Federal agencies are striving to expand the role of the public, including members of marginalized communities, in developing regulatory policy. At the same time, agencies are considering how to mobilize data of increasing size and complexity to ensure that policies are equitable and evidence-based. However, community engagement has rarely been extended to the process of examining and interpreting data. This is a missed opportunity: community members can offer critical context to quantitative data, ground-truth data analyses, and suggest ways of looking at data that could inform policy responses to pressing problems in their lives. Realizing this opportunity requires a structure for public participation in which community members can expect both support from agency staff in accessing and understanding data and genuine openness to new perspectives on quantitative analysis.
To deepen community involvement in developing evidence-based policy, federal agencies should form Data Collaboratives in which staff and members of the public engage in mutual learning about available datasets and their affordances for clarifying policy problems.
Executive Order 14094 and the Office of Management and Budget’s subsequent guidance memo direct federal agencies to broaden public participation and community engagement in the federal regulatory process. Among the aims of this policy are to establish two-way communications and promote trust between government agencies and the public, particularly members of historically underserved communities. Under the Executive Order, the federal government also seeks to involve communities earlier in the policy process. This new attention to community engagement can seem disconnected from the federal government’s long-standing commitment to evidence-based policy and efforts to ensure that data available to agencies support equity in policy-making; assessing data and evidence is usually considered a job for people with highly specialized, quantitative skills. However, lack of transparency about the collection and uses of data can undermine public trust in government decision-making. Further, communities may have vital knowledge that credentialed experts don’t, knowledge that could help put data in context and make analyses more relevant to problems on the ground.
For the federal government to achieve its goals of broadened participation and equitable data, opportunities must be created for members of the public and underserved communities to help shape how data are used to inform public policy. Data Collaboratives would provide such an opportunity. Data Collaboratives would consist of agency staff and individuals affected by the agency’s policies. Each member of a Data Collaborative would be regarded as someone with valuable knowledge and insight; staff members’ role would not be to explain or educate but to learn alongside community participants. To foster mutual learning, Data Collaboratives would meet regularly and frequently (e.g., every other week) for a year or more.
Each Data Collaborative would focus on a policy problem that an agency wishes to address. The Environmental Protection Agency might, for example, form a Data Collaborative on pollution prevention in the oil and gas sector. Depending on the policy problem, staff from multiple agencies may be involved alongside community participants. The Data Collaborative’s goal would be to surface the datasets potentially relevant to the policy problem, understand how they could inform the problem, and identify their limitations. Data Collaboratives would not make formal recommendations or seek consensus; however, ongoing deliberations about the datasets and their affordances can be expected to create a more robust foundation for the use of data in policy development and the development of additional data resources.
The Office of Management and Budget should
- Establish a government-wide Data Collaboratives program in consultation with the Chief Data Officers Council.
- Work with leadership at federal agencies to identify policy problems that would benefit from consideration by a Data Collaborative. It is expected that deputy administrators, heads of equity and diversity offices, and chief data officers would be among those consulted.
- Hire a full-time director of Data Collaboratives to lead such tasks as coordinating with public participants, facilitating meetings, and ensuring that relevant data resources are available to all collaborative members.
- Ensure agencies’ ability to provide the material support necessary to secure the participation of underrepresented community members in Data Collaboratives, such as stipends, childcare, and transportation.
- Support agencies in highlighting the activities and accomplishments of Data Collaboratives through social media, press releases, open houses, and other means.
Data Collaboratives would move public participation and community engagement upstream in the policy process by creating opportunities for community members to contribute their lived experience to the assessment of data and the framing of policy problems. This would in turn foster two-way communication and trusting relationships between government and the public. Data Collaboratives would also help ensure that data and their uses in federal government are equitable, by inviting a broader range of perspectives on how data analysis can promote equity and where relevant data are missing. Finally, Data Collaboratives would be one vehicle for enabling individuals to participate in science, technology, engineering, math, and medicine activities throughout their lives, increasing the quality of American science and the competitiveness of American industry.
While the U.S. government grapples with the definition of the bioeconomy and what sectors it does and does not contain, another definitional issue needs to be addressed: What does sustainability mean in a bioeconomy?
Federal clearinghouses should incorporate open science practices into their standards and procedures used to identify evidence-based social programs eligible for federal funding.
To better address security and sustainability of open source software, the United States should establish a Digital Technology Fund through multi-stakeholder participation.
Building on existing data and privacy efforts, the White House and federal science agencies should collaborate to develop and implement clear standards for research data privacy across the data management and sharing life cycle.