A request for applications with set aside is proposed, entitled “Data Sharing for Demographic Research (DSDR)” using the U24 NIH Resource-Related Research Project - Cooperative Agreement grant mechanism. This will be an open competition to encourage innovation and cost-effectiveness. The current award (U24HD048404) to the University of Michigan includes a consortium of several institutions with expertise and experience in data sharing and harmonization. To date, 35 projects have been archived and disseminated, there have been approximately 5,000 downloads of archived data sets, and the data have been used by approximately 10,000 unique users.
- Support archiving, documentation, and dissemination of demographic and other population science data.
- Improve the integration of data collected at several levels (for example, individual, family, neighborhood, school district, county, and state) and through multiple modalities, such as survey data and geographic information systems (GIS) data such as satellite images.
- Increase the impact of NICHD-funded research projects by expanding the use of data collected through NICHD grants to research teams outside the original grantees.
- Improve access to high-quality data to young investigators and scientists at smaller, less research oriented institutions.
- On a limited basis, support the archiving, documentation, and dissemination of other data sets collected with support from NICHD.
- Work with NICHD staff to support the archiving, documentation, and dissemination of data sets collected with support from NICHD and to identify other population science data to archiving, document, and disseminate on a limited basis.
- Maintain access to existing DSDR data sets.
- Develop protocols and technologies for data sharing, including use of restricted data, that promote cost-efficiency, wide-spread dissemination of population data while ensuring protection of human subjects.
- Develop and disseminate best practices in data sharing to population scientists and scientists in other disciplines.
- Develop methods of integrating data collected at several levels and through multiple modalities, such as survey data and GIS data.
- Develop methods and best practices for integrating and data from studies that include both data that can be stored in electronic format and biomarkers.
- Improve human subjects protections, especially privacy protection, by shifting data archiving and dissemination to scientists who are experts at these tasks.
- Promote the development of cutting-edge cost-efficient procedures and technologies for data sharing.
- Disseminate best practices in data sharing to population scientists and scientists in other disciplines.
- Reduce the costs of using restricted data, both financially and in terms of researchers' time, while ensuring high level human subjects protection.
Regina M. Bures, PhD
Population Dynamics Branch
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