Creating research that is reproducible -- empirically, statistically, and computationally -- is challenging, and doing so is increasingly a condition for publishing in journals. Fortunately, modern tools make the process significantly easier than it was even five years ago. Join us on January 30th for a talk by Daniel Evanko of American Association for Cancer Research and Seth Green of Code Ocean on “Preparing your manuscript, code, and data for publication.”
Dr. Evanko will present from the publisher’s side, drawing on his experience working in scientific publishing since 2004, when he left the lab bench and joined Nature Methods as an editor before the journal published its first issue. He will discuss empirical/methodological reproducibility, the nuts and bolts of describing your work in sufficient detail that another researcher can clearly interpret and, ideally, replicate it.
Seth will present some techniques for preparing code for reproducibility, a criterion that is specifically assessed by certain journals and is likely to become increasingly common over the next few years. He will demonstrate these techniques through the use of Code Ocean, an online computational reproducibility platform, but the ideas will generalize across platforms and languages. The desired end-goal is research that is computationally reproducible with a single click.
Food will be provided.
As Developer Advocate, Seth is the liaison between scientists (Code Ocean’s developers) and the product/team; he helps authors get their code up and running on the platform and also tries to represent their interests in internal discussions. He did undergrad at Swarthmore and a few years of a Ph.D. program at Columbia, which he left with a masters degree in 2015.