Data flows in enormous quantities from individuals to companies, as the use of basic products including search engines, social platforms, health products, entertainment services, and others is conditioned on the surrender of biographical, biometric, behavioral, and experiential data. The accumulation of individual data on such a large scale has given rise to elaborate markets for individual data that generate immense value for firms and platforms but create a complex of risks for the individuals whose data these markets trade. This collaborative project between law and computer science aims to focus for the first time on the advent of parallel public data markets. Federal, state, and local governments, who have privileged access to intimate data at enormous scale and range about their constituents, have followed the template developed in the private sector and learned to expand, aggregate, and increase the value of their data stores by sharing and consolidating data across levels and institutions of government. These intergovernmental data markets are no less sizable or consequential than those established by private-sector firms; and they introduce risks to individuals not always present in private data sharing. This project aims to develop an integrated legal and technical understanding of how data flows between governments; to study the unique risks these data flows pose to individuals in areas ranging from privacy to discrimination to accuracy to power; and to develop and test tools to improve the fairness of intergovernmental data sharing that are alert to both legal and technical realities.