Federal agencies seek to expand the role of the public, including members of marginalized communities, in the development of regulatory policy. At the same time, agencies are considering how to leverage data that is growing in size and complexity to ensure policies are fair and evidence-based. However, community engagement rarely extends to the process of data exploration and interpretation. This is a lost opportunity. Community members can provide critical context for quantitative and truthful data analysis and suggest ways of looking at data that inform policy responses to life’s pressing issues. Realizing this opportunity requires a structure of public participation where community members can expect both support from agency staff in accessing and understanding the data, as well as genuine openness to new perspectives on quantitative analysis. Is required.
To deepen community engagement in evidence-based policy development, federal agencies are implementing data collaborations in which employees and the public learn from each other about available datasets and their affordances to clarify policy questions. should be formed.
detail
Executive Order 14094 and subsequent Office of Management and Budget guidance memos direct federal agencies to increase public participation and community involvement in federal regulatory processes. The objectives of this policy include establishing two-way communication and promoting trust between government agencies and the public, especially those in historically underserved communities. Under the executive order, the federal government also aims to involve local communities early in the policy process. This new focus on community engagement is separate from the federal government’s longstanding commitment to evidence-based policy and efforts to ensure that the data available to agencies supports equity in policy decisions. It may seem that it is. Evaluating data and evidence is typically considered the job of people with highly specialized, quantitative skills. However, a lack of transparency around data collection and use can undermine public trust in government decision-making. Additionally, the community may have important knowledge that qualified experts do not have, knowledge that can help put data into context and make analyzes more relevant to the problems on the ground.
If the federal government is to achieve its goals of expanded participation and fair data, it must provide the public and sufficient public with opportunities to help shape how data is used to inform public policy. underserved communities need to create them. Data Collaboratives provides such an opportunity. Data collaborators consist of agency staff and individuals affected by agency policy. Each member of a data collaboration is considered a person with valuable knowledge and insight. The role of staff is not to explain or educate, but to learn together with community participants. To facilitate mutual learning, data collaborations will meet regularly and frequently (e.g. biweekly) over a period of one year.
Each data collaboration focuses on a policy problem that the agency wants to address. For example, the Environmental Protection Agency could establish a data collaboration on pollution prevention in the oil and gas sector. Depending on the policy issue, staff from multiple agencies may be involved along with community participants. The goal of the Data Collaborative is to uncover datasets that may be relevant to a policy problem, understand how they can inform the problem, and identify their limitations. Data Collaboration does not make formal recommendations or seek consensus. However, continued consideration of datasets and their affordances can be expected to build a more solid foundation for the use of data in policy development and the development of additional data resources.
Recommendations
The Office of Management and Budget should:
- Establish a government-wide data collaboration program in consultation with the Council of Chief Data Officers.
- Collaborate with federal agency leaders to identify policy issues that would benefit from data collaboration. It is expected that the Deputy Administrator, Head of Equity and Diversity, and Chief Data Officer will be consulted.
- Hire a full-time director of data collaboration to lead tasks such as coordinating with public participants, facilitating meetings, and ensuring relevant data resources are available to all collaboration members.
- Enable government agencies to provide the material support, such as salaries, childcare, and transportation, necessary to ensure the participation of underrepresented community members in data collaborations.
- We help agencies highlight data collaboration activities and results through social media, press releases, open houses, and other means.
conclusion
Data collaborations promote public participation and community engagement upstream of the policy process by creating opportunities for community members to contribute their lived experiences to data evaluation and framing of policy issues. This will foster two-way communication and trust between the government and the people. Data collaboration also helps ensure that data and its use in the federal government is fair by taking a broader view of how data analytics can promote equity and where relevant data is missing. It also helps insure. Finally, data collaboration is one way to enable individuals to participate in science, technology, engineering, mathematics, and medicine activities throughout their lives, improving the quality of American science and the competitiveness of American industry. Sho.
To learn more about the importance of making science open and read the rest of the published memo, visit the Open Science Policy Sprint landing page.
