This grant funds a project led by Brian Granger to expand and enhance Jupyter Notebooks—a powerful, popular, and open-source scientific computing platform—to enhance its handling of private, proprietary, or otherwise sensitive data. Planned features to be developed and implemented include a nuanced permissions structure that can be used to ensure that only properly credentialed individuals can see or manipulate data, stronger event logging and internal telemetry, and encryption of data both at rest and in transit. To test the software, Granger will work closely with a wide variety of data holders including a U.S. company dealing with health data; a German warehouse for financial data; and NYU’s Center for Urban Science and Progress (CUSP), which collect all kinds of municipal data. Grant funds support software development along with a host of dissemination activities that will promote and test Jupyter’s expanded capabilities among researchers dealing with sensitive data.