Transparency

Transparent processes are fundamental to trust in science. The people whose money supports science – whether those people are taxpayers, donors, or shareholders – should have access to accurate data on how funds are allocated and what they have produced. The data and decision-making processes underlying funding allocation should likewise be fully transparent to all stakeholders, including applicants.

Responsibility

Quantitative data have the power to explain and even predict what happens in the world around us. Using data to describe and direct complex systems like those that drive scientific progress has the potential to deliver important advancements, but it is essential to recognize that errors or misinterpretations can delay or derail important work. To manage this risk, every possible effort must be made to ensure that data are consistent and complete, comparisons are fair, controls are appropriately chosen, and analyses are delivered to stakeholders with sufficient context.

Public good

Science should serve society. Although the results may not be immediate, over time the research enterprise should provide measurable benefit to the public. Historically, such benefits have been easier to demonstrate for applied than for fundamental research, even though careful analysis shows that a subset of the latter has had outsized positive effects. A data-driven understanding of how all types of science contribute to the public good can help articulate the value of fundamental research and the pursuit of scientific curiosity.