Site icon fundsforNGOs

Robert Wood Johnson Foundation Grant to Support Data-Driven Community Equity (US)

Deadline: 04-Mar-2026

The Robert Wood Johnson Foundation Local Data for Equitable Communities grant provides $50,000 to U.S.-based nonprofit organizations to use local data to reduce inequities and improve community conditions. The program supports community-driven data collection and analysis to advance health equity and build healthier, more just places.

Robert Wood Johnson Foundation Local Data for Equitable Communities Grant Overview

The Robert Wood Johnson Foundation (RWJF) is inviting proposals from nonprofit organizations that use local data as a tool to address inequities and strengthen community conditions. The program emphasizes community-led approaches where data informs decisions, accountability, and action toward health equity.

Program Purpose and Strategic Focus

The grant supports projects that leverage local data to understand and address inequities affecting health and well-being. Health is defined broadly as a product of physical, economic, and social conditions within communities.

Key focus areas include:

Why Local Data Matters

Local data enables communities to identify challenges that may be overlooked by national or aggregated datasets. When residents and community organizations control how data is gathered and used, it becomes a powerful tool for equity, transparency, and sustainable change.

This program recognizes local data as essential for:

Funding Amount and Project Duration

Each selected organization will receive a grant of $50,000. Projects must be completed within a nine-month period.

Key funding conditions include:

Who Is Eligible to Apply

Eligible applicants must meet all organizational requirements.

Eligible organizations include:

Who Is Not Eligible

The following entities are not eligible to apply:

Collaboration and Partnership Rules

Applicant organizations may collaborate or contract with other entities to implement the project. However:

How the Grant Works

The program supports short-term, focused projects that demonstrate how local data can drive equitable change.

Projects should:

How to Apply

Applicants should prepare a clear and concise proposal outlining how local data will be used to improve community conditions.

Recommended steps:

  1. Confirm organizational eligibility

  2. Identify a specific equity-focused community challenge

  3. Define how local data will be collected, analyzed, and applied

  4. Demonstrate community involvement and leadership

  5. Submit one complete proposal on behalf of the organization

Incomplete or misaligned applications are unlikely to be funded.

Common Mistakes to Avoid

Applicants should avoid:

Frequently Asked Questions

What is the grant amount for each selected organization?

Each selected organization will receive $50,000.

How long can the project last?

Projects must be completed within nine months.

Who can apply for this grant?

Eligible applicants are U.S.-based nonprofit organizations with 501(c)(3) or 501(c)(4) status or organizations with an eligible fiscal sponsor.

Are government agencies or universities eligible?

No. Government entities, universities, and public institutions are not eligible to apply.

Can organizations partner with others on the project?

Yes, collaborations are allowed, but only one eligible nonprofit may serve as the applicant and lead organization.

Can individuals apply directly?

No. Awards are made to organizations only, not individuals.

Can current RWJF Local Data for Equitable Communities grantees apply?

No. Current grantees of this program are not eligible.

Conclusion

The Robert Wood Johnson Foundation Local Data for Equitable Communities grant empowers nonprofit organizations to use local data as a catalyst for equity, accountability, and healthier communities. By supporting community-driven data initiatives, the program strengthens local leadership and advances health as a fundamental right for everyone.

For more information, visit RWJFoundation.

Exit mobile version