Funds Awarded for "Expanding MLDS Data Access and Research Capacity with Synthetic Data Sets"

September 20, 2018

 

The Maryland Longitudinal Data System Center has awarded over $734,000 to the SSW for a project titled "Expanding MLDS Data Access and Research Capacity with Synthetic Data Sets Year 3."  Associate Professor Michael Woolley is the Principal Investigator.

 

The purpose of the project is to investigate creating synthetic versions of the data housed in the Maryland Longitudinal Data System (MLDS).  The project will first create gold standard (cleaned up and ready to analyze real data), then synthetic, versions of three longitudinal data sets: high school to workforce, high school to postsecondary education, and postsecondary education to workforce.

 

Synthetic data are data that statistically act like the real data, however, have been imputed based on models of the real data that capture the relationships between and among the variables and individuals in the data. Because synthetic data do not contain any actual data about actual individuals synthetic data can be released to scholars and policy analysts outside the small number of folks privileged to access the MLDS data without violating federal and state confidentiality laws which restrict sharing such administrative data. Therefore, synthetic data can greatly expand the potential knowledge gained, and policy and programming lessons learned, from those data.

 

The potential impact includes state longitudinal data systems across the country adopting this strategy to greatly expand the number of education, workforce, and policy scholars who will be able to access and therefore analyze synthetic versions of state longitudinal data to inform policy and programming. That would greatly leverage the benefits of such state administrative data given the large budgetary expenditures at both the state and federal levels to build and maintain such data systems.

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2017 University of Maryland School of Social Work

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