DxP

Our project is a geographical analysis of demographics trends in the Detroit Metro area focused around the year 2018. We used a variety of sources, from American Community Survey (ACS) data to public survey data, to better understand the area and how various factors have changed it recently. A focus of this project was to create a guide on how publicly accessible data can be used to create deeper analysis and visualization. We also created documentation that traces our steps so it would be helpful to people trying to do similar projects. 

This guide is meant for folks who have some experience with data but wouldn’t consider themselves experienced practitioners. We wanted to lower the barrier to entry of doing interesting and important data analysis — knowing that these are skills that people can use to further policy, community organizing, and other streams of work that better the progressive ecosystem. 

Within the guide, we touch on data methodology and how to plan a data analysis project, how to source and store data in BigQuery, how to conduct a simple analysis in Looker Studio, and how to conduct a more advanced analysis in Tableau.

Fellow Bios

Data matching and linkage with ethnic data

Our project’s goal is to better understand the linkage and matching problem in political data, in which algorithmic biases against non-Anglicized names makes it more difficult for ethnic names to be properly matched against the voter file. 

There are many ethnic communities who either do not conform to a traditional “first name / last name” convention, possess diacritical marks like accents, or are rooted in non-Latin alphabets like Arabic or Chinese which necessitates correct usage of tones. While many people in those communities may have an Anglicized or shorthand nickname of their given name for official records, we know that this is less true in foreign-born and immigrant communities.

Our project examines the tradeoff involved in the matching and linking process in which individual records from disparate databases are linked together, for the purposes of political and civic engagement. We offer a short-term solution in the creation of an open-source Github repository, in which a “data dictionary” of common cultural names can be matched.

We understand that the long-term goal of this work is to build a radically inclusive tech ecosystem. A more cultured and linguistically informed voter file is only one step in that direction, and we know that there are several pathways possible towards that future.

Fellow Bios