0
kaitlin thaney
@kaythaney ; @mozillascience
eResearch NZ / 2 july 2014
making the web work
for science
doing good is part of our code
help researchers use the
power of the open web to
change science’s future.
(0)
science is still (largely)
rooted in 17th c. practices.
(with more powerful horses)
early forms of knowledge sharing
our current systems are
designed to create
friction.
despite original intentions.
we’re locked in old mechanisms.
What Des-Cartes did was a good step.
You have added much several ways, &
especially in taking ye colours of thin
plates in...
existing system is imperfect
traditions last not because they are
excellent, but because influential
people are averse to change and
because of the shee...
power, performance, scale
current state of science
articles
data
patents
some have a firehose
articles
data
patents
(1)
leveraging the power of
the web for scholarship
- access to content, data, code, materials.
- emergence of “web-native” tools.
- rewards for openness, interop, collaborat...
emergence of new
communities, practice
research cycle
idea
experiment
lit review
materials
publish
share results
retest
analyze
collect data
types of information
hypothesis/query
protocols
parameters
content
non-digital “stuff”
articles
proceedings
negative resul...
blocking points
idea
experiment
access
attaining
materials
publish
share results
retest
analyze
collect data
(to name a fe...
how to shift practice
towards open?
routine
rewardcue
Source: Michener, 2006 Ecoinformatics.
Source: Wolkovich et al. GCB 2012.
wasted ...
$$$
time
resource
opportunity
(2)
looking beyond “open”
is access enough?
code
(interop)
community
(people)
code/data literacy
(means to learn/engage)
our systems need to
talk to one another.
leveraging open technology, existing infrastructure.
unpacking what the web
can do for science
code as a research object
what’s needed to reuse ?
http://bit.ly/mozfiggit
code as a research object
http://xkcd.com/285/
http://bit.ly/mozfiggit
(community driven)
metadata for software discovery: JSON-LD
http://bit.ly/mozfiggit
(3)
our practices are
limiting us.
how best move towards adoption?
“web-enabled science”
- access to content, data, code, materials.
- emergence of “web-native” tools.
- rewards for opennes...
“web-enabled science”
what’s missing?
- access to content, data, code, materials.
- emergence of “web-native” tools.
- rew...
social
software
hardware
infrastructure layers
“the social
infrastructure”
routine
rewardcue
upping our digital literacy
upping our digital literacy
“Reliance on
ad-hoc, self-
education
about what’s
possible
doesn’t scale.”
- Selena Decklemann
current activity:
130+ instructors
(60+, training)
3700+ learners
instill best
(digital,
reproducible)
practice
“research hygiene”
building capacity locally
(join us.)
focus on building capacity,
not just more nodes.
(4)
shifting practice
(and getting it to stick)
is challenging.
... but not impossible.
63 nations
10,000 scientists
50,000 participants
can we do the same
for research on the web?
tools and technology
cultural awareness, best practice
connections, open dialogue
skills training
what are the necessary c...
Source: Piwowar, et al. PLOS.
(5)
the future is here ...
it’s just not evenly distributed.
- william gibson
“
“
operating in isolation
doesn’t scale.
coordination is key.
open as an accelerant.
build capacity, community.
join us
(and the conversation.)
teach, contribute, learn.
http://software-carpentry.org
http://mozillascience.org
kaitlin@mozillafoundation.org
@kaythaney ; @mozillascience
special thanks:
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
Making the web work for science - eResearch nz
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Making the web work for science - eResearch nz

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Keynote for eResearch NZ conference at Waikato University

Published in: Science, Technology, Education

Transcript of "Making the web work for science - eResearch nz"

  1. 1. kaitlin thaney @kaythaney ; @mozillascience eResearch NZ / 2 july 2014 making the web work for science
  2. 2. doing good is part of our code
  3. 3. help researchers use the power of the open web to change science’s future.
  4. 4. (0)
  5. 5. science is still (largely) rooted in 17th c. practices. (with more powerful horses)
  6. 6. early forms of knowledge sharing
  7. 7. our current systems are designed to create friction. despite original intentions.
  8. 8. we’re locked in old mechanisms.
  9. 9. 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 “ “
  10. 10. existing system is imperfect
  11. 11. 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
  12. 12. power, performance, scale
  13. 13. current state of science articles data patents
  14. 14. some have a firehose articles data patents
  15. 15. (1)
  16. 16. leveraging the power of the web for scholarship
  17. 17. - access to content, data, code, materials. - emergence of “web-native” tools. - rewards for openness, interop, collaboration, sharing. - push for ROI, reuse, recomputability, transparency. “web-enabled science”
  18. 18. emergence of new communities, practice
  19. 19. research cycle idea experiment lit review materials publish share results retest analyze collect data
  20. 20. types of information hypothesis/query protocols parameters content non-digital “stuff” articles proceedings negative results analysis code datasets models (added complexity) prof activities mentorship teaching activities
  21. 21. blocking points idea experiment access attaining materials publish share results retest analyze collect data (to name a few ...)
  22. 22. how to shift practice towards open? routine rewardcue
  23. 23. Source: Michener, 2006 Ecoinformatics.
  24. 24. Source: Wolkovich et al. GCB 2012.
  25. 25. wasted ... $$$ time resource opportunity
  26. 26. (2)
  27. 27. looking beyond “open” is access enough?
  28. 28. code (interop) community (people) code/data literacy (means to learn/engage)
  29. 29. our systems need to talk to one another. leveraging open technology, existing infrastructure.
  30. 30. unpacking what the web can do for science
  31. 31. code as a research object what’s needed to reuse ? http://bit.ly/mozfiggit
  32. 32. code as a research object http://xkcd.com/285/ http://bit.ly/mozfiggit
  33. 33. (community driven) metadata for software discovery: JSON-LD http://bit.ly/mozfiggit
  34. 34. (3)
  35. 35. our practices are limiting us. how best move towards adoption?
  36. 36. “web-enabled science” - access to content, data, code, materials. - emergence of “web-native” tools. - rewards for openness, interop, collaboration, sharing. - push for ROI, reuse, recomputability, transparency.
  37. 37. “web-enabled science” what’s missing? - access to content, data, code, materials. - emergence of “web-native” tools. - rewards for openness, interop, collaboration, sharing. - push for ROI, reuse, recomputability, transparency.
  38. 38. social software hardware infrastructure layers
  39. 39. “the social infrastructure” routine rewardcue
  40. 40. upping our digital literacy
  41. 41. upping our digital literacy
  42. 42. “Reliance on ad-hoc, self- education about what’s possible doesn’t scale.” - Selena Decklemann
  43. 43. current activity: 130+ instructors (60+, training) 3700+ learners
  44. 44. instill best (digital, reproducible) practice “research hygiene”
  45. 45. building capacity locally (join us.)
  46. 46. focus on building capacity, not just more nodes.
  47. 47. (4)
  48. 48. shifting practice (and getting it to stick) is challenging. ... but not impossible.
  49. 49. 63 nations 10,000 scientists 50,000 participants can we do the same for research on the web?
  50. 50. tools and technology cultural awareness, best practice connections, open dialogue skills training what are the necessary components?
  51. 51. Source: Piwowar, et al. PLOS.
  52. 52. (5)
  53. 53. the future is here ... it’s just not evenly distributed. - william gibson “ “
  54. 54. operating in isolation doesn’t scale.
  55. 55. coordination is key. open as an accelerant. build capacity, community.
  56. 56. join us (and the conversation.) teach, contribute, learn. http://software-carpentry.org http://mozillascience.org
  57. 57. kaitlin@mozillafoundation.org @kaythaney ; @mozillascience special thanks:
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