Over the past few months, I became increasingly aware that I wasn’t be as open with my research as I could be. Sure, all my articles are openly available, including preprints of some of my work. But I also advocate for sharing code and data, and until now, I hadn’t done either. That changes today.

Want my data? You can have it. Want my code? You can have that, too. Want step-by-step instructions on how to analyze my data and reproduce the tables and figures in my manuscripts? You got it.

I’ve set up a github repository (my first ever!), which includes all the data and code associated with my latest preprint. I’ll be updating that preprint with a new version soon. But in the meantime, I would love to get feedback on the repository contents and especially the ipython notebook (also my first!) detailing how to view the electrophysiological recordings provided and how to analyze the bursting data extracted from those recordings.

When I have more time, I hope to blog about all that went into obtaining these data and creating the repository. Since this is the first time I’ve done this, I learned a lot about how to make my data and code more reusable, and even optimized my code in the process. (Special thanks go to Ross Mounce for his great advice on best practices to follow for sharing data, and to Marco Herrera Valdez for excellent feedback on an earlier version of the notebook.) Issues surrounding data preparation aren’t trivial, and I think we have to consider the time and skill investment involved if we want to see more widespread adoption of data sharing. More on that soon…

For now, please download the data. Play around with it. Tell me what you think. I see tools like github and ipython notebooks as hugely powerful and an essential part of opening up the scientific process. And I’m very excited to be taking these next steps in opening up own work.

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