Mapping inequality
For this project I decided to look at Mapping Inequality, made by Robert K. Nelson and others. The project itself is a text and map based website designed to educate on redlining in America. The site has many different pages which provide more information and teaching material regarding redlining. On top of this, and maybe the most interesting part of the site, is the interactive map. Starting from a country wide view you are able to zoom in on different higher populated areas. A interactive graphic then appears which allows you to look at specific counties and provides information. It gives a detailed excerpt about the current state of the county with information about diversity, income, and development.
Sources / Contributors
This DH projects has a large amount of contributors and sources as well as being the second iteration of the site. Just to name a few: Robert K. Nelson, development of the web application; Justin Madron and Riley Champine, creation and management of the spatial data for the project; Chad Devers, web designed; Nathaniel Ayers, created spatial data; Annie Evans, creation of K-12 learning resources; LaDale Winling; editor for the introductions (with scholars); Reagan Tobias, Cassandra Cogan, and Jared Kimball, general work. On top a sleuth of experts in each field, they were able to work with MapBox to create the interactive map. A startup AI map company which generously donated data and viewers to be incorporated into the application.
Process / Presentation
The application was built with the contribution of many people focusing on specific aspects of the webpage. The interactive viewer works through an API to MapBox hosted on AWS web services which dynamically loads content to the viewer. A different server endpoint, https://dsl.richmond.edu/, stores the data related to other pages and county descriptions. This is most likely data purely created by the DH team, not MapBox. This does leave me with some questions. Does MapBox save redlining statistics? The map viewer color codes areas based on different metrics which I would assume is data gathered by the DH team. Although, most map functionality is through MapBox which leads me to wonder how much data the MapBox and DH team are sharing.
These two data sources provide full functionality for the site, both the map viewer and educative content. The separation of this data is intuitive for the desired audience. It allows users to learn about redlining in a more structured educational format as well as exploratory learning through the map viewer. This allows for use in educative institutions and general use cases.
