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Making research more efficient - IDCC '13
1.
making research more
efficient kaitlin thaney @kaythaney ; @digitalsci #idcc13, amsterdam
2.
3.
london boston new york
tokyo
4.
5.
(3)
6.
machines researchers decision
makers
7.
machines researchers decision
makers
8.
discovery is still
sub-optimal. (an example in chemistry)
9.
still the starting
point
10.
specific DBs no
better (in this case, likely worse)
11.
name disambiguation 103-90-2 254-465-1 4-(Acetylamino)phenol 4-13-00-01091 (Beilstein
Handbook Reference) 4-Acetaminophenol 4'-Hydroxyacetanilide 4-Hydroxyanilid kyseliny octove Acetamide, N-(4-hydroxyphenyl)- Acetamide, N-(p-hydroxyphenyl)- Acetanilide, 4'-hydroxy- APAP N-(4-Hydroxyphenyl)acetamid N-(4-Hydroxyphenyl)acetamide N-(4-Hydroxy-phenyl)-acetamide N-(4-Hydroxyphényl)acétamide N-(4-Hydroxyphenyl)acetanilide N-(p-hydroxyphenyl)acetamide N-Acetyl-4-aminophenol N-Acetyl-p-aminophenol ... and the list goes on ...
12.
13.
streamline search
14.
Link to other
open chemistry resources
15.
machines researchers decision makers
16.
our definition of “data”
is changing. (or, at least, is long overdue to.)
17.
CC-BY-2.0 - Plaxco
Lab - http://www.flickr.com/photos/34857812@N04/
18.
CC-BY-2.0 - Plaxco
Lab - http://www.flickr.com/photos/34857812@N04/
19.
20.
21.
protocols parameters calibration misc. lit
22.
ordering
+ processing the non-digital
23.
24.
use data to
better optimise, enable (behaviour, productivity, reproducibility...)
25.
26.
27.
28.
29.
30.
T[citable, sharable, discoverable]
ext
31.
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
32.
a smarter, open
alternative
33.
topline data on
figshare: bit.ly/11w7MnE http://www.nature.com/news/safety-survey-reveals-lab-risks-1.12121
34.
35.
machines researchers decision
makers
36.
working on social
problems using software
37.
rewards, incentives
the “why”
38.
existing system is
imperfect authority -> distributive ability to add context
39.
40.
administrators /
funders as influencers drivers of behavioral change
41.
42.
43.
changing models of
authority ?
44.
we’re battling tradition, not
just technology.
45.
k.thaney@digital-science.com
www.digital-science.com
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