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# Rule 1. Love your data, and help others love it too.  Data management is a repeat-play game. If you take care to make your data easily available to others, others are more likely to do the same--eventually. While we wait for this new sharing-equilibrium to be reached, you can take two important actions. First, cherish, document, and **publish your data**, using the robust methods described in Rule 2. Better tools and resources for data management are becoming available, and universities and research communities are investing in data repositories (Rule 8) and more librarians and scientists are learning data management skills (Rule 10). At the very least, loving your own data available will serve _you_: you'll be able to find and reuse your own data if you treat them well. Second, enable and **encourage others to cherish, document, and publish their data**. If you are a research scientist, chances are that not only are you an author, but also a reviewer for a specialized journal or conference venue. As a reviewer, **request that the authors of papers you review provide documentation and access to their data** according to the rules set out in the remainder of this article. While Institutional approaches are also clearly  needed (Rules 8 and 10), changing minds one scientist at a time is essential as well.