This talk will consider a paradigm where the public generally own and control their data. Here, mechanisms for purchasing data could create huge economic value (and share it fairly). But putting this into practice requires assigning value to data and efficiently matching the mechanism to providers. I will outline some research on this problem utilizing ideas from prediction markets, active learning, and differential privacy. We will see a few important directions for future work. I may also ramble briefly regarding software freedom, labor versus capital, etc.