Chapter 21: Qualitative Data Methods

Chapter Overview

This chapter introduces qualitative data methods for Community Mapping — the structured approaches for gathering, documenting, and analyzing lived experience, stories, meanings, and relationships. Qualitative methods answer the "why" and "how" questions that numbers alone cannot address. They make space for resident voice, local knowledge, and the texture of community life. Effective Community Mapping integrates qualitative data with spatial and quantitative analysis, treating numbers and narratives as complementary forms of evidence.

Learning Outcomes

By the end of this chapter, you will be able to:

Explain the purpose and value of qualitative data in Community Mapping
Identify appropriate qualitative methods for different research questions
Conduct interviews, focus groups, and observation with ethical rigor
Recognize the distinct responsibilities of working with oral histories and visual documentation
Apply field note and community diary methods to capture ongoing observation
Distinguish participatory research from extractive data collection
Analyze qualitative data using coding, thematic analysis, and synthesis techniques

Key Terms

Qualitative Data: Non-numeric information that captures meaning, experience, perspective, and context — including words, images, stories, and observations.
Thick Description: Detailed, context-rich observation that captures not just what happened, but the social meanings and cultural context (Geertz, 1973).
Thematic Analysis: A systematic process of identifying, organizing, and interpreting patterns (themes) across qualitative data.
Member Checking: The practice of sharing findings with research participants to validate interpretation and ensure their voices are accurately represented.
Saturation: The point in qualitative research when new data no longer reveals new themes or insights.
OCAP Principles: Ownership, Control, Access, and Possession — a framework for Indigenous data sovereignty developed by the First Nations Information Governance Centre.

21.1 Interviews

Interviews are structured conversations designed to gather in-depth information about experience, perspective, knowledge, or meaning. In Community Mapping, interviews help researchers understand how residents perceive place, what barriers they face, what assets matter most, and what changes they hope to see.

Interviews can be structured (following a fixed script of questions), semi-structured (using a flexible guide with room for follow-up), or unstructured (open-ended conversation). Most Community Mapping interviews are semi-structured — specific enough to ensure key topics are covered, flexible enough to follow unexpected insights.

A good interview guide starts with the research question. If you are mapping food access, you might ask: Where do you shop for groceries? How do you get there? What barriers do you face? What would make food access easier? Each question should be open-ended, neutral, and clear. Avoid leading questions ("Don't you think the bus system is terrible?") and yes/no questions that shut down conversation.

Building rapport is essential. Interviews are not interrogations. Begin with introduction and informed consent. Explain who you are, why you are doing the research, how the data will be used, and what protections are in place. Give participants the right to skip questions, pause, or end the interview. Record only with explicit permission, and honour refusals.

Active listening is the core skill. Listen more than you talk. Follow the participant's lead when they introduce a topic you hadn't anticipated. Notice body language, tone, and what is not said. Take notes even when recording — recordings fail, and note-taking shows attentiveness.

Interviews produce rich, detailed data — but they are time-intensive. One hour of interview can take three to four hours to transcribe and analyze. Sampling strategy matters. You cannot interview everyone. Choose participants who bring diverse perspectives: long-time residents and newcomers, different ages, different neighborhoods, different relationships to the place. Aim for saturation — the point where new interviews are no longer revealing new themes.

Finally, interviews create ethical obligations. Participants trust you with their stories. Honour that trust. Anonymize identifying details unless participants explicitly consent to attribution. Store data securely. Share findings in accessible formats. When the research is complete, offer participants copies of the final report or map.

21.2 Focus Groups

Focus groups are facilitated group discussions, typically with 6 to 10 participants, designed to explore shared and divergent perspectives on a topic. In Community Mapping, focus groups are particularly useful for identifying collective priorities, surfacing disagreements, and understanding how community members talk about place when they are in conversation with one another.

Focus groups generate different data than individual interviews. The group dynamic itself becomes part of the data. Participants respond to, build on, and challenge each other's ideas. A statement one person makes can trigger a memory or perspective from someone else. This interplay can reveal social norms, power dynamics, and collective meaning-making in ways that one-on-one interviews cannot.

Facilitation is the key skill. A good facilitator keeps the conversation focused without being rigid, ensures quieter voices are heard, and prevents dominant participants from monopolizing the discussion. Ground rules help: respect others, speak one at a time, no personal attacks, confidentiality (what is shared in the room stays in the room). The facilitator must also watch for signs of discomfort or harm — if a participant is visibly distressed, offer a break or the option to step out.

