On Reproducibility

I just got back from a fascinating one-day workshop on “Data and Code Sharing in Computational Sciences” that was organized by Victoria Stodden of the Yale Internet Society Project. The workshop had a wide-ranging collection of contributors including representatives of the computational and data-driven science communities (everything from Astronomy, and Applied Math to Theoretical Chemistry and Bioinformatics), intellectual property lawyers, the publishing industry (Nature Publishing Group and Seed Media, but no society journals), foundations, funding agencies, and the open access community. The general recommendations of the workshop are going to be closely aligned with open science suggestions, as any meaningful definition of reproducibility requires public access to the code and data.

There were some fascinating debates at the workshop on foundational issues; What does reproducibility mean? How stringent of a reproducibility test should be required of scientific work? Reproducible by whom? Should resolution of reproducibility problems be required for publication? What are good roles for journals and funding agencies in encouraging reproducible research? Can we agree on a set of reproducible science guidelines which we can encourage our colleagues and scientific communities to take up?

Each of the attendees was asked to prepare a thought piece on the subject, and I’ll be breaking mine down into a couple of single-topic posts in the next few days / weeks.

The topics are roughly:

  • Being Scientific: Fasifiability, Verifiability, Empirical Tests, and Reproducibility
  • Barriers to Computational Reproducibility
  • Data vs. Code vs. Papers (they aren’t the same)
  • Simple ideas to increase openness and reproducibility

Before I jump in with the first piece, I thought it would be helpful to jot down a minimal idea about science that most of us can agree on, which is “Scientific theories should be universal”. That is, multiple independent scientists should be able to subject these theories to similar tests in different locations, on different equipment, and at different times and get similar answers. Reproducibility of scientific observations is therefore going to be required for scientific universality. Once we agree on this, we can start to figure out what reproducibility really means.

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)
Be Sociable, Share!
This entry was posted in Conferences, Open Data, open science, Policy, Science. Bookmark the permalink.

3 Responses to On Reproducibility

  1. Pingback: Tweets that mention The OpenScience Project » On Reproducibility -- Topsy.com

  2. Greg says:

    The link you provided for the “thought piece” explanation (http://yaleisp.org/wiki/index.php?title=Thought_pieces) requires viewers to log in. Is this on purpose?

  3. Dan Gezelter says:

    I forgot they had password protected the workshop wiki. You can read my position paper here.


Leave a Reply

Your email address will not be published. Required fields are marked *