Ten Simple Rules of Credible Practice/Mathematical and Computational Sciences Team

Top Ten Simple Rules Ranked:

  1. Use competition of multiple implementations to check and balance each other
  2. Document your code and make your code readable
  3. Explicitly identify experimental scenarios illustrating when, why, and how the model is false \ Explicitly list your limitations
  4. Make it easy for anyone to repeat and/or falsify your results \ Make sure your results are reproducible
  5. Use traceable data that can be traced back to the origin
  6. Use version control
  7. Define your evaluation metrics in advance
  8. Practice Verification / Validation / Uncertainty Quantification \ Attempt verification within context
  9. Define the use context for which the model is intended
  10. Develop with the end user in mind

Draft of Rules in Original Order + Score Before Ranking:

Here are the Raw Rules in original order with alternatives noted after \ according to our team (Score according to our discussion – based on responses by everyone in the forum who responded).

Notes:

The Rule Scoring and Ranking can be found in the forum at: https://simtk.org/forums/viewtopic.php?f=848&t=4333

This ranking is only for the Mathematical and Computational Sciences Team. The ranking for all committee teams can be found in the parent wiki in the following link: http://wiki.simtk.org/cpms/Ten_Simple_Rules_of_Credible_Practice

Ten Simple Rules of Credible Practice/Mathematical and Computational Sciences Team (last edited 2016-05-04 22:03:12 by localhost)