Project Summary IPUMS is a family of nine integrated databases that comprise the largest and most intensively-used data resource for research on population dynamics and health. This competing continuation proposal has two main goals. First, the project will provide the primary support for expanding, improving, and maintaining IPUMS-USA, which consists of microdata from decennial censuses and American Community Surveys. Second, the project will provide central coordination across the nine IPUMS databases, exploiting synergies and eliminating redundant work. Over the past five years, IPUMS has seen explosive growth in the number of researchers using the database, the amount of data they request, and the number of high-impact publications they produce. At the same time, however, there is unprecedented demand from researchers for expansion, improvement, and support of the infrastructure. This project will undertake four major activities to meet this demand: 1. Database Expansion. We will add data from the American Community Survey and the 1950 census, update variables to accommodate new standards, and evaluate new Census Bureau disclosure controls. 2. IPUMS-FSRDC. We will make IPUMS data housed in the Federal Statistical Research Data Centers more usable through comprehensive documentation, streamlined access, and improvement of the restricted microdata, including new harmonized small-area identifiers. 3. Data Access Redesign. We will redesign the IPUMS user interface and provide new tools for variable discovery and data sharing, including a new user interface conforming to modern accessibility standards, simplified data sharing for replication and collaboration, and enhancement of our online data analysis tool. 4. IPUMS Coordination. The project will synchronize technological development, user support and outreach, and long-run planning for preservation and sustainability across the nine IPUMS databases to avoid duplication of effort, increase the impact, and reduce the cost of IPUMS data infrastructure. IPUMS reduces costs for the population and health research community by minimizing redundant effort, simplifying data access, increasing the replicability of studies, and improving data reliability. The availability of large-scale integrated microdata has opened extraordinary new opportunities for fine-grained contextual analyses of population dynamics and health, resulting in transformational research across a diverse range of topics and disciplines.