- Love your data, and help others love it too.
- Share your data online, with a permanent identifier.
- Conduct science with a particular level of reuse in mind.
- Publish workflow as context.
- Link your data to your publications as often as possible.
- Publish your code (even the small bits).
- Say how you want to get credit.
- Foster and use data repositories.
- Reward colleagues who share their data properly.
- Be a booster for data science.
— Source (with more details for each of the rules): https://www.authorea.com/users/3/articles/3410/ (Or: http://dx.doi.org/10.1371/journal.pcbi.1003542)