making research more efficient     kaitlin thaney @kaythaney ; @digitalsci  #idcc13, amsterdam
london bostonnew york tokyo
(3)
machines  researchersdecision makers
machines  researchersdecision makers
discovery is still  sub-optimal.(an example in chemistry)
still the starting point
specific DBs no better (in this case, likely worse)
name disambiguation103-90-2254-465-14-(Acetylamino)phenol4-13-00-01091 (Beilstein Handbook Reference)4-Acetaminophenol4-Hy...
streamline  search
Link to other open chemistry resources
machines researchersdecision makers
our definition of“data” is changing.  (or, at least, is long overdue to.)
CC-BY-2.0 - Plaxco Lab - http://www.flickr.com/photos/34857812@N04/
CC-BY-2.0 - Plaxco Lab - http://www.flickr.com/photos/34857812@N04/
protocolsparameterscalibration misc. lit
ordering             +        processingthe non-digital
use data to better  optimise, enable(behaviour, productivity, reproducibility...)
T[citable, sharable, discoverable]                ext
Sigma Life Science                                This was the worst ordering experience of                     Labrat07  ...
a smarter, open alternative
topline data on figshare: bit.ly/11w7MnEhttp://www.nature.com/news/safety-survey-reveals-lab-risks-1.12121
machines  researchersdecision makers
working on social problems using    software
rewards, incentives    the “why”
existing system is imperfect  authority -> distributive   ability to add context
administrators /     funders as influencers   drivers ofbehavioral change
changing models of    authority  ?
we’re battlingtradition, not just   technology.
k.thaney@digital-science.com   www.digital-science.com
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
Making research more efficient - IDCC '13
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Making research more efficient - IDCC '13

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Making research more efficient - IDCC '13

  1. 1. making research more efficient kaitlin thaney @kaythaney ; @digitalsci #idcc13, amsterdam
  2. 2. london bostonnew york tokyo
  3. 3. (3)
  4. 4. machines researchersdecision makers
  5. 5. machines researchersdecision makers
  6. 6. discovery is still sub-optimal.(an example in chemistry)
  7. 7. still the starting point
  8. 8. specific DBs no better (in this case, likely worse)
  9. 9. name disambiguation103-90-2254-465-14-(Acetylamino)phenol4-13-00-01091 (Beilstein Handbook Reference)4-Acetaminophenol4-Hydroxyacetanilide4-Hydroxyanilid kyseliny octoveAcetamide, N-(4-hydroxyphenyl)-Acetamide, N-(p-hydroxyphenyl)-Acetanilide, 4-hydroxy-APAPN-(4-Hydroxyphenyl)acetamidN-(4-Hydroxyphenyl)acetamideN-(4-Hydroxy-phenyl)-acetamideN-(4-Hydroxyphényl)acétamideN-(4-Hydroxyphenyl)acetanilideN-(p-hydroxyphenyl)acetamideN-Acetyl-4-aminophenolN-Acetyl-p-aminophenol ... and the list goes on ...
  10. 10. streamline search
  11. 11. Link to other open chemistry resources
  12. 12. machines researchersdecision makers
  13. 13. our definition of“data” is changing. (or, at least, is long overdue to.)
  14. 14. CC-BY-2.0 - Plaxco Lab - http://www.flickr.com/photos/34857812@N04/
  15. 15. CC-BY-2.0 - Plaxco Lab - http://www.flickr.com/photos/34857812@N04/
  16. 16. protocolsparameterscalibration misc. lit
  17. 17. ordering + processingthe non-digital
  18. 18. use data to better optimise, enable(behaviour, productivity, reproducibility...)
  19. 19. T[citable, sharable, discoverable] ext
  20. 20. Sigma Life Science This was the worst ordering experience of Labrat07 my career. The antibody was fake, causing my a 8 month loss to my research. NEVER again. Text
  21. 21. a smarter, open alternative
  22. 22. topline data on figshare: bit.ly/11w7MnEhttp://www.nature.com/news/safety-survey-reveals-lab-risks-1.12121
  23. 23. machines researchersdecision makers
  24. 24. working on social problems using software
  25. 25. rewards, incentives the “why”
  26. 26. existing system is imperfect authority -> distributive ability to add context
  27. 27. administrators / funders as influencers drivers ofbehavioral change
  28. 28. changing models of authority ?
  29. 29. we’re battlingtradition, not just technology.
  30. 30. k.thaney@digital-science.com www.digital-science.com
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