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kaitlin thaney
SciPy, 13 july 2011 austin, texas
the reality of ‘digital science’
Wednesday, 13 July 2011
- xi. background
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the reality of digital science kaitlin thaney SciPy, 13 july 2011 - - PowerPoint PPT Presentation
the reality of digital science kaitlin thaney SciPy, 13 july 2011 - - PowerPoint PPT Presentation
the reality of digital science kaitlin thaney SciPy, 13 july 2011 austin, texas Wednesday, 13 July 2011 xi. background Wednesday, 13 July 2011 about me Wednesday, 13 July 2011 Digital Science (the company) Wednesday, 13 July 2011
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about me
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Digital Science (the company)
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investment arm incubator role in-house dev
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tiered approach build to scale researcher-focused
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- 1. science, tech, and
moving online
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research
idea experiment lit review discovery materials publish share results
retest
analyze collect data
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blocking points
idea experiment lit review discovery materials publish share results
retest
analyze collect data (to name a few ... )
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access analysis dissemination
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text text
text
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discovery & delivery
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changes at the workbench
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annotation & curation
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social & administrative
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gaps still exist
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- 2. key constituencies
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(3)
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machines researchers decision makers
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machines researchers decision makers
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... annotation markup search discovery “behind the scenes” ...
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[brief interlude]
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digitisation of the scholarly canon
(content is still king)
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not nearly there yet ...
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barriers to “access”
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still the starting point
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patents are no better
(in many cases, worse)
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can streamline
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name disambiguation
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10,11-dihydro-5-methyl-5H-dibenzo[b,e][1,4]diazepin-11-one
(still strains the minds of the best)
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machine readability is key.
agreement is hard.
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10,11-dihydro-5-methyl-5H-dibenzo[b,e][1,4]diazepin-11-one
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“everything is metadata ... everything can be a label.”
- david weinberger
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machines researchers decision makers
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a few edge cases
(though no field is perfect)
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CC-BY-2.0 - Plaxco Lab - http://www.flickr.com/photos/34857812@N04/
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tracking expiration calibration
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the non-digital
+
- rdering
processing
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protocols parameters calibration
- misc. lit
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managing information
different types of “data”
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- ften gigabytes,
not terabytes
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“i invented a folder based system ...”
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“i invented a folder based system ...” “yeah, we had a LIMS. it only ever got used to store photos from lab nights out.”
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why? experimentation reliance data moves, grows legs funder/instit’n pressure
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machines researchers decision makers
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rewards, incentives the “ why ”
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data capture (of a different sort)
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the “social issue”
best practices behaviour roadblocks discipline / researcher specific
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paper’s still the currency
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imperfect system
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“Right now we're going through a Cambrian explosion of metrics.”
- Johan Bollen
Nature 465, 864-866 (2010) | doi:10.1038/465864a
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there’s been a drastic spike in terms of sheer volume and type
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citation / impact factor h - index weighted citations (eigenfactor, sjr) “betweenness centrality” alt-metrics, etc.
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difficult to ...
harmonise track /maintain / map understand (even still measure)
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administrators / funders = part of the research cycle
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- 3. the reality
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“the future is here ... just not evenly distributed yet.”
- William Gibson
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changing understandings, paradigms
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technology can help design decisions are key plan for the irrational
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more efficient research increase productivity enable reproducibility
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thank you.
k.thaney@digital-science.com www.digital-science.com @kaythaney
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