International Integrated Microdata Series

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

This research project will enrich and expand the Integrated Public Use Microdata Series (IPUMS). IPUMS is the world's largest population database, with information describing over 2.5 billion individuals drawn from censuses and surveys of 157 countries. To meet the challenges created by rapid demographic, economic, and environmental change, researchers must have full and open access to the best possible information. This project will expand the geographic and chronological coverage of the database, preserve it for future generations, and make the data available to users around the world. IPUMS data already have stimulated new research that transcends national boundaries and static interpretation. The data are broadly used by national and international agencies to inform policy. This project will enhance scientific understanding of critical policy-related issues such as population aging, international migration, and the effects of government programs on economic development and well-being. The project will promote teaching, training, and learning through three mechanisms. IPUMS will provide online data analysis and promote the sharing of curricular materials. Training workshops will be conducted, and the research team will further develop online training modules on how to use the data. The project will continue to employ a diverse group of graduate and undergraduate research assistants, including members of underrepresented groups, who will develop valuable skills in an interdisciplinary environment. This research project will conduct five major activities. First, the research team will obtain and preserve data from international censuses and household surveys, focusing on data from the most recent round of censuses. Second, the research team will clean and process the data, drawing samples, correcting errors, applying confidentiality edits, and coding the data consistently across countries. Third, the investigators will develop comprehensive documentation to guide users on the meaning of census and survey responses and their comparability across time and space. Fourth, the research team will improve geographic identifiers in the data to allow detailed spatial analysis and improved interoperability across IPUMS data collections. Fifth, the project provides education and dissemination activities designed to strengthen relationships with both the research community and with partner statistical agencies and uses machine learning to produce machine-understandable metadata for dissemination to the research community. These activities will multiply the quality, quantity, accessibility, and interoperability of information about the changing human population, creating a transnational resource of unprecedented power for understanding human society on a global scale. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.