Trevor Owens discusses the complexities of crowdsourcing cultural heritage, emphasizing that successful projects involve engaged volunteers rather than large anonymous crowds. He explores concepts like human computation, wisdom of crowds, scaffolding user expertise, and intrinsic motivation, stressing the importance of community involvement and the tools needed for effective participation. Key questions addressed include how to enhance human judgment in digital processes, empower users, and foster a sense of purpose among contributors.

1. The Crowd &
the Library
The agony and the ecstasy of
“crowdsourcing” our cultural heritage
Trevor Owens
@tjowens
May 4th, 2012

2. Two problems with
Crowdsourcing

3. First Problem:
the word Crowd

4. Crowds

5. Most successful crowdsourcing
projects are not about large
anonymous masses of people.
They are about inviting
participation from relatively
small interested and engaged
members of the public.

6. Volunteers

7. These projects can continue a
long standing tradition of
volunteerism and involvement
of citizens in the creation and
continued development of
public goods

8. Second Problem:
the term Sourcing

9. Sourcing
is for labor

10. “Work consists of whatever a
body is obliged to do.
Play consists of whatever a
body 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 the
best possible sense of the
word.

12. Amateur: (French amateur
"lover of“) a person attached
to a particular pursuit, study,
or science, without pay and
often without formal training.

13. Still, we are stuck
with the word
crowdsourcing

14. Toward a richer crowdsourcing
1.Human Computation
2.The Wisdom of Crowds
3.Scaffolding Users into Expertise
4.Understanding Motivation

15. Human
Computation
people as computers.

16. People can make
judgments that
computers cant.

19. Human computation
sees people as
machines.

20. Human competition
is often about labor.

23. Human computation
is most interesting
when it isn’t about
labor.

25. Human computation’s
Key Question:
How could we use human
judgment to augment computer
processable information?

26. Wisdom of Crowds
The question of the web is
“Why Wasn’t I Consulted”

27. Wikipedia has
nothing to do with
human computation.

29. Why Wasn’t I Consulted:
is the fundamental question of the web…
Humans have a fundamental need to be
consulted, engaged, to exercise their
knowledge (and thus power), and no
other medium that came before has
been able to tap into that as effectively.
The Web Is a Customer Service Medium, Paul Ford

30. If you tap into the human need to be
consulted you can get some interesting
reactions. 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 site
with comments, 4Chan, Encyclopedia
Dramatica. Plus the entire Open Source
movement.
The Web Is a Customer Service Medium, Paul Ford

32. Wisdom of Crowd’s
Key Question:
How could we empower and
consult with a community of
users?

33. Scaffolding Users
into expertise
The right tools for the job

34. Scaffolding
puts one in
position to
do a job.

35. Helping someone succeed is
often about getting them the right
tools. All tools can act as
scaffolds to break down a task.
We frequently embed our
expertise inside our tools.

36. Measuring the Diameter of a tree
1. 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 )
= 42
5. Isolate the diameter by dividing 22, obtaining
42/22
6. Reduce the fraction 42/22 1.9 feet

37. Or…

38. Just use a measuring tape that
has the algorithm for diameter
embedded inside it and let it
think for you.
From Distributed Intelligence, Roy Pea

40. All tools can act as scaffolds to
break down a task. We frequently
embed our expertise inside our
tools. For example…

42. Example:
Getting People to Translate a
Firefox Extension is hard.

43. They need to know English, how to
edit Firefox locale files, and another
language to make any sense of this.

44. BabelZilla Made it so they only
needed to know the languages.

45. Scaffolding Users
Key Question:
How can our tools act as
scaffolds to help make the most
of users efforts?

46. Helping someone succeed is
often about getting them the right
tools. All tools can act as
scaffolds to break down a task.
We frequently embed our
expertise inside our tools.

47. Motivation
Who would want to do this and
why?

48. A quick story about motivation

49. Ben Brumfield runs a range of
crowdsourcing transcription projects.
At one point in a transcription project
he noticed that one of his power
users was slowing down, cutting
back significantly on transcribing
these manuscripts.

50. The user explained that they had
seen that there weren’t that many
manuscripts left to transcribe.

51. For this user, the 2-3 hours a day
they spent working on transcriptions
was an important part of their day
that they had decided to deny
themselves some of that
experience.

52. They needed to ration it out.
They needed to make sure that it
lasted.

53. After our basic needs are covered, the
things that generally matter most to us
are
Purpose: causes we care for
Identity: things that define us
Meaning: doing things that matter
Belonging: being a part of something

54. Motivating Users
Key Question:
Whose sense of purpose does
this project connect to? What
identities are involved?

55. 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?

56. Example Project Goals and Measures
Social Metadata for Libraries, Archives, and Museums, Karen Smith-Yoshimura and Rose Holley

57. Stages in Web Archiving to Consider
1.Identifying Collecting Targets
2.Quality Assurance
3.Cataloging and Organizing
4.Extracting Metadata
5.Exhibiting and Contextualizing