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gateways for
open science
kaitlin thaney
@kaythaney ; @mozillascience
xsede conference / july 22, 2013
(0)
doing good is part of our code
help researchers use the
power of the open web to
change science’s future.
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
(1)
gateways:
maximise scale
foster connectivity
minimise friction
our current systems are
designed to create
friction.
despite original intentions.
we’re locked in old mechanisms.
“... up to 70% of research from academic labs
cannot be reproduced, representing an enormous
waste of money and effort.”
- Elizabeth Iorns, Science Exchange
“There’s greater reward,
and more temptation to
bend the rules.”
- David Resnik, bioethicist
our definition of
“knowledge” is evolving.
our systems need to follow.
research cycle
idea
experiment
lit review
materials
publish
share results
retest
analyze
collect data
blocking points
idea
experiment
access
attaining
materials
publish
share results
retest
analyze
collect data
(to name a few ...)
types of information
hypothesis/query
protocols
parameters
content
non-digital “stuff”
articles
proceedings
negative results
analysis
code
datasets
models
(added complexity)
prof activities
mentorship
teaching activities
3 GB/year
9 GB/PhD
3 GB/year
30,000,000 GB/all*
9 GB/PhD
3 GB/year
* roughly
how much made available?
9 GB/PhD
3 GB/year
* roughly
30,000,000 GB/all*
Source: Michener, 2006 Ecoinformatics.
wasted ...
$$$
time
resource
opportunity
Source: Wolkovich et al. GCB 2012.
(2)
learn from open source
(culture as well as technology)
avoid reinventing
square wheels.
the best minds are usually
outside of your walls.
(3)
we need to build
capacity, not just
more nodes.
“Reliance on
ad-hoc, self-
education
about what’s
possible
doesn’t scale.”
instill best
(digital,
reproducible)
practice
“research hygiene”
license-like assessment
in an increasingly digital, data-
driven world, what core skills, tools
do the next-generation need?
(4)
we’re facing a
perception problem.
(but there’s hope.)
existing system is imperfect
we can/need to do better.
“Altmetrics” generally refers to tracking
online attention (esp. social media) data
to try and get an idea of the wider
impact of scholarly research.
?
changing models of
authority, community
rethink how we reward
“digital research”
idea
protocols
parameters
content
non-digital “stuff”
articles
proceedings
negative results
analysis
code
datasets
models
prof activities
mentorship
teaching activities
Source: Piwowar, et al. PLOS.
(5)
we’re battling inertia and
flawed assumptions.
at network scale, you have
(and should want)
serendipity ... by design.
help us make the web
work for science.
questions?
kaitlin@mozillafoundation.org
@kaythaney ; @mozillascience

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