KCALSI Annual Dinner Keynote
@wilbanks
October 1, 2013
1. give me a place to
stand, and a lever, and i
shall move the world.
every age has its
own lever.
ours is cheap data.
cheap data
changes how we
justify our opinions.
OPS = AB(H + BB + HBP) +
TB(AB + BB + SF + HBP) /
AB(AB + BB + SF + HBP)
2. research data v.
consumer data
https://www.scienceexchange.com/
3.
engaging a larger cohort
(or, “crowdsourcing”).
tension between
anonymity and utility.
“more like plutonium
than gold”
tension between
expectation and reuse.
our data isn’t worth much
- on its own.
$.50 to $2.50 for SSN,
birthdate, etc.
$5 to $15 for credit
checks, health records
the value is in the
aggregate.
4.
the current approach
won’t cut it.
33
34
35
36
assume 1,000,000 downloads
assume 10% false positive rate
100,000 doctor visits
$1000 per biopsy
that’s the setup.
sharing by small but
coherent groups can
create asymmetrically
valuable resources.
small group
sharing
proven to work in:
software
content
let’s try a small but
coherent group to
share data and see if it
works in science.
Omberg,	
  et	
  al.	
  Nature	
  Gene*cs
•Analysis of: 12 Tumor types, 6 molecular
profiling platforms
•Focus series of: 4...
68core projects
248researchers
28institutions
1070datasets
1723results
18papers in press
let’s try a small but
coherent group to
share data and see if it
works in health.
“eat less and exercise”
the experiment:
volunteer must click to proceed
all boxes must be checked
http://opensnp.org/users/615
http://files.snpedia.com/reports/promethease_data/genome_jtw_ui2.html
“Also there is no suggestion of
consanguinity in your pedigree.”
http://www.ianlogan.co.uk/
it’s likely that we will
end up with a sharing
monopoly of some sort.
once entrenched, hard to
move.
instinct of institution: to
increment.
a. “just like now, but
moreso”
b. the cartel.
c. an open system.
77
“in the end, all
data is either
deleted or
made public”
- quinn norton
shared data will be
the fulcrum.
thank you
@wilbanks
john.wilbanks@sagebase.org
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
Kansas City Area Life Sciences Institute - keynote @ annual dinner
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Kansas City Area Life Sciences Institute - keynote @ annual dinner

  1. 1. KCALSI Annual Dinner Keynote @wilbanks October 1, 2013
  2. 2. 1. give me a place to stand, and a lever, and i shall move the world.
  3. 3. every age has its own lever.
  4. 4. ours is cheap data.
  5. 5. cheap data changes how we justify our opinions.
  6. 6. OPS = AB(H + BB + HBP) + TB(AB + BB + SF + HBP) / AB(AB + BB + SF + HBP)
  7. 7. 2. research data v. consumer data
  8. 8. https://www.scienceexchange.com/
  9. 9. 3. engaging a larger cohort (or, “crowdsourcing”).
  10. 10. tension between anonymity and utility.
  11. 11. “more like plutonium than gold”
  12. 12. tension between expectation and reuse.
  13. 13. our data isn’t worth much - on its own.
  14. 14. $.50 to $2.50 for SSN, birthdate, etc.
  15. 15. $5 to $15 for credit checks, health records
  16. 16. the value is in the aggregate.
  17. 17. 4. the current approach won’t cut it.
  18. 18. 33
  19. 19. 34
  20. 20. 35
  21. 21. 36
  22. 22. assume 1,000,000 downloads assume 10% false positive rate 100,000 doctor visits $1000 per biopsy
  23. 23. that’s the setup.
  24. 24. sharing by small but coherent groups can create asymmetrically valuable resources.
  25. 25. small group sharing
  26. 26. proven to work in: software content
  27. 27. let’s try a small but coherent group to share data and see if it works in science.
  28. 28. Omberg,  et  al.  Nature  Gene*cs •Analysis of: 12 Tumor types, 6 molecular profiling platforms •Focus series of: 4 papers in Nature Genetics, with 14 more to follow in other NPG journals TCGA Pan-Cancer Consortium
  29. 29. 68core projects
  30. 30. 248researchers
  31. 31. 28institutions
  32. 32. 1070datasets
  33. 33. 1723results
  34. 34. 18papers in press
  35. 35. let’s try a small but coherent group to share data and see if it works in health.
  36. 36. “eat less and exercise”
  37. 37. the experiment:
  38. 38. volunteer must click to proceed all boxes must be checked
  39. 39. http://opensnp.org/users/615
  40. 40. http://files.snpedia.com/reports/promethease_data/genome_jtw_ui2.html
  41. 41. “Also there is no suggestion of consanguinity in your pedigree.” http://www.ianlogan.co.uk/
  42. 42. it’s likely that we will end up with a sharing monopoly of some sort.
  43. 43. once entrenched, hard to move.
  44. 44. instinct of institution: to increment.
  45. 45. a. “just like now, but moreso”
  46. 46. b. the cartel.
  47. 47. c. an open system.
  48. 48. 77
  49. 49. “in the end, all data is either deleted or made public” - quinn norton
  50. 50. shared data will be the fulcrum.
  51. 51. thank you @wilbanks john.wilbanks@sagebase.org
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