The document discusses challenges with the current scientific research system and proposes moving towards a more "open science" model. It notes that the existing system was not designed for knowledge sharing and reproducibility. Open science principles advocate for open access to content, data, code, and materials in order to enable greater collaboration, reuse of results, and transparency. However, moving research practices will require building skills and changing incentives across the scientific community. The document calls for coordinating efforts to provide training, establish best practices, and foster connections to support operating research on the web in a more open and interoperable manner.

1. making the web
work for science
kaitlin thaney
@kaythaney ; @mozillascience
univ. of north dakota / 5 feb 2014

2. doing good is part of our code

3. help researchers use the
power of the open web to
change science’s future.

4. (0)

5. science is still (largely)
rooted in 17th c. practices.
(and not in that “retro is cool” sort of way.)

6. early forms of knowledge sharing

11. our current systems are
designed to create
friction.
despite original intentions.

13. “ What Des-Cartes did was a good step.
You have added much several ways, &
especially in taking ye colours of thin
plates into philosophical consideration.
If I have seen further it is by standing on
ye shoulders of Giants.
“
- Isaac Newton, 1676

14. existing system is imperfect

16. data,

17. ability to reproduce experiments,

18. incentive to change,

19. “ traditions last not because they are
excellent, but because influential
people are averse to change and
because of the sheer burdens of
transition to a better state ... “
Cass Sunstein

20. (1)

21. “open science”
- access to content, data, code, materials.
- emergence of “web-native” tools.
- rewards for openness, interop, collaboration, sharing.
- push for ROI, reuse, recomputability, transparency.

22. research cycle
idea
publish
lit review
share results
analyze
materials
retest
collect data
experiment

23. types of information
(added complexity)
articles
proceedings
hypothesis/query
prof activities
mentorship
teaching activities
negative results
content
non-digital “stuff”
protocols
parameters
analysis
code
datasets
models

24. blocking points
(to name a few ...)
idea
access
publish
attaining
materials
share results
analyze
retest
collect data
experiment

25. “... up to 70% of research from academic labs
cannot be reproduced, representing an enormous
waste of money and effort.”
- Elizabeth Iorns, Science Exchange

26. Source: Michener, 2006 Ecoinformatics.

28. (2)

29. is open enough?
what does it mean to “operate on/like the web”?

30. code
(interop)
community
(people)
code/data literacy
(means to learn/engage)

31. our systems need to
talk to one another.

34. “One worry I have is that, with reviews like this, scientists will be
even more discouraged from publishing their code [...] We need
to get more code out there, not improve how it looks.”

35. code as a research object
what’s needed
to reuse ?

36. code as a research object
http://xkcd.com/285/

37. “There’s greater reward,
and more temptation to
bend the rules.”
- David Resnik, bioethicist

40. (3)

41. we need to even
(/ elevate) the playing field.

42. facing a digital skills gap

44. “Reliance on
ad-hoc, selfeducation
about what’s
possible
doesn’t scale.”
- Selena Decklemann

48. learn from open source
(culture as well as technology)

49. current activity:
129 instructors
(60+, training)
109 bootcamps
3700+ learners

50. we need to build capacity,
not just more nodes.

51. “research hygiene”
instill best
(digital,
reproducible)
practice

53. in an increasingly digital, datadriven world, what core skills, tools
do the next-generation need?

54. education as a means of
building community
... globally, as well as across disciplines.

55. (4)

56. shifting practice
(and getting it to stick)
is challenging.
... but not impossible.

57. disciplines as cultures

59. can we do the same
for research on the web?
63 nations
10,000 scientists
50,000 participants

60. what are the necessary components?
tools and technology
cultural awareness, best practice
connections, open dialogue
skills training

61. (5)

62. operating in isolation
doesn’t scale.

63. coordination and
collaboration are key.
design for interoperability.
remember the
non-technical challenges.

64. join us
(and the conversation.)
teach, contribute, learn.
http://software-carpentry.org
http://mozillascience.org

65. questions?
kaitlin@mozillafoundation.org
@kaythaney ; @mozillascience