A strategy document that sets out USAID’s vision, goals, principles, and operational requirements for promoting open, inclusive, secure, and rights-respecting digital ecosystems to advance development and humanitarian outcomes worldwide.
United States Agency International Development (USAID)
This profile provides a cross-sectoral profile of the AI Risk Management Framework specifically for Generative AI (GAI), outlining risks unique to or exacerbated by GAI and offering detailed guidance for organizations to govern, map, measure, and manage those risks responsibly.
National Institute of Standards and Technology (NIST)
This is a modular, dynamic roadmap guides the U.S. HHS's ongoing implementation of open data policies while inviting public collaboration and feedback.
U.S. Department of Health and Human Services (HHS)
Guidance on improving how well AI systems can understand digital content. It emphasizes using machine-readable formats and applying clear content design strategies to enhance both AI processing and human accessibility
A case study documenting how a modular API layer was built to support a state-level paid family and medical leave program, improving interoperability, scalability, and user experience.
This presentation, from the Data Sharing Working Group, highlights a Michigan Department of Health and Human Services and Benefits Data Trust project to increase enrollment in the Women, Infants, and Children (WIC) program.
An interactive dashboard that enables users to explore and monitor key metrics of the Supplemental Nutrition Assistance Program (SNAP) Quality Control (QC) system.
This blog describes the purpose and functionality of the Look Before You Rent online tool, which enables users to search rental property addresses and view any recorded housing code violations, inspection outcomes, or complaints.
This Congressional Research Service (CRS) Insight discusses the Office of Management and Budget's (OMB)guidance for implementing the OPEN Government Data Act of 2019.
A central hub of guidance, standards, and supporting documentation explaining how UK public sector bodies should record and publish information about algorithmic systems to ensure transparency and accountability.
