  The U.S. Census Bureau collects and publishes detailed demographic data about
Americans which are heavily used by researchers and policymakers. The Bureau
has recently adopted the framework of differential privacy in an effort to
improve confidentiality of individual census responses. A key output of this
privacy protection system is the Noisy Measurement File (NMF), which is
produced by adding random noise to tabulated statistics. The NMF is critical to
understanding any errors introduced in the data, and performing valid
statistical inference on published census data. Unfortunately, the current
release format of the NMF is difficult to access and work with. We describe the
process we use to transform the NMF into a usable format, and provide
recommendations to the Bureau for how to release future versions of the NMF.
These changes are essential for ensuring transparency of privacy measures and
reproducibility of scientific research built on census data.
