iSchool Students Contribute to Nationally Recognized Project to Expose Historically Racist Housing Policies

Our newest team member Liz Laribee wrote this article on Mapping Inequality. She interviewed two team members about their personal experiences with the project and how it has impacted them. Check out the original article here.


A project of the iSchool’s Digital Curation and Innovation Center (DCIC) has been attracting national attention. The project, Mapping Inequality, is a multi-institutional research project that explores the long-term effects of redlining in New Deal America. It has been recently featured by NPR, National Geographic, Slate, Forbes, Dissent, City Lab, and others praising its dedication to uncovering a piece of obscured American history.

The Project

Utilizing archival practices and digital curation techniques, Mapping Inequality aims to transform historical documents into accessible digital records and display their content in new, innovative ways. The 1929 stock market crashed in triggered a devastating economic depression, which resulted in families losing their homes to foreclosure. The Home Owners’ Loan Corporation (HOLC) was born out of federal funding to assess the housing and neighborhood conditions so banks knew where (and where not) to give out loans. These findings were translated into maps with green, blue, yellow, and red outlines, with each color representing the “good” and “bad” areas for housing.

The institutions involved in this research have been working diligently for four years to digitize the documents and maps, extract the information, and make the data accessible to the public through the creation of a usable database. Researchers are coming extremely close to finishing up data transcription.

The Team

The team is formed by students, historians, archivists, and information managers. Mapping Inequality draws leadership from a collaboration between faculty of University of Maryland (Dr. Richard Marciano), Virginia Tech (Dr. LaDale Winling), Johns Hopkins (N. D. B. Connolly), and University of Richmond (Dr. Robert Nelson). But this is a project that has been fully adopted by its student workers, including the iSchool’s  Mary Kendig, Myeong Lee, Sydney Vaile, Shaina Destine, Darlene Reyes, Maddie Allen, Erin Duram, Benjamin Sagey, Martin Moreno, and Jhon Dela Cruz.


Student Interview

We spoke with iSchool students Mary Kendig and Myeong Lee about their experiences as members of DCIC and contributing to this notable and important innovation. The full interview is below:

This is a great story about how digital archives interact with social justice. Can you speak to that?

Mary: 100%. I would like these archival records to impact how the government and housing agencies interact and view neighborhoods containing minorities and crumbling infrastructure. Furthermore, in today’s political climate, there are many Americans who don’t understand or don’t believe that Black and Hispanic communities have suffered from systemic oppression over and over again from these housing policies. With the records and mapping visualization, these individuals might have a clearer picture of where highways and football stadiums were built; in cleared Black and Hispanic neighborhoods.

Myeong:  I think the meaning of social justice changes depending on time and space, so one of the best way to promote social justice is to present historical/factual data to people with an easy-to-use tools/technology, so that they can explore and think about what happened and how to choose the right direction for the future. In this sense, I think digitizing archives and designing a tool for that is very meaningful work.

What drew you to work at DCIC in the first place?

Mary: The ability and flexibility to learn new things. Furthermore, the staff is completely open to creative thinking and student initiative. It offers students the opportunity to make their own decisions on projects and make their own mistakes if something breaks or doesn’t work. Students don’t always have that freedom in their coursework or employment settings because their grades and income depend on it.

Myeong:  My research interest is in understanding the dynamics of local communities, so I have been using geo-tagged data a lot. When DCIC first opened at the UMD iSchool two years ago, I noticed that they were using GIS (geographical information systems) to deal with geospatial archival data. So I became interested in the projects at DCIC due to the overlapping interests, and in 2015, I had an opportunity to join the team.

What excites you most about the Mapping Inequality project?

Mary: This project excites me because it has real impact on communities that are currently suffering from previous discriminatory housing policies and present gentrification. We can look back at the data and say with confidence, “The neighborhoods and communities that did not receive loans suffered immensely and were cleared in Urban Renewal.”

Myeong: The most exciting thing is that I can use my technical skills to contribute to social justice. Especially, it is very meaningful for me to use crowdsourcing techniques and map-based visualizations to transcribe, manage, and show the historical data effectively.

What are your hopes for how the project will develop? Where could it go next?

Myeong: I think one of main goals for the project is to make the system scalable by making it possible to accommodate a large amount of archival data. Historical data such as redlining documents were created nationally, so there needs to be ways to not only present the bit dataset to people, but also digitize them using effective techniques. For now, massive digitization technology is not yet fully implemented but under development. I hope we could connect the digitization part to the mapping inequality tool in the next step. Then, I think we will be able to present the all data digitally, which will make it possible for users to search and filter data for their needs.

Mary: Next steps include building a database to house the data. Furthermore, we would like to conduct analytics and create visualizations so we can understand relationships between neighborhoods across US cities.