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Revive the core principles of science

Revive the core principles of science

Openness and transparency are core principles ofscience but are violated at several points in the research process. Here are diferent examples what is wrong and how we can fix it.

Konrad Förstner

July 14, 2014
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  1. Revive the core principles of science
    Konrad U. F¨
    orstner
    Core Unit Systems Medicine, Universit¨
    at W¨
    urzburg
    July 14th, 2014, MPI-CBG Dresden
    The opinions expressed here represent my own and not those of my employer.

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  2. Why Open Science?
    ”It’s a tragedy we had to add the word
    open to science.”
    Eduardo Robles
    https://twitter.com/edulix/status/219390289519968256
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  3. Why Open Science?
    Openness and transparency are core principles of
    science but are violated at several points in the
    research process.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  4. Examples for low reproducibility
    Study performed at Bayer prior to launching a
    drug development program - 20–25% of
    published data reproducible (Nat. Rev. Drug
    Discov. 10, 712, 2011)
    Similar approach performed at Amgen -
    reproducibility rate of 11% (Nature 483,
    531–533, 2012)
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  5. Research workflow – spot the error
    Scientists (publicly funded) generate knowledge
    Scientists transfer the copyright of the resulting
    manuscript* to commercial publishers for free in
    exchange for free** publication.
    Library (publicly funded) buys*** the journal
    subscription from publisher while the broad
    public has no access.
    * After peer review performed by other publicly funded scientists
    ** Oh, colored/extra pages!?! Well, then we need to charge a small fee!
    *** Often in bundles of journals and after signing a NDA about the prices negotiations
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  6. In 2013 Elsevier had a profit margin of 39%!
    http://poeticeconomics.blogspot.de/2014/03/elsevier-stm-publishing-profits-rise-to.html
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  7. My very personal opinion
    The subscription-based publication system is
    obsolete, over-prized and hampering the exchange
    of knowledge.
    It is obscene and embarrassing that this a core
    instrument of the scientific community.
    https://secure.flickr.com/photos/[email protected]/2514147406 – CC-BY by flickr user Malinki

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  8. Open Access journals
    Luckily there is a growing number of open-access
    journals and pressure by funding bodies.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  9. Still, the concept of the immutable publications,
    publisher and journals should reconsidered.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  10. From publisher to open repositories
    The Episciences Project aims to create
    community-run, open-access journals based on open
    repositories like arXiv.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  11. Writing scientific article in Wikis / version control systems
    Constant, real-time update of ”articles”
    Contributions are trackable
    Avoiding of redundancy (”Background” etc.)
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  12. Open Peer-Review
    Making the reviewing process transparent.
    source: The Library of Congress

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  13. Post Publication Peer-Review
    Publish first – then review.
    E.g. done by F1000 Research
    source: The Library of Congress

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  14. Open (Research) Data
    Making all experimental and derived data accessible.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  15. Open (Research) Data
    Currently: A selected subset of the experimental
    data of a project becomes part of the
    publication.
    Needed: The full data set becomes public with
    the manuscript.
    Optimum: Data is immediately after generation
    public.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  16. Feeling uncomfortable now?
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  17. Sharing the data immediately would be the best for
    science.
    In the current system this is not necessarily the best
    for the scientists.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  18. Aligning the interests
    Scientist compete for limited resources and try to
    adapt optimally to the given evaluation/funding
    system.
    Due to this we have to generate a system which
    promotes openness and has incentives to share
    results.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  19. New measurements of scientific impact are required
    Not only measure ”papers” but also shared
    data, manuscript review, comments etc.
    ORCID compiles different typs of ”works”
    Alternative metrics - beyond impact factors,
    h-index (etc.)
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  20. Besides these technical approaches we have to
    change our research culture.
    This is hard and one of the major challenges.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  21. Now it gets even more uncomfortable.
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  22. Have you every asked yourself if you are really
    needed in your lab?
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  23. Automation of science
    Use formalization of experimental protocols and
    open standards to implement automated research.
    http://www.flickr.com/photos/tallkev/256810217/ – CC-BY by flickr user tallkev

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  24. Automation of science
    Program your experiments and share the code.
    http://www.flickr.com/photos/tallkev/256810217/ – CC-BY by flickr user tallkev

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  25. Automation of science
    Optimal reproducibility and transparency.
    http://www.flickr.com/photos/tallkev/256810217/ – CC-BY by flickr user tallkev

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  26. Formal language – EXACT
    http://www.flickr.com/photos/tallkev/256810217/ – CC-BY by flickr user tallkev

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  27. Robot scientist ADAM
    http://www.flickr.com/photos/tallkev/256810217/ – CC-BY by flickr user tallkev

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  28. Microfluid systems as one path
    https://secure.flickr.com/photos/schlaus/708447474 – CC-BY by flickr user schlaus

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  29. Current challenges
    Price (as long as not coming a commondity)
    Lack of flexibility
    Formalization is hard
    Vendor lock-in ⇒ open standards required
    http://www.flickr.com/photos/tallkev/256810217/ – CC-BY by flickr user tallkev

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  30. Summary
    Openness and transparency are core principle of
    science
    We are not using the full potential of available
    technologies to implement openness in our
    research workflow
    We need a culture of openness and incentives to
    open up science
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  31. What can you do right now (easily)?
    Use/promote Open Acces journals
    Use/promote pre-print servers (arXiv, bioRxiv)
    Use/promote specialized data repositories as
    well as general-purpose repositories to publish
    you research data
    Think ”open”
    http://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle

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  32. http://www.flickr.com/photos/nateone/3768979925/ – CC-BY by flick user nateone

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