NeuRA Ahead of the Open Science Curve

I had great fun yesterday visiting NeuRA (Neuroscience Research Australia), a large research institute in Sydney. I was hosted by Simon Gandevia, Deputy Director, who has been a long-time proponent of Open Science and The New Statistics.

Neura’s Research Quality page describes the quality goals they have adopted, at the initiative of Simon and the Reproducibility & Quality Sub-Committee, which he leads. Not only goals, but strategies to bring their research colleagues on board–and to improve the reproducibility of NeuRA’s output. My day started with a discussion with this group. They described a whole range of projects they are working on to strengthen research at NeuRA–and to assess how quality is (they hope!) increasing.

For example, Martin Heroux described the Quality Output Checklist and Content Assessment (QuOCCA) tool that they have developed, and are now applying to recent past research publications from NeuRA. In coming years they plan to assess future publications similarly–so they can document the rapid improvement!

I should mention that Martin and Joanna Diong run a wonderful blog, titled Scientifically Sound–Reproducible Research in the Digital Age.

It was clear that the R&Q folks, at least, were very familiar with Open Science issues. Would my talk be of sufficient interest for them? Its title was Improving the trustworthiness of neuroscience research (it should have been given by Bob!), and the slides are here. The quality of the questions and discussion reassured me that at least many of the folks in the audience were (a) on board, but also (b) very interested in the challenges of Open Science.

After lunch my ‘workshop’ was actually a lively roundtable discussion, in which I sometimes managed to explain a bit more about Significance Roulette (videos are here and here), demo a bit of Bob’s new esci in R, or join in brainstorming strategies for researchers determined to do better. My slides are here.

Yes, great fun for me, and NeuRA impresses as working hard to achieve reproducible research. Exactly what the world needs.


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