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.

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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.
  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
  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
  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
  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
  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
  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 My very personal opinion The subscription-based publication system is obsolete,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/96302395@N00/2514147406 – CC-BY by flickr user Malinki
  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
  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
  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
  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
  12. Open Peer-Review Making the reviewing process transparent. source: The Library

    of Congress
  13. Post Publication Peer-Review Publish first – then review. E.g. done

    by F1000 Research source: The Library of Congress
  14. Open (Research) Data Making all experimental and derived data accessible.

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

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

    flickr user subcircle
  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
  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
  24. Automation of science Program your experiments and share the code.

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

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

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

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

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