Report by Judah Axelrod, Karolina Ramos, and Rebecca Bullied: “Data are central to understanding the lived experiences of different people and communities and can serve as a powerful force for promoting racial equity. Although public data, including foundational sources for policymaking such as the US Census Bureau’s American Community Survey (ACS), offer accessible information on a range of topics, challenges of timeliness, granularity, representativeness, and degrees of disaggregation can limit those data’s utility for real-time analysis. Private data—data produced by private-sector organizations either through standard business or to market as an asset for purchase—can serve as a richer, more granular, and higher-frequency supplement or alternative to public data sources. This raises questions about how well private data assets can offer race-disaggregated insights that can inform policymaking.
In this report, we explore the current landscape of public-private data sharing partnerships that address topic areas where racial equity research faces data gaps: wealth and assets, financial well-being and income, and employment and job quality. We held 20 semistructured interviews with current producers and users of private-sector data and subject matter experts in the areas of data-sharing models and ethical data usage. Our findings are divided into five key themes:
- Incentives and disincentives, benefits, and risks to public-private data sharing
Agreements with prestigious public partners can bolster credibility for private firms and broaden their customer base, while public partners benefit from access to real-time, granular, rich data sources. But data sharing is often time and labor intensive, and firms can be concerned with conflicting business interests or diluting the value of proprietary data assets.
- Availability of race-disaggregated data sources
We found no examples in our interviews of race-disaggregated data sources related to our thematic focus areas that are available externally. However, there are promising methods for data imputation, linkage, and augmentation through internal surveys.
- Data collaboratives in practice
Most public-private data sharing agreements we learned about are between two parties and entail free or “freemium” access. However, we found promising examples of multilateral agreements that diversify the data-sharing landscape.
- From data champions to data stewards
We found many examples of informal data champions who bear responsibility for relationship-building and securing data partnerships. This role has yet to mature to an institutionalized data steward within private firms we interviewed, which can make data sharing a fickle process.
- Considerations for ethical data usage
Data privacy and transparency about how data are accessed and used are prominent concerns among prospective data users. Interviewees also stressed the importance of not privileging existing quantitative data above qualitative insights in cases where communities have offered long-standing feedback and narratives about their own experiences facing racial inequities, and that policymakers should not use a need to collect more data as an excuse for delaying policy action.
Our research yielded several recommendations for data producers and users that engage in data sharing, and for funders seeking to advance data-sharing efforts and promote racial equity…(More)”