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Reproducible science: the good, the bad, the ug...

Tania Allard
September 13, 2019

Reproducible science: the good, the bad, the ugly and the untold

Tania Allard

September 13, 2019
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  1. Tania Allard, PhD [she/her] @ixek Developer Advocate at Microsoft Reproducible

    science: the good, the bad, the ugly and the untold PyCon UK 2019 bit.ly/PyConUK-reproducibility
  2. 2 A bit about me Alan Turing Institute Industrial Fellow

    I am a recovering researcher Ex RSE – UK RSE Society Trustee JOSS editor @ixek
  3. 4 I spend a lot of time helping researchers to

    make research reproducible and open @ixek
  4. 5 I spend a lot of time helping data scientist

    to make machine learning reproducible and transparent @ixek
  5. 18 Software Sustainability Institute Survey – do researchers use software?

    @ixek https://slides.com/simonhettrick/why-recognising-scientific-software-experts-is-key-to-open-science#/2/1
  6. 24 @ixek q First M87 Event Horizon Telescope Results. III.

    Data Processing and Calibration q A series of 6 papers published in April 2019 q Incredible long term international collaboration (200+ scientists, 60 institutes, 18 countries, 6 continents) https://doi: 10.3847/2041-8213/ab0c57
  7. 30 What we say we want from research: - Innovation

    - Openness - Collaborations @ixek
  8. 37 An article about computational science in a scientific publication

    is not the scholarship itself, it is merely advertising of the scholarship. The actual scholarship is the complete software development environment and the complete set of instructions which generated the figures Buckheit and Donoho (paraphrasing John Claerbout) Wavelab and Reproducible Research 1995 @ixek
  9. 52 Why reproducibility matters @ixek Protects against bad actors Helps

    with correctness Helps ensure robustness Makes it easier to collaborate
  10. 53 Why reproducibility matters @ixek Leads to progress Enables strong

    baselines Is necessary for extensibility Makes you trustworthy
  11. 76 @ixek Ø Citations are academic currency (whether they should

    be or not!) Ø They’re the best way we have to endorse good work. Ø We should be citing the software we use.
  12. 79 How can we change research? Open tools and infrastructure-

    to make the last mile shorter Checklists, processes- no excuse that they did not know RSEs – no need to do it all alone Community - to advocate for change @ixek
  13. 81 Credits and special thank yous @ixek • Chris Holdgraf

    and all of the Jupyter community https://speakerdeck.com/choldgraf/open-infrastructure-in-the-cloud-with- jupyterhub • Kirstie Whitaker and the Turing Way community https://doi.org/10.5281/zenodo.3238189 • Simon Hettrick and the RSE community & Society https://slides.com/simonhettrick/why-recognising-scientific-software- experts-is-key-to-open-science