The crowd and the library
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The crowd and the library

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A talk I gave to kick off the International Internet Preservation Consortium's workshop on crowdsourcing. Most of the talk is about reframing and unpacking the key components of crowdsourcing.

A talk I gave to kick off the International Internet Preservation Consortium's workshop on crowdsourcing. Most of the talk is about reframing and unpacking the key components of crowdsourcing.

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  • 1. The Crowd &the Library The agony and the ecstasy of “crowdsourcing” our cultural heritage Trevor Owens @tjowens May 4th, 2012
  • 2. Two problems withCrowdsourcing
  • 3. First Problem: the word Crowd
  • 4. Crowds
  • 5. Most successful crowdsourcingprojects are not about largeanonymous masses of people.They are about invitingparticipation from relativelysmall interested and engagedmembers of the public.
  • 6. Volunteers
  • 7. These projects can continue along standing tradition ofvolunteerism and involvementof citizens in the creation andcontinued development ofpublic goods
  • 8. Second Problem: the term Sourcing
  • 9. Sourcingis for labor
  • 10. “Work consists of whatever abody is obliged to do.Play consists of whatever abody is not obliged to do.”Mark Twain, The Adventures of Tom Sawyer
  • 11. A Citizen Scientist, Archivist,or Journalist is not a labor.They are Amateurs in thebest possible sense of theword.
  • 12. Amateur: (French amateur"lover of“) a person attachedto a particular pursuit, study,or science, without pay andoften without formal training.
  • 13. Still, we are stuckwith the wordcrowdsourcing
  • 14. Toward a richer crowdsourcing 1.Human Computation 2.The Wisdom of Crowds 3.Scaffolding Users into Expertise 4.Understanding Motivation
  • 15. HumanComputation people as computers.
  • 16. People can makejudgments thatcomputers cant.
  • 17. Human computationsees people asmachines.
  • 18. Human competitionis often about labor.
  • 19. Human computationis most interestingwhen it isn’t aboutlabor.
  • 20. Human computation’sKey Question:How could we use humanjudgment to augment computerprocessable information?
  • 21. Wisdom of CrowdsThe question of the web is “Why Wasn’t I Consulted”
  • 22. Wikipedia hasnothing to do withhuman computation.
  • 23. Why Wasn’t I Consulted:is the fundamental question of the web…Humans have a fundamental need to beconsulted, engaged, to exercise theirknowledge (and thus power), and noother medium that came before hasbeen able to tap into that as effectively. The Web Is a Customer Service Medium, Paul Ford
  • 24. If you tap into the human need to beconsulted you can get some interestingreactions. Here are a few: Wikipedia,StackOverflow, Hunch,Reddit, MetaFilter,YouTube, Twitter, StumbleUpon, About,Quora, Ebay,Yelp, Flickr, IMDB,Amazon.com, Craigslist, GitHub,SourceForge, every messageboard or sitewith comments, 4Chan, EncyclopediaDramatica. Plus the entire Open Sourcemovement. The Web Is a Customer Service Medium, Paul Ford
  • 25. Wisdom of Crowd’sKey Question:How could we empower andconsult with a community ofusers?
  • 26. Scaffolding Usersinto expertise The right tools for the job
  • 27. Scaffoldingputs one inposition todo a job.
  • 28. Helping someone succeed isoften about getting them the righttools. All tools can act asscaffolds to break down a task.We frequently embed ourexpertise inside our tools.
  • 29. Measuring the Diameter of a tree1. Measure the circumference of the tree (6 feet);2. Remember that the diameter is related to the circumference of an object according to the formula circumference/diameter equals 22/ z (or pi);3. Set up the formula, replacing the variable circumference with the value of 6 feet;4. Cross-multiply, getting 22 (diameter-unknown ) = 425. Isolate the diameter by dividing 22, obtaining 42/226. Reduce the fraction 42/22 1.9 feet
  • 30. Or…
  • 31. Just use a measuring tape thathas the algorithm for diameterembedded inside it and let itthink for you. From Distributed Intelligence, Roy Pea
  • 32. All tools can act as scaffolds tobreak down a task. We frequentlyembed our expertise inside ourtools. For example…
  • 33. Example:Getting People to Translate aFirefox Extension is hard.
  • 34. They need to know English, how toedit Firefox locale files, and anotherlanguage to make any sense of this.
  • 35. BabelZilla Made it so they onlyneeded to know the languages.
  • 36. Scaffolding UsersKey Question:How can our tools act asscaffolds to help make the mostof users efforts?
  • 37. Helping someone succeed isoften about getting them the righttools. All tools can act asscaffolds to break down a task.We frequently embed ourexpertise inside our tools.
  • 38. MotivationWho would want to do this andwhy?
  • 39. A quick story about motivation
  • 40. Ben Brumfield runs a range ofcrowdsourcing transcription projects.At one point in a transcription projecthe noticed that one of his powerusers was slowing down, cuttingback significantly on transcribingthese manuscripts.
  • 41. The user explained that they hadseen that there weren’t that manymanuscripts left to transcribe.
  • 42. For this user, the 2-3 hours a daythey spent working on transcriptionswas an important part of their daythat they had decided to denythemselves some of thatexperience.
  • 43. They needed to ration it out.They needed to make sure that itlasted.
  • 44. After our basic needs are covered, thethings that generally matter most to usarePurpose: causes we care forIdentity: things that define usMeaning: doing things that matterBelonging: being a part of something
  • 45. Motivating UsersKey Question:Whose sense of purpose doesthis project connect to? Whatidentities are involved?
  • 46. The Concepts and their Questions • Human Computation: How could we use human judgment to augment computer processable information? • Wisdom of Crowds: How could we empower and consult with a community of users? • Scaffolding: How can our tools act as scaffolds to help make the most of users efforts? • Motivation: Whose sense of purpose does this project connect to? What identities are involved?
  • 47. Example Project Goals and Measures Social Metadata for Libraries, Archives, and Museums, Karen Smith-Yoshimura and Rose Holley
  • 48. Stages in Web Archiving to Consider1.Identifying Collecting Targets2.Quality Assurance3.Cataloging and Organizing4.Extracting Metadata5.Exhibiting and Contextualizing