Making the web work for science - UND
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Making the web work for science - UND






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    Making the web work for science - UND Making the web work for science - UND Presentation Transcript

    • making the web work for science kaitlin thaney @kaythaney ; @mozillascience univ. of north dakota / 5 feb 2014
    • doing good is part of our code
    • help researchers use the power of the open web to change science’s future.
    • (0)
    • science is still (largely) rooted in 17th c. practices. (and not in that “retro is cool” sort of way.)
    • early forms of knowledge sharing
    • our current systems are designed to create friction. despite original intentions.
    • “ What Des-Cartes did was a good step. You have added much several ways, & especially in taking ye colours of thin plates into philosophical consideration. If I have seen further it is by standing on ye shoulders of Giants. “ - Isaac Newton, 1676
    • existing system is imperfect
    • data,
    • ability to reproduce experiments,
    • incentive to change,
    • “ 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)
    • “open science” - access to content, data, code, materials. - emergence of “web-native” tools. - rewards for openness, interop, collaboration, sharing. - push for ROI, reuse, recomputability, transparency.
    • research cycle idea publish lit review share results analyze materials retest collect data experiment
    • types of information (added complexity) articles proceedings hypothesis/query prof activities mentorship teaching activities negative results content non-digital “stuff” protocols parameters analysis code datasets models
    • blocking points (to name a few ...) idea access publish attaining materials share results analyze retest collect data experiment
    • “... up to 70% of research from academic labs cannot be reproduced, representing an enormous waste of money and effort.” - Elizabeth Iorns, Science Exchange
    • Source: Michener, 2006 Ecoinformatics.
    • (2)
    • is open enough? what does it mean to “operate on/like the web”?
    • code (interop) community (people) code/data literacy (means to learn/engage)
    • our systems need to talk to one another.
    • “One worry I have is that, with reviews like this, scientists will be even more discouraged from publishing their code [...] We need to get more code out there, not improve how it looks.”
    • code as a research object what’s needed to reuse ?
    • code as a research object
    • “There’s greater reward, and more temptation to bend the rules.” - David Resnik, bioethicist
    • (3)
    • we need to even (/ elevate) the playing field.
    • facing a digital skills gap
    • “Reliance on ad-hoc, selfeducation about what’s possible doesn’t scale.” - Selena Decklemann
    • learn from open source (culture as well as technology)
    • current activity: 129 instructors (60+, training) 109 bootcamps 3700+ learners
    • we need to build capacity, not just more nodes.
    • “research hygiene” instill best (digital, reproducible) practice
    • in an increasingly digital, datadriven world, what core skills, tools do the next-generation need?
    • education as a means of building community ... globally, as well as across disciplines.
    • (4)
    • shifting practice (and getting it to stick) is challenging. ... but not impossible.
    • disciplines as cultures
    • can we do the same for research on the web? 63 nations 10,000 scientists 50,000 participants
    • what are the necessary components? tools and technology cultural awareness, best practice connections, open dialogue skills training
    • (5)
    • operating in isolation doesn’t scale.
    • coordination and collaboration are key. design for interoperability. remember the non-technical challenges.
    • join us (and the conversation.) teach, contribute, learn.
    • questions? @kaythaney ; @mozillascience