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kaitlin thaney
@kaythaney ; @mozillascience
grand rounds / 27 may 2015
building capacity for open,
data-driven science
doing good is part of our code
help researchers leverage
the power of the open web.
learning around
open source, data sharing
needed to further open practice;
empowering others to lead in
their communities.
code
(interop)
community
(people)
code/data literacy
(means to learn/engage)
(0)
communication
access, reuse, scale
community-building
the web as a platform
power, performance, scale
our current systems are
designed to create
friction.
despite original intentions.
current state of science
articles
data
patents
patients
some have a firehose
articles
data
patents
patients
quality versus quantity
measured systems
Source: Michener, 2006 Ecoinformatics.
“There’s greater reward,
and more temptation to
bend the rules.”
- David Resnik, bioethicist
(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...
research social capital capacity
infrastructure layers for
efficient, reproducible research
open tools
standards
best pract...
our models of discovery
are rapidly evolving.
moving from the specialist to the adaptive generalist.
“
“
“
“
more data, more demand, higher understanding
http://www.bmj.com/content/350/bmj.g7785
http://www.myopennotes.org/
wasted ...
$$$
time
resource
opportunity
(2)
learning from (+ through)
open source
applying lessons from open source
development to science
code as a research object
what’s needed to reuse ?
http://bit.ly/mozfiggit
http://softwarediscoveryindex.org/report/
open, iterative
development
the “work in progress” effect
http://openresearchbadges.org/
http://mozillascience.org/contributorship-badges-a-new-project/
(3)
how do we build
capacity?
furthering adoption of
open, data-driven science
fostering a (sustainable)
community of practitioners
rewards, incentives,
reputation
Source: Piwowar, et al. PLOS.
supports needed for
“professional development”
“Reliance on
ad-hoc, self-
education
about what’s
possible
doesn’t scale.”
- Selena Decklemann
https://mozillascience.github.io/studyGroupHandbook/
resbaz.edu.au
next global sprint: june 4-5, 2015
mozillascience.org/collaborate
in an increasingly digital, data-
driven world, what core skills, tools
do the next-generation need?
lowering barriers to entry
(+ leveling the playing field)
focus on building capacity,
not just more nodes.
(4)
shifting practice
(and getting it to stick)
is challenging.
(takeaways and closing caveats.)
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, incentives
what are the...
coordination and
collaboration are key.
design for interoperability.
remember the
non-technical challenges.
we’re here to help.
http://mozillascience.org
sciencelab@mozillafoundation.org
kaitlin@mozillafoundation.org
@kaythaney ; @mozillascience
special thanks:
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
Building capacity for open, data-driven science - Grand Rounds
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Building capacity for open, data-driven science - Grand Rounds

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Grand Rounds at Strong Memorial and Rochester General Hospitals, May 26-27, 2015.

Veröffentlicht in: Technologie
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Building capacity for open, data-driven science - Grand Rounds

  1. 1. kaitlin thaney @kaythaney ; @mozillascience grand rounds / 27 may 2015 building capacity for open, data-driven science
  2. 2. doing good is part of our code
  3. 3. help researchers leverage the power of the open web.
  4. 4. learning around open source, data sharing needed to further open practice; empowering others to lead in their communities.
  5. 5. code (interop) community (people) code/data literacy (means to learn/engage)
  6. 6. (0)
  7. 7. communication access, reuse, scale community-building the web as a platform
  8. 8. power, performance, scale
  9. 9. our current systems are designed to create friction. despite original intentions.
  10. 10. current state of science articles data patents patients
  11. 11. some have a firehose articles data patents patients
  12. 12. quality versus quantity measured systems
  13. 13. Source: Michener, 2006 Ecoinformatics.
  14. 14. “There’s greater reward, and more temptation to bend the rules.” - David Resnik, bioethicist
  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 research”
  18. 18. research social capital capacity infrastructure layers for efficient, reproducible research open tools standards best practices research objects scientific software repositories incentives recognition / P&T interdisciplinarity collaboration community dialogue training mentorship professional dev new policies recognition stakeholders: universities, researchers, tool dev, funders, publishers, medical professionals ...
  19. 19. our models of discovery are rapidly evolving. moving from the specialist to the adaptive generalist.
  20. 20. “ “ “ “
  21. 21. more data, more demand, higher understanding http://www.bmj.com/content/350/bmj.g7785 http://www.myopennotes.org/
  22. 22. wasted ... $$$ time resource opportunity
  23. 23. (2)
  24. 24. learning from (+ through) open source applying lessons from open source development to science
  25. 25. code as a research object what’s needed to reuse ? http://bit.ly/mozfiggit
  26. 26. http://softwarediscoveryindex.org/report/
  27. 27. open, iterative development the “work in progress” effect
  28. 28. http://openresearchbadges.org/
  29. 29. http://mozillascience.org/contributorship-badges-a-new-project/
  30. 30. (3)
  31. 31. how do we build capacity? furthering adoption of open, data-driven science
  32. 32. fostering a (sustainable) community of practitioners
  33. 33. rewards, incentives, reputation
  34. 34. Source: Piwowar, et al. PLOS.
  35. 35. supports needed for “professional development”
  36. 36. “Reliance on ad-hoc, self- education about what’s possible doesn’t scale.” - Selena Decklemann
  37. 37. https://mozillascience.github.io/studyGroupHandbook/
  38. 38. resbaz.edu.au
  39. 39. next global sprint: june 4-5, 2015 mozillascience.org/collaborate
  40. 40. in an increasingly digital, data- driven world, what core skills, tools do the next-generation need?
  41. 41. lowering barriers to entry (+ leveling the playing field)
  42. 42. focus on building capacity, not just more nodes.
  43. 43. (4)
  44. 44. shifting practice (and getting it to stick) is challenging. (takeaways and closing caveats.)
  45. 45. 63 nations 10,000 scientists 50,000 participants can we do the same for research on the web?
  46. 46. tools and technology cultural awareness, best practice connections, open dialogue skills training, incentives what are the necessary components?
  47. 47. coordination and collaboration are key. design for interoperability. remember the non-technical challenges.
  48. 48. we’re here to help. http://mozillascience.org sciencelab@mozillafoundation.org
  49. 49. kaitlin@mozillafoundation.org @kaythaney ; @mozillascience special thanks:

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