Data Science continues to have a transformative impact on Science and Engineering, and on society at large, by enabling evidence-based decision making, reducing costs and errors, and improving objectivity. The techniques and technologies of data science also have enormous potential for harm if they reinforce inequity or leak private information. As a result, sensitive datasets in the public and private sector are restricted from research use, slowing progress in those areas that have the most to gain: human services in the public sector. Furthermore, the misuse of data science techniques and technologies will disproportionately harm underrepresented groups across race, gender, physical ability, sexual orientation, education, and more. These data equity issues are pervasive, and represent an existential risk for the use of data-driven methods in science and engineering. This project will establish a Framework for Integrative Data Equity Systems (FIDES): a National Institute for the study of systems that enable research on sensitive data while preventing misuse and misinterpretation.