On May 23, 2025, the White House issued Executive Order 14303, titled “Restoring Gold Standard Science,” marking a shift in how federal agencies must manage, interpret, and communicate scientific data. The executive order targets and revokes the Biden administration’s 2021 presidential memorandum “Restoring Trust in Government Through Scientific Integrity and Evidence-Based Policymaking.”
For government agencies shaping public policy and regulatory decisions, this order introduces new definitions for transparency in scientific activities. Now more than ever, agencies must employ robust data governance practices to ensure compliance.
A New Directive for Scientific Integrity
Executive Order 14303 emphasizes that scientific work conducted by federal agencies must meet rigorous criteria. It must be:
- Reproducible
- Transparent
- Communicative of error and uncertainty
- Collaborative and interdisciplinary
- Skeptical of its findings and assumptions
- Structured for falsifiability of hypotheses
- Subject to unbiased peer review
- Accepting of negative results as positive outcomes
- Without conflicts of interest
Agencies must document the assumptions and uncertainties underlying scientific models, and avoid reliance on highly unlikely or precautionary assumptions except where legally mandated. The order requires agencies to use a “weight of evidence” approach when scientific information is used for agency evaluation or decision making.
This directive applies broadly to scientific activities within all executive departments and agencies. Agency leadership is tasked with revising internal scientific integrity policies to align with these requirements and reporting on their implementation.
Implications for Data Governance Leaders
The executive order places significant new responsibilities on data governance teams to support these scientific standards. To comply, agencies will need to enhance how they manage scientific data and models by:
- Ensuring detailed metadata and data lineage: Every dataset, underlying assumption, and model version must be fully documented to enable reproducibility and auditability.
- Implementing transparency protocols: Agencies must clearly communicate what is known, what is assumed, and the degree of uncertainty in scientific analyses.
- Establishing systematic review and validation processes: Analysis methods and source data must be traceable and made available for peer review to uphold integrity.
These governance practices must extend beyond agency walls, as contractors and vendors must also adhere to the same rigorous standards.
FOIA and the Disclosure of Scientific Models
One of the executive order’s most significant policy shifts involves changes to how agencies must handle Freedom of Information Act (FOIA) requests related to scientific data. Under the new rules:
- Agencies are restricted from invoking FOIA exemptions—particularly 5 U.S.C. § 552(b)(5)—to withhold scientific data, models, and source code that substantially affect public policies or private sector decisions.
- Exceptions are made only for national security concerns, sensitive personal information, or confidential business data.
- Any decision to withhold such information under FOIA exemptions requires written approval from the agency head and prior notice to the White House Office of Science and Technology Policy (OSTP).
- Enforcement-related models used to guide regulatory actions are exempt from disclosure requirements.
This heightened transparency mandate means agencies must integrate FOIA readiness into their data governance strategies, balancing openness with legal protections for sensitive data.
Preparing for OSTP Guidance and Implementation Timelines
The order tasked the OSTP director with issuing detailed implementation guidance within 30 days. Now, each agency head must update policies accordingly and report on compliance actions by August 22, 2025.
During this transition, agencies must revert to scientific integrity policies that existed before January 20, 2021, until new frameworks are finalized. This interim period requires flexible and well-documented governance processes that can adapt quickly to evolving federal requirements.
Key Takeaways
Executive Order 14303 marks a new emphasis on scientific transparency in federal agencies. For data governance teams, this means elevating standards around documentation, model transparency, data sharing, and FOIA compliance. Strong data governance is no longer just a best practice, it is a critical enabler of trust.
Based on the cited policy objectives, the executive order appears to be designed to remove activist influence on science policy, especially in healthcare and environmental issues. This includes the rejection of equitable outcomes and eliminating community engagement in the decision-making process.
Agencies that prioritize their data governance strategies will be best positioned to deliver science that withstands scrutiny in this new regulatory environment.
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