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Computing & Data: From academia to open source

Fernando Perez
February 26, 2013

Computing & Data: From academia to open source

Slides for a lightning talk for the UC Berkeley workshop "Supporting Data Science - A Campus-Wide Workshop": http://vcresearch.berkeley.edu/datascience/workshop

Fernando Perez

February 26, 2013

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  1. Computing & Data
    From academia to open source
    Fernando Pérez
    http://fperez.org, @fperez_org
    [email protected]
    Henry H. Wheeler Jr. Brain Imaging Center, UC Berkeley
    Supporting Data Science
    Feb 23, 2013

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  2. Computing and data
    Now part of the DNA of science
    Much more than “the third/fourth branch” of science
    Computing and data are everybody’s problem...
    Therefore they are nobody’s problem

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  3. An educational problem:
    the computer as a research tool
    All scientists need to own their computational processes.
    This means literacy in statistics, linear algebra, algorithms,...
    But also in ’software carpentry’ skills:
    version control, software design, testing, documentation, ...
    NOT yet another department on campus (ask Dave Culler)...

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  4. Open Source:
    skills, tools and practices we need!
    The culture where these things get done.
    Wildly collaborative
    Reproducible by necessity
    Version control, testing, documentation, public peer review, etc.

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  5. Reward Structure in academia:
    we punish all of the above
    Departmental boundaries: interdisciplinary work is a great buzzword,
    not such a great career path.
    Computational heritage is built on code, not on citations of prior
    Continuous evolution vs publication milestones
    Authorship in collaborative works vs the first-author paper.
    Scholarship and intellectual effort embedded in the code.

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