mapping for Movement hub

PROJECT Movement Hub is a digital platform created in response to the rise of anti-Asian American hate crimes across the United States during COVID-19. As part of this platform, I was tasked with creating a pair of maps to visualize relevant census data and policy protections, and to collect stories documenting hate crimes.

CLIENT Center for Neighborhood Knowledge @ UCLA; AAPI Civic Engagement Fund

COLLABORATOR Madeline Avram Blount, creative technologist

LOCATION United States (nationwide project)

LINK TO FULL SITE Movement Hub

Movement Hub is a centralized platform created to amplify the on-the-ground activism and organizing within Asian American and Pacific Islander (AAPI) communities across the country. As part of this project, the client wanted to build a data repository that would map critical information for advocates assisting victims of hate crimes. I was hired with my collaborator, creative technologist Madeline Avram Blount, to develop this mapping component - which would combine relevant census data, anti-hate crime policy protections, and crowdsourced stories documenting hate crimes.

Given the primary intended user (“helpers” or advocates assisting community members in the aftermath of a hate crime), the many layers of data involved, and the need to depict both the nationwide scope of the issue as well as local contexts, our team had to strategize to break-down complexity and keep the map usable and accessible. We approached this front-end challenge by dividing the end product into two interactive maps to avoid crowding too much information on a single map, and by creating a seamless and organic experience for users to switch back between different levels of geographic data. On the back-end, we needed to create an integrated framework that would allow community partners to have access to the data, and to easily update the map whenever new data was available. Below, read more about the nuts and bolts behind each map and our process for developing them.

WEBMAPPING USING THE CENSUS API

Our team developed the census data map using the Census Data API in combination with the Javascript library CitySDK and the webmapping platform Mapbox, and worked together using the collaborative coding platform Glitch. Rather than having to download large amounts of census data onto a local server, our framework queries and pulls data from the Census Bureau dynamically, then merges the statistical information with cloud-based geographic files to create a data visualization. In addition to avoiding having to store and host large datasets, this approach also allows for rapid updates anytime new census data is released.

On the front-end, the map starts at a nationwide view, and allows the user to dive in and explore data in greater detail at the state- and county-levels. The data is disaggregated at the county-level into the two key demographic groups that make up AAPI communities - Asian-Americans and Pacific Islanders - offering a more granular view. The user can click on each geography (State, county) to view further data indicators, such as the percentage of individuals with limited english proficiency.

MAPPING HATE CRIMES AND POLICY PROTECTIONS

For the second map, our client’s vision was to combine crowdsourced incidents of hate crimes in AAPI communities with an inventory of existing federal and state statutes that protect individuals against racially-motivated crimes. Both of these datasets (collected stories and policy statutes) would have to be readily accessible on the back-end by community partners and researchers working on the project, and the map needed to be updated as new data came in.

After discussing with our client, we chose Airtable as the data back-end as it offered a particularly user-friendly and secure interface. My collaborator Madeline developed the infrastructure to reformat the Airtable data for Mapbox, and display this data on our front-end map via an Express server in Node.js. Meanwhile, I focused on designing a data schema for the choropleth map and restructuring our client’s policy data to make it mappable using a unique geographic identifier (FIPS code).

After several prototypes and iterations of the user interface, we arrived at several key functionalities: a hover and click effect that allows the user to view detailed policy statues in an interactive info-window based on the selected geography, a search bar that enables the user to look up their own community or address, and a “fly to” effect that takes the user into a local geography when they click on a story point. Story points are color-coded based on four thematic categories (AAPIs in action, rise in anti-Asian violence, systemic inequalities, and racial justice). Finally, we added navigation instructions that orient the user to the map once they arrive at the page.

To facilitate the process of collecting and geocoding crowdsourced stories, we built a customer data entry form with a built-in geocoder for our client and their community partners to use. Our next steps for this project are to train partners to add stories from their communities to continue populating the map with lived experiences of how the current context is impacted Asian-American Pacific Islander communities.