Best Practice on Kailas Venkitasubramanian

CRDT - Data Privacy

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

On data privacy practice at the Charlotte Regional Data Trust

Revamping the Charlotte Regional Data Trust - The story so far

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

Releasing v1.0 of the Charlotte-Mecklenburg Quality of Life Explorer Data Pipeline

Thu, 16 Mar 2023 00:00:00 +0000

A successful wrap

It’s a great day today.

We completed the version 1.0 of the Charlotte-Mecklenburg Quality of Life Explorer automation project. It’s hard to put in words how exciting and rewarding this feels but I’ll try anyways.

We managed to automate most of the data and computational processes needed to generate the 80-odd quality of life indicators featured in the explorer and create functional data pipelines to serve the application. Through this work, we’ve accomplished a significant reduction of our project workload and fundamentally transformed the nature of our engagement in this project. The completion of this work also revitalizes our team’s vision to building a reproducible data science framework at the Urban Institute and a unified data ecosystem. Let me tell you how all this worked out.

Reproducible Research Framework at the Charlotte Urban Institute: Why It Matters Now

Fri, 08 Jul 2022 00:00:00 +0000

In recent years, conversations about reproducibility have moved from academic journals into policy circles, foundations, and government agencies. What was once framed as a “replication crisis” in psychology has broadened into a wider concern about the credibility, transparency, and cumulative nature of scientific work across disciplines (Open Science Collaboration, 2015).

For those of us engaged in quantitative community research—especially in dynamic regional contexts like the Charlotte metropolitan area—reproducibility is not merely a philosophical concern. It is an operational one.

CRDT Technical Operations Manual

Mon, 04 Apr 2022 00:00:00 +0000

Summary

Objective(s) and Scope

The goal of this project is to create a comprehensive technical operations manual that documents all operational processes of the Charlotte Regional Data Trust The manual will serve as a single point of reference and provide clear, up-to-date information on all operational procedures.

The manual will be created using Rmarkdown, a tool that allows for the creation of rich, interactive documents. The manual will be hosted as a website that can be easily updated and maintained by team members.

CRDT Data Documentation Project

Thu, 03 Mar 2022 00:00:00 +0000

Summary

Objective(s) and Scope

The project seeks to enhance the quality and completeness of CRDT’s data documentation, and establish a centralized and organized infrastructure for storing and managing metadata.

The project includes reviewing the existing metadata, developing standardized data documentation (metadata, codebook, data dictionary), and implementing a data infrastructure for storing and organizing metadata for all databases.

Expected Outcomes

Improved data documentation quality and completeness.
Consistent and standardized data documentation across all databases.
A centralized and organized infrastructure for storing and accessing metadata.

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

CRDT Data Integration Project

Tue, 05 Oct 2021 00:00:00 +0000

Summary

Background

This is part of the CRDT Data Infrastructure project

Objective(s) and Scope

This project aims to develop improved data integration mechanisms for CRDT’s data assets, ensuring accurate and consistent data integration. This involves the development of an entity resolution framework and the implementation of probabilistic record linkage techniques to enhance the CRDT’s data integration processes.

The project will start with a comprehensive review of CRDT’s current data integration mechanisms and identification of areas for improvement. Based on this review, an entity resolution framework will be developed to ensure accurate identification of entities across different data sources. Probabilistic record linkage techniques will be implemented to link records from different data sources and provide a unified view of the data.