsibility
    • Divide and conquer?!?
      • Stub record created at request time; Cataloging enhances
    Crowd Control
  25. Crowd Control
    • Create documentation
    • TEACH it!
    • Quality: Live it, Learn it, Love it
    • Responsibility
    • Divide and conquer
    • Give up
      • Less control, more power
  26. Crowd Control
    • Would you want to try this?
      • Give yourself room to evolve and change through the project
      • Don’t feel like every image is a precious snowflake
      • More than any single technique, it’s the philosophy of crowdsourcing that’s more important
  27. Crowd Control
    • Would you want to try this?
      • Don’t feel like every image is a precious snowflake
    l Access to a low-quality scan… … is still better than no access at all.
    • Would you want to try this?
      • More than any single technique, it’s the philosophy of crowdsourcing that’s important
  28. Crowd Control
  29.  
  30. Attracting a Crowd
  31. Attracting a Crowd
    • Letting Go
      • “ Letting go” creates efficiencies
      • Looking at expertise across the Libraries
      • Distribute the burden
    • Move away from “trophy” collections
    • toward online Research Collections
  32. Attracting a Crowd
    • Distributed Problem-solving
      • Ideas from Archives:
        • Organizing repository by subject rather than by collection
        • Dabbling in folder-level description (and digitization) rather than just item-level
    • Neutral Collection-building
      • Erway, Ricky and Jennifer Schaffner. 2007, “Gearing Up to Get Into the Flow.” Report produced by OCLC Programs and Research (formerly RLG)
  33. Attracting a Crowd
    • Distributed Problem-solving
      • Ideas from Archives:
        • Using “stub records” from patron request forms
        • Dabbling in folder-level description (and digitization) rather than just item-level
    • “ Neutral” Collection-building
      • Wikipedia-style collection-building
      • Building a collection with wide range
  34. Attracting a Crowd
    • Mass digitization
      • Google projects:
        • Books
        • Newspapers
    • Mass decision- making
      • Instead of item-level decision-making
  35. Attracting a Crowd
    • Making Digitization a Core Function of the Library
      • Mission Statements come to life!
      • Organizing around digitization – very little has really been done yet
    Why? For researchers
    • “ Fringe activities” need to become core investments
      • Metadata creation
      • Digitization
    Council on Library and Information Resources (CLIR). No Brief Candle: Reconceiving Research Libraries for the 21 st Century , 2008.
  36. Crowdsourcing Digitization
    • THANKS!
    • Access these slides at:
    • http://www.personal.ecu.edu/presentations/Crowdsourcing.ppt
    • Or:
    • http://www.slideshare.net
    Gretchen Gueguen [email_address] East Carolina University Greenville, North Carolina Ann Hanlon [email_address] Marquette University Milwaukee, Wisconsin

+ Gretchen GueguenGretchen Gueguen, 2 years ago

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