Data Collaborative Case Study: The Atlas of Inequality and Cuebiq’s Data for Good Initiative
By: Michelle Winowatan
Tags: Data Collaborative, Data Stewardship, Examples, Data For Good, City Planning

Data Collaborative Case Study: The Atlas of Inequality and Cuebiq’s Data for Good Initiative Michelle Winowatan Follow Apr 8 · 3 min read

By Michelle Winowatan, Andrew Young, and Stefaan Verhulst

This is the third installment of an ongoing series of case studies on Data Collaboratives and Data Stewardship. These case studies intend to provide insights toward leveraging private data for public good in a systematic, sustainable and responsible manner. Subscribe to our Data Stewards Newsletter to be notified of future releases.

Photo by Christopher Burns on Unsplash

Summary: The Atlas of Inequality is a research initiative led by scientists at the MIT Media Lab and Universidad Carlos III de Madrid. It is a project within the larger Human Dynamics research initiative at the MIT Media Lab, which investigates how computational social science can improve society, government, and companies. Using multiple big data sources, MIT Media Lab researchers seek to understand how people move in urban spaces and how that movement influences or is influenced by income. Among the datasets used in this initiative was location data provided by Cuebiq, through its Data for Good initiative. Cuebiq offers location-intelligence services to approved research and nonprofit organizations seeking to address public problems. To date, the Atlas has published maps of inequality in eleven cities in the United States. Through the Atlas, the researchers hope to raise public awareness about segregation of social mobility in United States cities resulting from economic inequality and support evidence-based policymaking to address the issue.

Data Collaborative Model: Based on the typology of data collaborative practice areas developed by The GovLab, the use of Cuebiq’s location data by MIT Media Lab researchers for the Atlas of Inequality initiative is an example of the research and analysis partnership model of data collaboration, specifically a data transfer approach. In this approach, companies provide data to partners for analysis, sometimes under the banner of “data philanthropy.” Access to data remains highly restrictive, with only specific partners able to analyze the assets provided. Approved uses are also determined in a somewhat cooperative manner, often with some agreement outlining how and why parties requesting access to data will put it to use.

Data Stewardship Approach: Through its Data for Good initiative, Cuebiq provided access to location data that supported the Atlas’s development. The Data for Good initiative is an example of how active data stewardship can help data-holding companies find public utility in their data beyond their day-to-day business. Such utility includes the creation of scientific and public value by securely providing academic researchers and nonprofit organizations access to Cuebiq’s data assets. These collaborations involve a licensing agreement between Cuebiq and its partners, where all the parties pledge to adhere to certain privacy and data-handling standards to prevent potential risks that may arise, such as data breach and misuse. Further, Cuebiq also created the Director of Research Partnership and Data for Good role to carry out various data stewards functions, including internal coordination, partnership building, and risk assessment. This approach can serve as a good model for how companies can practice responsible data-sharing. Indeed, in early 2020, the MIT Media Lab team began using Cuebiq data to study the effectiveness of social distancing policies in New York City in light of the COVID-19 pandemic.

MIT Media Lab and Cuebiq Data Collaborative Operational Variables. Detailed description of each variable can be found here.

Read the full case study here.