The Data for Black Lives conference, held in January at the Massachusetts Institute of Technology, highlighted the many ways in which data interact with the lives of black people. From facial recognition technology to algorithms that predict criminal risk, data and technology can often feel like an unseen and unfamiliar force used to criminalize and disempower black people.
At the conference, I was struck by the many ways in which brilliant black researchers were flipping this notion on its head; yes, data and technology can reinforce existing disparities, but it can also illuminate the world around us and build power and agency among people who are traditionally shut out of decision-making.
This same sense of power and agency can be transmitted to communities that rarely engage with data–or at least the sort of quantitative data that many researchers engage with. There are many ways to engage communities around research findings including online data tools, community meetings, and presentations. However, there are fewer examples for how to directly involve the community in generating and processing data. This is certainly not for lack of interest; my conversations with civically-minded researchers often revolve around how to involve community members more deeply in their research.
Researchers can be unfamiliar with working in the community, and the notion of involving community members directly in the process can be daunting. How do you start? And what about data quality?
One model for engaging the community in data collection — community mapping — is a relatively low barrier entry point. I will discuss one example that typifies this strategy: the DC Preservation Network. Keep in mind that community mapping is just one of a number of ways to engage community members in the nuts and bolts of research — for example, others include community-based participatory research and data walks.
What is Community Mapping?
Community mapping is a process by which volunteers from the community collect spatial data on their neighborhood or city. The data can be on vacant or blighted housing, sidewalk or roadway conditions, or flood damage–really any data that has a spatial component. It engages community members in tracking and creating data about the neighborhoods in which they live. At the end of the process communities can literally see themselves in the data.
Community members may collect primary data and eventually be able to link it with existing administrative or survey data. One such project, Motor City Mapping, ran from 2013 to 2017 and engaged over 150 volunteers in a project to map blighted properties in Detroit. The project used an app that allowed volunteers to document residential and commercial property conditions. These data fed into a centralized database for quality control. Data Driven Detroit then linked the collected data to over 20 other data sets to inform Detroit’s overall strategy to reduce blight in the city.
Community mapping carries the added benefit of providing a potentially novel source of data that can be valuable beyond the ability to engage community members. Community mapping can generate data that are not currently released by the city or that have unique variables that the city may not have available. For example, the technique has been used to develop data on open gas stations after natural disasters as well as mapping the state of sidewalks near schools.
Community Mapping in Action
The DC Preservation Network, a project co-sponsored by the Coalition of Non-Profit Housing and Economic Development and the Urban Institute, works to pair on-the-ground expertise with parcel-level housing data. The Urban Institute provides data on at-risk housing using data integrated from multiple sources at the federal and local level. These data are then shared with local policymakers, housing officials, housing organizers, and community members living in the units themselves.
Sharing data with the community provides crucial context to help decide which buildings are most at-risk of losing their affordability. For example, the community might help us answer questions we don’t see in the federal and local data, such as: Is this unit owned by an owner with a history of selling off subsidized buildings? Is the building currently involved in a court case? Have the tenants in this building created a tenant organization? Advocates and organizers also benefit from closer familiarity with the data collection process, learning what building data is available and better targeting their scarce resources.
These questions provide vital context that underlying parcel data alone could never provide. The DC Preservation Network relies on researchers compiling administrative data and presenting it to community members to add, correct, and provide context and nuance to the data.
Empowering Communities through Data
There are substantial management hurdles to community data collection. Managing volunteers, coordinating meetings, and developing protocols and quality control all take time and money. Speaking of money, such projects can face difficulty in finding ongoing funding. Funders may not understand or value the ongoing work of community collected data, or may not believe the benefit is worth the cost. And as government priorities shift, agencies may begin collecting data that makes community collected data redundant.
However, in the right circumstances, community mapping can be a vital source of information for community members to understand what is occurring in their own neighborhood. The experience interacting with and handling data collection or validation can provide community members with a sense of agency and control over research being conducted in their neighborhood. Creating or augmenting existing data is a source of power in decision-making processes.
In the future, it is possible that community collected data could be vital in shedding light on some of the most pressing questions about our neighborhoods where data are scarce, such as evictions and displacement. Increasingly, data about communities is collected and used to power automated decision-making processes. Developing the tools for communities to create and understand their own data can give them power over how their own stories are told.
