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What academia can learn from open source
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Arfon Smith
October 22, 2014
Science
1
190
What academia can learn from open source
My slides from All Things Open -
http://allthingsopen.org/
Arfon Smith
October 22, 2014
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Transcript
What Academia Can Learn from Open Source Creative Commons Attribution
3.0 Unported License Arfon Smith
[email protected]
@arfon "
!
What is a GitHub?
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A story from my life (10 years ago)
Astronomer
tl;dr - technical, but brimming with inefficiencies
http://www.flickr.com/photos/blachswan
http://www.flickr.com/photos/esoastronomy/
http://www.flickr.com/photos/esoastronomy/ http://www.flickr.com/photos/jamiegilbert
http://amandabauer.blogspot.com/
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Diffraction grating Telescope Detector
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130 130 1 2048 189 189 258 258 480 562
378 378 493 521 390 397 851 851 247 274 319 319 304 580 493 511 610 636 188 188 228 228 > cat bad_pix_mask.txt
Wasteful
Wasteful 2 days work
Wasteful 2 days work 3 observing runs/week
Wasteful 2 days work 3 observing runs/week 52 weeks in
year
Wasteful 2 days work 3 observing runs/week 52 weeks in
year 15 year detector lifetime
Wasteful 2 days work 3 observing runs/week 52 weeks in
year 15 year detector lifetime 2*3*52*15 = 4680 days (13 years)
Wasteful… but the norm 2 days work 3 observing runs/week
52 weeks in year 15 year detector lifetime 2*3*52*15 = 4680 days (13 years)
A second story from my life (2 months ago)
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Software composed of many components
Your software is the thing that is different
Open Source: Ubiquitous culture of reuse
Why isn’t academia like this?
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http://dx.doi.org/ 10.1051/0004-6361
Careers are based on paper counts
Careers are based on paper citations
Three major problems
1. ’Novel’ results preferred
2. Reduced collaboration
3. The format sucks
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Explain what you did
So that others can repeat
Everybody learns
It’s the way that we explain that matters most
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State of the art technology
State of the art technology… for the late 17th century*
* Michael Nielsen
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Data, methods, prose
http://www.nature.com/news/2011/111005/full/478026a.html
BIG SCIENCE
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Complex stuff Numbers, data Science!
Reproducibility Data intensive
Verification may take years (if at all)
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What do open source collaborations do well?
Open source collaborations Open Source vs Open Collaborations
Open source collaborations Open Source: the right to modify, not
the right to contribute.
Open source collaborations Open Collaborations: a highly collaborative development process
and are receptive to contributions of code, documentation, discussion, etc from anyone who shows competent interest.
Open source collaborations Open Collaborations: a highly collaborative development process
and are receptive to contributions of code, documentation, discussion, etc from anyone who shows competent interest. THIS
Ubiquitous culture of reuse
Expose their collaborative process
How do 4000 people work together?
The pull request
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discuss improve Code first, permission later
Every time this happens the community learns
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Merged pull requests
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“open source is… reproducible by necessity” Fernando Perez http://blog.fperez.org/2013/11/an-ambitious-experiment-in-data-science.html
Better at collaborating because they have to be
(doesn’t have to mean this) Open Public? =
‘Open Source’ way of working
Open (within your team, department or institution)
Electronic & Available
Asynchronous, exposed process
Lock-free
Low friction collaboration
Academia can learn from open source
Academia must learn from open source
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What’s happening in academia today?
Collaboration around code
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Collaborative authoring
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Collaborative teaching
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Where might more significant change happen?
Where do communities form?
Around a shared challenge?
Around shared data?
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10 ? n Level 1 (continual) Level 2 (periodic)
Supernovae Weak lensing Active Galactic Nuclei Solar System Galaxies Transients/variable
stars Large-scale structure Stars, Milky Way Strong lensing Informatics and Statistics Dark Energy (DESC)
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Software composed of many components
Your software should be the thing that is different
science too! Your software should be the thing that is
different
Scientific data is becoming more open
http://www.nature.com/news/2011/111005/full/478026a.html
How do we make this behaviour the norm?
Credit
“Academic environments of today do not reward tool builders” Ed
Lazowska, OSTP event http://lazowska.cs.washington.edu/MS/MS.OSTP.pdf
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“publishing a paper about code is basically just advertising” David
Donoho http://www.stanford.edu/~vcs/Video.html
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How to derive meaningful metrics from open contributions?
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Trust
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Discoverability
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Barriers are cultural, not technical
Why should we care?
Because we paid for it?
Because open=good?
Because care about the creation of knowledge?
Open source has solved much of what academia needs
Our challenge is to adapt and evolve the academy in
this new collaborative age
Thanks
[email protected]
@arfon "