Claire Morton is a third-year undergraduate student at Stanford University, majoring in mathematical and computational science and minoring in environmental justice. She is passionate about how statistics and community-based research can be combined to advance environmental justice goals. In her free time, she enjoys juggling.

We are living in an explosion of publicly available data. A huge amount of information is released in publications and publicly available surveys, updated data-sharing policies frequently require primary data to be accessible, and advancing technology facilitates more sophisticated analyses. All this data has power—power to affect all areas of policy, influence decision-makers, and, ultimately, tell people’s stories.

Statisticians and data scientists have a responsibility to analyze data in the most thoughtful way possible. We need to be informed by the context of the data we analyze, figure out the most critical questions to ask, and choose appropriate methods to answer these questions. However, traditional approaches to secondary data analysis (analysis of data that has already been collected) do not involve the people most affected by the analysis. This creates distance between statisticians or data scientists working with secondary data and the communities behind it.

If we don’t connect with the communities behind the data we’re looking at, we’re left with evidence that has been created without thoughtfulness.

By connecting secondary data analysis with community-based research, we can decrease this distance. Community-based research involves mutually beneficial collaboration between academic researchers and community partners. There are exciting synergies between community-based research and secondary data analysis. Because community-based research involves building two-way connections with community partners who have the power to set analytical priorities, it can build alignment between statisticians working with secondary data and the communities affected by its analysis. Community partners can direct secondary data analysis to ask the most impactful questions possible. Partners can also guide which data sets should be used for which purposes and identify errors or omissions in secondary data.

Based on these and other synergies, I’ve developed empathetic data science practice, which combines the two research approaches to their mutual benefit. Major principles of this practice are the following:

• Determine a wide range of potential stakeholders to engage in the research process. It can be difficult to think about how to define “community” in secondary data analysis because the data might not have been collected with the same groups that will be affected by its analysis. Because of this, researchers should determine a variety of potential stakeholders.
• Stay involved, even outside of funded research windows. The partnership is just as important as the publications, particularly when projects (like secondary data analyses) don’t have a clear arc of planning surveys or other data collection methods, data collection, and data analysis.
• Communicate project findings. Since secondary data may not have been collected from or by community partners explicitly, researchers may feel less of a need to share findings back to the communities. However, data is often viewed as more objective and therefore better evidence for policy change than other types of evidence, which means research findings must be communicated directly to the affected communities; when the potential for impact is greater, the need for science communication is, too.

If we don’t connect with the communities behind the data we’re looking at, we’re left with evidence that has been created without thoughtfulness. Through combining secondary data analysis with community-based research, we can produce more empowering and effective research.

WANT TO KNOW MORE?
 
The following papers focus on community-based research:
 
“Review of Community-Based Research: Assessing Partnership Approaches to Improve Public Health,” Annual Review of Public Health

“The Three Rs: How Community-Based Participatory Research Strengthens the Rigor, Relevance, and Reach of Science,” Environmental Justice

“The Truth, the Whole Truth, and Nothing but the Ground-Truth: Methods to Advance Environmental Justice and Researcher–Community Partnerships,” Health Education & Behavior