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Making the web work for science - RIT Dean's Lecture Series

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Making the web work for science - RIT Dean's Lecture Series

  1. 1. kaitlin thaney @kaythaney ; @mozillascience RIT / 17 march 2015 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. power, performance, scale
  6. 6. our current systems are designed to create friction. despite original intentions.
  7. 7. current state of science articles data patents
  8. 8. some have a firehose articles data patents
  9. 9. 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
  10. 10. downside of output-driven recognition systems
  11. 11. “There’s greater reward, and more temptation to bend the rules.” - David Resnik, bioethicist
  12. 12. (1)
  13. 13. leveraging the power of the web for scholarship
  14. 14. - 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”
  15. 15. what do we mean by “open research”? community technology practices collaborative interoperable open review participatory discoverable data management recognition open tools sharing / reuse mentorship designed for reuse documentation / versioning
  16. 16. (example)
  17. 17. let’s look at an example
  18. 18. 2004-2010 $350 million spent 70+ tools created
  19. 19. we’re rewarding the wrong behavior. at the sacrifice of scientific progress.
  20. 20. Source: Michener, 2006 Ecoinformatics.
  21. 21. Source: Wolkovich et al. GCB 2012.
  22. 22. “... up to 70 percent of research from academic labs cannot be reproduced, representing an enormous waste of money and effort.” - Elizabeth Iorns, Science Exchange
  23. 23. wasted ... $$$ time resource opportunity
  24. 24. $60m+ for “management” - Joe Gray Oregon Health + Science University Center “We are used to billion-dollar software, and it’s not what we can afford. I am worried that unless we rein in our expectations, we will do this experiment again and we will get the same result ...”
  25. 25. instill best (digital, reproducible) practice “research hygiene”
  26. 26. (2)
  27. 27. our systems need to talk to one another. applying lessons from open source development
  28. 28. code as a research object what’s needed to reuse ? http://bit.ly/mozfiggit
  29. 29. (community driven) metadata for software discovery: JSON-LD http://bit.ly/mozfiggit
  30. 30. http://softwarediscoveryindex.org/report/
  31. 31. open, iterative development the “work in progress” effect
  32. 32. Instead of cancer driving the development of technology, it was the development of technology that drove caBIG moving into position where this technology could be adopted by individuals who were interested in cancer. - Andrea Califano Columbia University “ “
  33. 33. [Their] approach to fulfilling [their] mission was upside down. - Andrea Califano Columbia University “ “
  34. 34. (3)
  35. 35. our practices are limiting us. how to further adoption of open, web-enabled science?
  36. 36. 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 ...
  37. 37. social software hardware infrastructure layers
  38. 38. “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.
  39. 39. “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.
  40. 40. fostering a (sustainable) community of practitioners
  41. 41. rethinking “professional development”
  42. 42. current activity: 250+ instructors (60+, training) 5000+ learners
  43. 43. resbaz.edu.au
  44. 44. next global sprint: june 4-5, 2015 mozillascience.org/collaborate
  45. 45. lowering barriers to entry (not expectations)
  46. 46. focus on building capacity, not just more nodes.
  47. 47. (4)
  48. 48. shifting practice (and getting it to stick) is challenging. (takeaways and closing caveats.)
  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, incentives what are the necessary components?
  51. 51. Source: Piwowar, et al. PLOS.
  52. 52. 1. bake reproducible practices into the fabric of research.
  53. 53. 2. design to unlock latent potential of our systems. (the technology is already there.)
  54. 54. 3. rethink how we reward researchers and support roles. (and don’t be afraid to hit refresh.)
  55. 55. 4. be mindful of jargon/ semantics traps.
  56. 56. we’re here to help. teach, contribute, learn. http://mozillascience.org sciencelab@mozillafoundation.org
  57. 57. kaitlin@mozillafoundation.org @kaythaney ; @mozillascience special thanks:

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