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    Gateways for Open Science - XSEDE Gateways for Open Science - XSEDE Presentation Transcript

    • 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