Last fall I participated in a really unique workshop at Yale put on by one of our Kauffman legal fellows, Victoria Stodden.  The purpose of the workshop was to discuss data and code sharing best practices and issues for creating replicable research.  While the workshop was a bit more in the computational science space than I am fully comfortable, I found the conversation incredible and the goals of the effort beyond compelling.  What has resulted is a Data and Code Sharing Declaration (just published in IEEE Computing in Science and Engineering).  This is a document that should be taken up for discussion at foundation and other funder events, in policy circles, and within the scientific academia as it lays out early and clear recommendations for actions each group can take to further data sharing and replication in the future.  It is a document which anyone who curates data, journal editors, and all scientists should be discussing.