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Content Type

Accolades

Recipient’s name

Angela Henneberger, Bess Rose, Terry Shaw, and Michael Woolley

Publication date

May 19, 2026

Author / contact

Name: Angela Henneberger
Email: ahenneberger@ssw.umaryland.edu

Image

Alt text: Angela Henneberger, Bess Rose, Terry Shaw, and Michael Woolley

Blurb

MLDS Researchers Publish Manuscript Evaluating Synthetic Versions of the MLDS Data.

Main content

A team led by Dr. Michael Woolley and including Dr. Angela Henneberger, Dr. Bess Rose, Dr. Terry Shaw, and collaborators at the University of Maryland, College Park, published “Balancing Privacy and Utility in Synthetic Data: Insights from Maryland’s State Longitudinal Data System.”

This paper details the approach taken to evaluate the synthesis of Maryland’s State Longitudinal Data System (SLDS) using fully synthetic Classification and Regression Tree (CART) models. Results demonstrated low disclosure risk (near-zero) and high research utility, validated through robust evaluations. Practical insights and best practices from this case provide valuable lessons for other organizations seeking balanced synthetic data solutions for administrative data.

This manuscript is in press at the Journal of Data Protection and Privacy. 

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