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Data Equity Principle 7

Restore communities as data experts using culturally responsive approaches to engagement and co-creation that support equitable data use.


Inequitable power dynamics between data users and communities can perpetuate the disparities that data users aim to address. However, these power dynamics are not inevitable: data users can and should proactively mitigate unintended consequences by involving communities in all phases of the data life cycle, from planning through co-creating solutions. Intentional engagement can promote mutual understanding of assets and challenges within a community, ensuring that data projects are relevant to communities, and that results can be used to drive meaningful change. Restoring communities as data experts involves more than simply offering a seat at the table. It means creating roles for community members to meaningfully impact or lead decision making, valuing their expertise as an integral part of the process, and building relationships rooted in respect to bridge data, policy, and practice.

Data users should seek to understand which communities are affected, both directly and indirectly, by the issue being addressed. In the context of E-W systems, community members might include students, families, educators, and more. Data users should further consider identifying which groups are adversely affected through an intersectional lens, such as Black students with disabilities. Then, data users should identify ways to embed community perspectives throughout the project, starting with its conception. Single, point-in-time engagement is typically insufficient—isolated outreach after decisions have been made may be seen as a “box-checking” exercise to nominally gather input. For example, rather than facilitate a single community listening session, data users might recruit community members with relevant lived experience for a recurring advisory council. In its most robust form, this might take the form of CBPR, in which community members actively engage as equal partners in the data project. However, no engagement model is one-size-fits-all, and community members might play a variety of roles depending on the project’s scope, purpose, and timeline.xxxiii Building in multiple entry points and avenues for engagement or feedback is essential.

Communities, especially marginalized communities, are often burdened with data initiatives that extract information for personal and institutional gain. To build trusting and productive relationships, data users should define clear roles and expectations for engagement, while collaborating with community partners to determine preferred engagement methods (for example, is it more feasible for community members to participate virtually or in person? During the workday or in the evening? Would they prefer to provide written or verbal feedback?) and opportunities to reduce barriers to participation (for example, by providing child care for in-person activities). Community members should also be equitably compensated to ensure that the partnership is mutually beneficial, and to signal that community members’ time and expertise are valued at levels commensurate with that of other experts. Data users should look for opportunities to build capacity within the community as part of the engagement (for example, through collaborative learning processes for data analysis and interpretation) to promote the community’s ability to advocate for itself and drive sustained progress beyond the conclusion of the data project. Engaging community members and co-creating opportunities to honor their expert knowledge are foundational activities to successfully implement all data equity principles described in this report.

xxxiii See Methods and Emerging Strategies to Engage People with Lived Experience (Skelton-Wilson et al., 2020) for a discussion of various roles for individuals with lived experience, including storyteller, advisor, grantee, partner, or staff member.

Community collaboration in NYC improves student outcomes

In New York City’s Community Schools model, the district provides formal support for data sharing and collaboration between school leaders and community partners. Confidential data sharing agreements enable schools and communities to access secure, real time data on attendance, behavior, and course performance. School leaders and community partners meet regularly to review data, interpret trends, and identify appropriate interventions. The city’s Office of Community Schools provides training and support on meeting facilitation, which includes guidance related to inclusive decision making. A stud y by the RAND Corporation showed that within the first three years (2015-2018), community schools positively affected attendance, on time grade progression, and high school credit accumulation, while reducing rates of chronic absence. Other state and district education leaders can apply lessons from New York City to promote meaningful community participation in decision making (Data Quality Campaign, 2018).

Applying this Principle

Key phases for this principle
Example applications

Identify what you mean by “priority communities,” that is, who is directly and indirectly affected by the focal issue. Be careful not to assume that racial, ethnic, or socioeconomic diversity indicates lived experience relevant to the project. Collaborate with community members to align on what the key issues are and which perspectives to prioritize. Examine potential power dynamics between data users and communities.


Recruit members of priority communities to participate in initiative teams or advisory councils. Honor the intersectionality of collaborators’ identities by recruiting individuals who have had a variety of experiences within the same community and therefore might bring nuanced perspectives on the issue or project. Establish decision-making criteria that systematically incorporate community perspectives. Use facilitation methods that promote equitable participation. For example, if facilitating a meeting involving policymakers and community partners, design activities that capture equally weighted input from all participants, such as anonymous ranked-choice voting.


Add dimension to findings through anecdotal and contextual information from lived experiences. Engage community partners when reviewing preliminary findings to validate that data have not been misinterpreted.


Visualize and communicate data and findings using plain language so that they are easy to interpret, accessible to communities, and can be used to drive change. Share data in a variety of formats, such as at town halls, at cultural events, and via email or webinar. Build trust with communities by providing timely access to data. For example, if a school administration is evaluating whether to include a program in its budget for the next school year, the administration must receive information before the budget is due to support data-driven decision making.

Reflection Questions

  • Which groups would this data project affect? Who can help validate our understanding of key groups or illuminate blind spots?
  • Who can we recruit from priority communities to participate throughout the project life cycle? How will we reach them? How will we compensate them for their involvement?
  • How will we systematically incorporate different groups’ perspectives in decision making?
  • What has the community engagement process revealed about the experiences, burdens, and benefits for different groups?

 Be On The Lookout

Be careful not to exploit or tokenize lived experience. Feeling pressure to speak on behalf of an entire community can be burdensome for people. Avoid suggesting a monolithic view of “community” by incorporating a variety of perspectives and honoring the diversity of experiences within communities. For example, invite several members from the community with diverse backgrounds to serve on an advisory council, not just a single representative. To avoid exploiting lived experience, data users should also take an inclusive, human-centered, trauma-informed approach to engaging the community to mitigate the risk of retraumatizing individuals when discussing potentially sensitive topics.

Additional Resources

  • Why Am I Always Being Researched?. This Chicago Beyond resource offers practical guidance for community organizations, researchers, and funders looking to address inequities and unintended bias in research projects.
  • Methods and Emerging Strategies to Engage People with Lived Experience. This brief by Skelton-Wilson et al. discusses strategies and best practices for engaging people with lived experience in federal research initiatives and discusses how they may serve in various roles.
  • Making Racial Equity Real in Research. This report by Creger, geared toward funders, researchers, and community partners, offers five key steps to establishing effective partnerships using an anti-racist approach.
  • Engaging People with Lived Experience Toolkit. This step-by-step guide, developed by 100 Million Healthier Lives, includes supporting resources and examples to help data users effectively and equitably engage with community members with lived experience.
  • The Spectrum of Community Engagement to Ownership. This toolkit by Facilitating Power helps data users understand and apply a spectrum of community partnership models, ranging from consultation to community ownership.


The framework's recommendations are based on syntheses of existing research. Please see the framework report for a list of works cited.

This website was funded in part by the Bill & Melinda Gates Foundation.