Administrative Data on Kailas Venkitasubramanian

Bayesian Improved Surname Geocoding: How It Works and Where We Use It

Sun, 15 Sep 2024 00:00:00 +0000

If you work with administrative data long enough, you run into the same wall eventually: the dataset has everything you need except race and ethnicity. Hospital discharge records, voter files, tax records, benefits enrollment data — these are often rich with information about where people live, what services they use, and what outcomes they experience. But ask whether they capture race or ethnicity, and the answer is usually no, or inconsistently, or only in ways that aren’t usable.

CRDT - Data Privacy

Wed, 10 Apr 2024 00:00:00 +0000

On data privacy practice at the Charlotte Regional Data Trust

Designing Reproducible Data Pipelines for Community Research

Sat, 09 Mar 2024 00:00:00 +0000

In the first post of this series, I argued that reproducibility is not a technical luxury for community research institutions—it is an ethical and operational obligation. In this post, I want to move from philosophy to plumbing—because this is where reproducibility becomes real.

Specifically: what does it mean to design reproducible data pipelines in a community research environment?

At the UNC Charlotte Urban Institute, this question became concrete as we built the Quality of Life Explorer, developed deposit and extraction pipelines for the Charlotte Regional Data Trust, and began orchestrating workflows using Apache Airflow in an AWS environment.

Revamping the Charlotte Regional Data Trust - The story so far

Mon, 22 May 2023 00:00:00 +0000

CRDT Anonymization and Privacy Project

Mon, 06 Jun 2022 00:00:00 +0000

Summary

Objective(s) and Scope

The project involves the development and implementation of protocols and best practices in privacy for data dissemination, including statistical disclosure control procedures of the integrated data system hosted by CRDT. This includes creating guidelines for data collection, storage, and dissemination, as well as implementing robust technical measures to prevent unauthorized access and disclosure of sensitive information.

The project will start with a comprehensive review of current privacy practices and identification of areas that need improvement. Based on this review, a set of protocols and best practices will be developed and incorporated into the organization’s data management processes. This will include the implementation of statistical disclosure control procedures to protect sensitive information. Training sessions will be conducted to educate employees on the new privacy protocols and best practices.

Institute for Social Capital - Data Privacy & Security - Present and Future

Mon, 06 Dec 2021 00:00:00 +0000

On data privacy practice at the Institute of Social Capital