Focus groups work best when participants have something in common — they live in the same neighborhood, use the same service, or share a common experience. Homogeneous groups (e.g., all youth, all seniors) may feel safer and speak more freely. Heterogeneous groups (mixing ages, backgrounds, or perspectives) can generate richer debate but may also reproduce existing power imbalances.

Recruitment matters. Compensate participants for their time — cash, gift cards, food, transit tokens, or childcare support. Hold sessions at times and locations that work for participants, not just for researchers. If language is a barrier, provide interpretation. If literacy is a barrier, use visual prompts or verbal discussion instead of written materials.

Document focus groups carefully. Audio recording is standard (with consent), but also assign a note-taker to capture body language, group dynamics, and moments when multiple people speak at once. After the session, debrief with the facilitation team while observations are fresh.

One caution: focus groups are not safe for discussing sensitive or stigmatized topics. A resident experiencing homelessness may not feel comfortable disclosing their housing status in a group. A youth facing violence at home may not speak freely in front of peers. For sensitive topics, individual interviews are more appropriate.

21.3 Observation

Observation is the systematic practice of watching, listening, and documenting what happens in a place. It is one of the oldest research methods — and one of the most underused in Community Mapping. Observation reveals patterns that people may not report in interviews: how spaces are actually used, who is present and who is absent, what informal rules govern behavior, and what barriers exist in practice.

Structured observation uses a predefined checklist or protocol. A walkability audit is a form of structured observation: the researcher walks a route and documents presence or absence of sidewalks, crosswalks, lighting, benches, and other features. The protocol ensures consistency and comparability across sites.

Unstructured observation is more open-ended. The researcher spends time in a place, takes notes on what they see, and lets patterns emerge. Unstructured observation is useful early in a project, when you are still figuring out what matters. Over time, patterns you notice through unstructured observation can inform the design of more structured tools.

Good observation requires patience and humility. Sit in the park. Watch the bus stop. Stand at the community center entrance. Notice who arrives, when, how they interact, and what they do. Notice what is missing: the ramp that should be there but isn't, the bench that would make waiting easier, the lighting that would make the path feel safer.

Thick description is the standard for high-quality observation (Geertz, 1973). Thin description says: "Three youth sat on the steps." Thick description says: "Three youth, roughly 14 to 16 years old, sat on the concrete steps outside the closed community center, using the steps as a gathering place because no other seating existed in the area. They spoke in a mix of English and another language I did not recognize. One held a phone; the others leaned in to look at the screen. When an adult passed, they went quiet until the adult moved on." Thick description captures context, meaning, and social dynamics, not just surface facts.

Observation also requires ethical awareness. You are watching people in public space, but that does not mean they have consented to being studied. In many research ethics frameworks, public observation without interaction is considered low-risk and does not require individual consent — but norms vary by discipline and jurisdiction. Be transparent when possible. If you are conducting a walkability audit, wear identification or inform the community in advance. Do not photograph or record individuals without permission.

Finally, observation has limits. You see what is visible. You may miss what happens at night if you only observe during the day. You may miss gendered or racialized experiences if your own identity grants you access and safety that others do not have. Observation should be triangulated with interviews, focus groups, or community diaries to validate and deepen findings.

21.4 Oral Histories

Oral histories are structured, recorded interviews that document personal memory, lived experience, and historical knowledge. In Community Mapping, oral histories capture what official records miss: how places have changed, what events shaped the community, who the informal leaders were, and what cultural practices have been sustained or lost.

Oral history work is distinct from general interviewing. It typically involves longer conversations (one to three hours, sometimes multiple sessions), deeper rapport-building, and a focus on memory and meaning. The goal is not just to collect information, but to preserve voice, honor experience, and create a record for future generations.

Indigenous oral histories carry particular ethical and epistemological weight. Oral traditions are not "data sources" to be mined by outsiders. They are living protocols, governed by community laws about who can speak, what can be shared, and how knowledge must be transmitted. Oral histories involving Indigenous knowledge require community consent, co-governance, and adherence to OCAP principles (Ownership, Control, Access, and Possession) as articulated by the First Nations Information Governance Centre. Knowledge shared orally may not be appropriate for written publication, digital storage, or public distribution. Respect community authority over the knowledge they share. If you do not have the relationships, permissions, and cultural competence to conduct Indigenous oral history work ethically, do not do it (Tuhiwai Smith, 1999).

For all oral histories, informed consent is paramount. Participants must understand how the recording will be used, stored, and shared. Will it be archived? Transcribed? Made public? Will their name be attached, or will they remain anonymous? These decisions belong to the participant, not the researcher.

