*New* Small Grants for Secondary Analyses of Existing Data Sets and Stored Biospecimens

New Small Grants for Secondary Analyses of Existing Data Sets and Stored Biospecimens

Posted: 3/23/2021 (Funding)

The NICHD is sponsoring grant applications for secondary analyses of data that had previously been supported by NICHD for the data collection phase. Examples of NICHD datasets and research resources include: the NICHD Data and Specimen Hub (DASH), Data Sharing for Demographic Research (DSDR), the Child Language Development Exchange (CHILDES), the Mouse Genome Informatics (MGI), and Xenbase. Often, research studies supported by NICHD and other scientific funders often produce data and/or specimens with utility beyond the hypotheses and questions the original research projects were designed to address. The CSDE team is always happy to help at all stages of the grant development and submission process. Contact Scott Kelly, Sara Curran, Steve Goodreau, or Belinda Sachs with any questions. The call can be found here.

The types of data available for analysis by researchers outside the original research team include data from clinical trials, panel studies and other longitudinal research, cross-sectional studies, observational studies, multi-method studies, and other types of basic biomedical, clinical, behavioral, demographic, and epidemiological research. Secondary use of existing data offers a cost-effective way to foster research within the scientific mission of the NICHD. Supporting secondary data analysis also lowers costs to researchers, especially researchers early in their careers and/or at resource-limited institutions, by decreasing the time and funds required to engage in research. In the past, limited data availability and poor documentation of available data were major barriers to secondary analysis of data and biospecimens. Ongoing NIH and NICHD support for data sharing, expanding NIH data and resource sharing requirements, and the development of standards for data documentation and metadata are all factors that have increased the amount and quality of data available for secondary analysis has increased.