Program Purpose and Introduction

The most interesting research problems happen in cycles. First there is the idea, then engineering to implement the idea on a real-world use case, followed by engagement with real-world experts, and then that feedback is what spurs us to look more carefully at the problem and realize its true complexity. Each iteration of this collaborative research cycle leads to more valuable and foundational research.

The NIST Differential Privacy Challenge Series saw huge gains in synthetic data generation performance and the publication of a variety of open source tools. Yet, realistic evaluation and benchmarking for deidentified data (synthetic and other techniques) remains difficult. NIST seeks to assist the research community by releasing new data and evaluation tools, drawn from real-world expertise, designed to more deeply understand data deidentification techniques and their behavior on diverse, real-world data.

The Diverse Communities Data Excerpts are real-world, limited-feature data (24 columns), drawn from the American Community Survey and divided into three distinct geographic partitions. The complimentary SDNist Deidentified Data Report Generator provides a suite of both machine- and human-readable outputs with more than ten metrics, including univariate and multivariate statistics, database distance metrics, principal component analysis, propensity, basic privacy evaluation, and other information-rich tools ( see examples here).

The CRC collects, evaluates, and packages contributed deidentified Diverse Communities Data Excerpts as a research acceleration bundle. The CRC plan to update the acceleration bundle at least once during the program to allow for on-going submissions. The CRC invites researchers to use this research acceleration bundle. for investigation, comparison, and analysis and to submit their findings to a workshop.