Prof. Lorena Barba has just posted a reading list for reproducible research that includes ten key papers:

  1. Schwab, M., Karrenbach, N., Claerbout, J. (2000) Making scientific computations reproducible, Comp. Sci. Eng. 2(6):61–67, doi: 10.1109/5992.881708
  2. Donoho, D. et al. (2009), Reproducible research in computational harmonic analysis, Comp. Sci. Eng. 11(1):8–18, doi: 10.1109/MCSE.2009.15
  3. Reproducible Research, by the Yale Law School Roundtable on Data and Code Sharing, Comp. Sci. Eng. 12(5): 8–13 (Sept.-Oct. 2010), doi:10.1109/mcse.2010.113
  4. Peng, R. D. (2011), Reproducible research in computational science, Science 334(6060): 1226–1227, doi: 10.1126/science.1213847
  5. Diethelm, Kai (2012) The limits of reproducibility in numerical simulation, Comp. Sci. Eng. 14(1): 64–72, doi: 10.1109/MCSE.2011.21
  6. Setting the default to reproducible (2013), ICERM report of the Workshop on Reproducibility in Computational and Experimental Mathematics (Providence, Dec. 10–14, 2012), Stodden et al. (eds.), // report PDF
  7. Sandve, G. K. et al. (2013), Ten simple rules for reproducible computational research, PLOS Comp. Bio. (editorial), Vol. 9(10):1–4, doi: 10.1371/journal.pcbi.1003285
  8. Leek, J. and Peng, R (2015), Opinion: Reproducible research can still be wrong: Adopting a prevention approach, PNAS 112(6):1645–1646, doi: 10.1073/pnas.1421412111
  9. M. Liberman, “Replicability vs. reproducibility — or is it the other way around?,” Oct. 2015,
  10. Goodman, S. N., Fanelli, D., & Ioannidis, J. P. (2016). What does research reproducibility mean? Science Translational Medicine 8(341), 341ps12–341ps12, doi: 10.1126/scitranslmed.aaf5027

The papers themselves are great, but what really adds value is the way they're ordered, analyzed, and connected. If you're trying to make sense of all this, or trying to help others do so, it's a great place to start.

This post originally appeared in the Software Carpentry blog.