digital science and thefuture of online research        kaitlin thaney     policy lunchbox, 3 aug 2011    charles darwin h...
xi. background
technology company   publisher link london, nyc, tokyo
investment arm incubator role  in-house dev
tiered approach    build to scaleresearcher-focused
1. science is changing
1. science is changing    (and the research workflow)
research                   idea     publish                   lit reviewshare results                   materials         ...
blocking points                (to name a few ... )                       idea     publish                      lit review...
types of information                (will revisit later)                       idea     articles                          ...
text text   text
roadblocks     (to name a few) ...specialisation of tools (+/-)      interoperability        accessibility     design deci...
2. key constituencies
(3)
machines  researchersdecision makers
machines  researchersdecision makers
...annotation  markup  search discovery“behind the  scenes”     ...
still the starting point
patents are no better (in many cases, worse)
can streamline
name disambiguation
10,11-dihydro-5-methyl-5H-dibenzo[b,e][1,4]diazepin-11-one     (still strains the minds of the best)
machines  researchersdecision makers
CC-BY-2.0 - Plaxco Lab - http://www.flickr.com/photos/34857812@N04/
trackingexpiration
ordering             +        processingthe non-digital
protocolsparameterscalibration misc. lit
managing information    different types of “data”
“i invented a folder based        system ...”
“i invented a folder based         system ...”“yeah, we had a LIMS. it onlyever got used to store photos    from lab night...
why?experimentation reliancedata moves, grows legsfunder/instit’n pressure
machines  researchersdecision makers
how we measureimpact, reputation etc.
data capture(of a different sort)
the “social issue”         best practices     behaviour roadblocksdiscipline / researcher specific
paper’s still the currency
imperfect system
“Right now were going through a Cambrian explosion of metrics.”                       - Johan Bollen                  Natu...
there’s been a drastic spike in terms of        sheer volume and type
citation / impact factor              h - indexweighted citations (eigenfactor, sjr)     “betweenness centrality”         ...
difficult to ...      harmonisetrack /maintain / map      understand  (even still measure)
tools for decision makers(research admin / funders) using technology to spur       cultural shift
“ what do we wanton the back of our(science) baseball Top Trumps cards? “      - paul groth (et al.)
3. the reality
“the future is here ...       just not evenly          distributed yet.”               - William Gibson
changingunderstandings,  paradigms
technology can helpdesign decisions are key plan for the irrational
more efficient researchincrease productivityenable reproducibility
thank you.k.thaney@digital-science.com   www.digital-science.com        @kaythaney
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
Policy Lunchbox - Digital Science
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Policy Lunchbox - Digital Science

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Policy Lunchbox - Digital Science

  1. 1. digital science and thefuture of online research kaitlin thaney policy lunchbox, 3 aug 2011 charles darwin house, london
  2. 2. xi. background
  3. 3. technology company publisher link london, nyc, tokyo
  4. 4. investment arm incubator role in-house dev
  5. 5. tiered approach build to scaleresearcher-focused
  6. 6. 1. science is changing
  7. 7. 1. science is changing (and the research workflow)
  8. 8. research idea publish lit reviewshare results materials retest analyze experiment collect data
  9. 9. blocking points (to name a few ... ) idea publish lit reviewshare results materials retest analyze experiment collect data
  10. 10. types of information (will revisit later) idea articles content proceedings prof activities mentorship patentsshare results the non-digital “stuff” retest analysis protocols synthesis parameters datasets
  11. 11. text text text
  12. 12. roadblocks (to name a few) ...specialisation of tools (+/-) interoperability accessibility design decisions the “social issue”
  13. 13. 2. key constituencies
  14. 14. (3)
  15. 15. machines researchersdecision makers
  16. 16. machines researchersdecision makers
  17. 17. ...annotation markup search discovery“behind the scenes” ...
  18. 18. still the starting point
  19. 19. patents are no better (in many cases, worse)
  20. 20. can streamline
  21. 21. name disambiguation
  22. 22. 10,11-dihydro-5-methyl-5H-dibenzo[b,e][1,4]diazepin-11-one (still strains the minds of the best)
  23. 23. machines researchersdecision makers
  24. 24. CC-BY-2.0 - Plaxco Lab - http://www.flickr.com/photos/34857812@N04/
  25. 25. trackingexpiration
  26. 26. ordering + processingthe non-digital
  27. 27. protocolsparameterscalibration misc. lit
  28. 28. managing information different types of “data”
  29. 29. “i invented a folder based system ...”
  30. 30. “i invented a folder based system ...”“yeah, we had a LIMS. it onlyever got used to store photos from lab nights out.”
  31. 31. why?experimentation reliancedata moves, grows legsfunder/instit’n pressure
  32. 32. machines researchersdecision makers
  33. 33. how we measureimpact, reputation etc.
  34. 34. data capture(of a different sort)
  35. 35. the “social issue” best practices behaviour roadblocksdiscipline / researcher specific
  36. 36. paper’s still the currency
  37. 37. imperfect system
  38. 38. “Right now were going through a Cambrian explosion of metrics.” - Johan Bollen Nature 465, 864-866 (2010) | doi:10.1038/465864a
  39. 39. there’s been a drastic spike in terms of sheer volume and type
  40. 40. citation / impact factor h - indexweighted citations (eigenfactor, sjr) “betweenness centrality” alt-metrics, etc.
  41. 41. difficult to ... harmonisetrack /maintain / map understand (even still measure)
  42. 42. tools for decision makers(research admin / funders) using technology to spur cultural shift
  43. 43. “ what do we wanton the back of our(science) baseball Top Trumps cards? “ - paul groth (et al.)
  44. 44. 3. the reality
  45. 45. “the future is here ... just not evenly distributed yet.” - William Gibson
  46. 46. changingunderstandings, paradigms
  47. 47. technology can helpdesign decisions are key plan for the irrational
  48. 48. more efficient researchincrease productivityenable reproducibility
  49. 49. thank you.k.thaney@digital-science.com www.digital-science.com @kaythaney

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