Encouraging code sharing in neuroscience

Encouraging code sharing in neuroscience

Stephen J Eglen                  Cambridge Computational Biology Institute
https://sje30.github.io          University of Cambridge
sje30@cam.ac.uk                  @StephenEglen

Slides: http://bit.ly/fens-eglen

Acknowledgements

INCF, co-authors, Freeman lab.

These slides are available under a creative common CC-BY license.

Inverse problems are hard

Research sharing: the inverse problem

Moral or selfish approach?

Selfish reasons to share

Why not align what is good for science with what is good for scientists?

1. Funding mandates (REF + enforcement from Wellcome Trust)
2. Credit through data papers
3. Leads to further collaborations (e.g. “EPAmeadev”)
4. Fixes data bugs / errors in analysis
5. Prevent data loss (Vines et al 2014). e.g. students have a habit of leaving…
6. Your future self is probably one of the main beneficiaries of sharing.

Code sharing: a way forward

Specific recommendations

1. Include enough code to reproduce key figure/result from your paper (“modeldb”).
2. Provide toy examples if your project is too intensive to expect others to run in a few hours.
3. Version control
4. Licence
5. Provide data
6. Provide tests
7. Use standards
8. Use permanent URLs

Simple example

Docker

Can bundle entire open-source evironment for others to share:

(start docker)
docker run -d -p 8787:8787 sje30/eglen2015
open http://192.168.99.100:8787/

This should launch a web page …

Jupyter notebooks

• Embed code within manuscript; figures/tables dynamically regenerated

binder = Docker + jupyter + cloud compute

• mybinder.org developed and supported by Freeman lab, Janelia Farm.
• Allows jupyter notebooks to be dynamically evaluated (not just rendered) online.