Funds from this grant support work by a team, led by David Cousins at a company called Duality, to develop mathematical tools and techniques that will enable social scientists and other researchers to link and analyze privacy-sensitive financial data without the risk of exposing protected information in the data. Partnering with the Institute for Research on Innovation and Science (IRIS), which collects administrative records from universities with the expectation that no sensitive information about one institutionХs employees, students, or finances will be revealed to any another, Cousins and the Duality team will work on the development of methods that use a type of advanced cryptography known as fully homomorphic encryption (FHE) to develop analysis tools that are powerful and scalable enough to be used in a wide variety of research contexts, yet satisfy very stringent data privacy standards. All developed software and code will be open source and deposited in freely accessible software libraries.