Equitable Adaptation Legal & Policy Toolkit

Collecting and Applying Qualitative Data

As discussed in the previous section, quantitative data, or statistical and structural data, are valuable tools for decisionmaking but can omit valuable information about the feasibility and effectiveness of policy options in neighborhoods. Policymakers may achieve a more comprehensive assessment of community needs by placing an equal emphasis on the findings from both quantitative and qualitative data.  

A map showing the overlap of Race and Water Shutoff Policies in Southeast Michigan. It clearly shows an overlap of the areas with the harshest water shutoff policies and African American populations.
Data showing the overlap of Race and Water Shutoff Policies in Southeast Michigan (Source: We the People of Detroit)

There are a number of methods for collecting qualitative data. The most common methods include first-hand interviews, focus groups or recorded observations, and document analysis.See footnote 1 Project participants can also collect qualitative data with surveys, focus groups, and observations to develop a more nuanced profile of a community. Qualitative data is also more likely to be collected through direct community engagement and can capture insights that are representative of a range of ages, races, and income levels. Studies with data triangulation (e.g. two or more data collection methods: interviews and focus groups) typically have greater credibility and are more likely to capture subjective information and conclusions that traditionally cannot be captured by quantitative data alone.See footnote 2 

The assessment of qualitative data can also be an effective way to measure community participation and trust. Qualitative data can strengthen the nexus between community storytelling and policy metrics to measure outcomes. A designated project participant can collect data through phone interviews and evaluate the stories to develop metrics to both measure outcomes and gauge community trust. In addition, qualitative data can measure community participation to ensure that community-specific experiences and knowledge are contributing to the development of project objectives and goals. An assessment of community feedback may provide project participants with data to measure community interest as an indicator of the likelihood that the project will achieve intended outcomes. By establishing data, metrics, and benchmarks to indicate broad-based citizen participation, policymakers can enhance the likelihood that the intended outcomes will benefit frontline communities.

Community Mapping

Community mapping is a process whereby community volunteers collect observational data about their neighborhood that would otherwise evade geospatial mapping.See footnote 3 Individuals record observations about their surroundings detailing neighborhood elements including vacant or blighted housing, sidewalks, or roadway conditions. Volunteers collect data, often through a web-supported application or ‘app’, and provide valuable input to policymakers that complement quantitative data collected by planning professionals. Successful community mapping activities provide policymakers with first-hand, on the ground perspectives that would not otherwise be reflected by other forms of local, state, or federal data. For example, community mapping can answer questions like whether tenants have created a tenant organization or whether plans to plant trees on particular blocks are more likely to create safety issues than achieve the intended benefit of reducing urban heat impacts. How a parcel of land is used represents data that identifying the parcel alone through geospatial information could not provide.

The participatory mapping process requires ongoing management to coordinate volunteers and meetings, while also developing protocols and quality control. Other considerations include ensuring the availability of sustained funding to invest in the community to conduct the ongoing work.See footnote 4 Community mapping is a critical tool in equitable adaptation planning. By capturing the first-hand insights of frontline communities, policymakers can supplement quantitative data with qualitative data that can improve the likelihood that the project design outcomes are closely aligned with the needs of the community.

Community-based Participatory Research (CPBR) Methods

Community-based participatory research is a collaborative approach to research that includes the input of community members, organizational representatives, researchers, and other stakeholders.See footnote 5 Together, policymakers and community stakeholders provide information to engage the community at each stage of the research process. 

At the initial stages of a planning process, project participants can provide platforms for sharing initial census and other related data that have helped policymakers identify a set of adaptation challenges. Data walks and photovoice, two examples of community mapping, offer ways for the community to offer their first-hand perspectives to inform policymaking. Policymakers can initiate these activities by first presenting background and descriptive data in a workshop setting to introduce the community to the statistics that are driving the policymaking process. These information sessions also provide policymakers an opportunity to produce formats for data sharing including texts and graphics, to make the data accessible and provide a means for future community engagement. Second, data walks or photovoice, encourage community members to identify and capture, through pictures and stories, their surroundings to provide input and ensure that there is a robust contribution to strengthen the collective analysis and understanding of the data. Last, the information collected during the course of data walks or photovoice can help to inform policymaking and programming to address the needs of the community and can inspire collective action.See footnote 6 This initial first step in the education and outreach process ensures that place-based research improves the quality of data collection by developing partnerships with the community.

At later stages of project execution, the participatory research process can include community data collection that directly contributes to the body of knowledge about the adaptation challenge. Community members can participate in citizen science activities by collecting the data and can also play a role in developing metrics for measuring the way in which spaces are utilized within their community. For example, as a part of the programs emerging from the National Integrated Heat Health Information System (NIHHIS), NOAA’s Communication, Education, and Engagement division is supporting and coordinating community science mapping field campaigns to help communities develop workshops and explore policy interventions to address urban heat island effects.See footnote 7 The NIHHIS platform includes social vulnerability data layered with NOAA climate-related projections to map extreme heat. Volunteers receive training to collect data and map the distribution of heat in the morning, afternoon, and evening and the findings can be shared on social media. Third-party consultants then process data and produce predictive surface models of temperature and heat index throughout the day. The city teams review the Heat Watch results and meet with consultants to discuss data and contemplate next steps towards addressing extreme heat. Stakeholder feedback from the data collection and sharing process is iterative and improves analysis and methods for future data collection and policymaking.See footnote 8 

We the People of Detroit Community Research Collective (WPD CRC) is another example of community participatory research where community-based organizations led an effort to collect qualitative data as evidence of policy impact on residents. The WPD CRC is a collaboration between community activists, academic researchers, and designers, engaged in a four-part research process that included (1) mapping the geographic impact of water policies on the city; (2) conducting a city-wide community survey to assess the health needs after a disaster; (3) creating a citizen science project to test the impact of water shutoffs on residential water quality; and (4) launching a story mapping project to support youth in telling individual and collective narratives about the impact of austerity on their community.See footnote 9 The research collective also executed a two-year, city-wide public health survey investigating the impact of water shutoffs on public health and published a book ‘Mapping the Water Crisis: The Dismantling of African American Neighborhoods in Detroit’(2016). The community-based participatory research process has provided statistically significant data to demonstrate the impact of policy interventions on water insecurity and psychological distress among residents.See footnote 10

Lessons Learned

  • Qualitative data collected through surveys, data walks, photovoice, and community mapping provides policymakers with first-hand lived experiences of residents that quantitative data does not capture.
  • Qualitative data can help determine the effectiveness of policy interventions by gauging the quality of community participation and trust.
  • Interviews and surveys provide valuable insights about the mental health, safety, or other emotional experiences residents may have in a reaction to a policy intervention that may not be sufficiently captured using quantitative data alone.
  • Community-led data collection that includes responses to surveys at each stage of the community engagement process provides policymakers with a tool for assessing whether the project outcomes benefited the community as intended.



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