Oral histories are time-intensive. A two-hour interview may take eight to ten hours to transcribe, and many more hours to analyze and archive. But the richness of the data justifies the effort. Oral histories produce narratives, not just answers. They reveal how people make sense of their lives, what they care about, and how memory and identity are bound to place.

When mapping oral histories spatially, handle location data carefully. A participant may describe a place that holds cultural or emotional significance but should not be marked on a public map — a hidden gathering place, a sacred site, or a location associated with trauma. Always ask: Should this be mapped? Who will see this map? What harm could result?

21.5 Photo Documentation

Photographs are a powerful form of qualitative data. They document physical conditions, reveal details that memory or description may miss, and serve as prompts for conversation and analysis. In Community Mapping, photo documentation is used to capture infrastructure conditions, land use patterns, accessibility barriers, environmental hazards, and the visual character of place.

Photo documentation can be researcher-led (the project team takes photos) or participatory (community members are given cameras or phones and asked to document what matters to them). Participatory photo documentation — sometimes called photovoice — shifts power. Participants decide what is photographed, how it is framed, and what story the image tells.

Ethics are non-negotiable. Consent, ownership, and veto rights must be established before any photo is taken or published. People in public spaces still have a right to privacy and dignity. Photographing someone without permission and publishing that image can cause harm — especially for vulnerable populations. A photograph of someone accessing a food bank, living in an encampment, or experiencing homelessness can expose them to stigma, surveillance, or retaliation.

Children require special care. In most jurisdictions, photographing minors in research contexts requires parental or guardian consent. Even with consent, consider whether the image could be used in ways that harm the child in the future.

Cultural and sacred spaces also require care. Some Indigenous communities prohibit photography of ceremonies, sites, or objects. Some religious sites have restrictions. Always ask before photographing, and honour refusals.

Metadata matters. Every photo should be documented with date, time, location, and a brief description of what is shown and why it matters. Without metadata, a photo is just an image — with metadata, it becomes evidence.

Finally, consider storage and access. Who owns the photos? Where will they be stored? Who can access them? If photos are stored in a cloud service controlled by the research team, participants have no control over their own images. Best practice: participants retain ownership, and the research team uses images only with ongoing, informed consent.

21.6 Video Documentation

Video documentation captures motion, sound, interaction, and process in ways that still images and text cannot. In Community Mapping, video can document walking tours, community meetings, interviews, environmental conditions, and dynamic patterns like traffic flow or gathering behavior.

Video is more intrusive than photos. A camera recording video attracts attention, changes behavior, and feels more like surveillance. This raises the ethical bar. Informed consent is required from everyone who appears in the video or whose voice is recorded. In public spaces where large numbers of people pass through, obtaining individual consent from everyone may be impossible — in those cases, do not use video, or film in ways that avoid capturing identifiable faces.

Editing introduces interpretive power. A two-hour community meeting can be edited into a five-minute video, but who decides what makes the cut? What voices are amplified? What dissent is erased? Editing is not neutral. Involve participants in reviewing and approving the final edit when possible. If that is not feasible, establish editorial principles in advance: Will you prioritize majority views or ensure dissenting voices are included? Will you focus on positive stories or also show conflict and struggle?

Video also creates long-term data management challenges. Video files are large, require significant storage, and are harder to anonymize than text. Faces, voices, and identifying details are embedded in the footage. If a participant later withdraws consent, redacting their presence from video is technically difficult or impossible. This is another reason why up-front consent processes must be clear, voluntary, and well-documented.

Used well, video can be a powerful tool for storytelling, education, and advocacy. A video showing the distance a senior must walk to reach the nearest bus stop — including the steep hill, the lack of sidewalk, and the dangerous road crossing — can move decision-makers in ways a written report cannot. But that power comes with responsibility. The video must represent the senior's experience accurately, must be shared with their consent, and must not reduce them to a symbol for someone else's agenda.

21.7 Field Notes

Field notes are the researcher's running record of observation, reflection, and analysis during fieldwork. They are not polished writing. They are raw, detailed, honest documentation of what you saw, heard, thought, and wondered about while in the field.

Good field notes capture multiple layers. Descriptive notes document observable facts: "At 3:00 PM on a Tuesday, six people were waiting at the bus stop. No seating. No shelter. Temperature approximately 2°C." Reflective notes capture your interpretations and questions: "The lack of seating may be a barrier for seniors or people with mobility challenges. I wonder if ridership is lower in winter because waiting outside is unpleasant." Methodological notes document decisions and challenges: "I planned to observe for an hour, but it started raining after 20 minutes and I had to leave. I will return tomorrow at the same time."

Write field notes as soon as possible after observation. Memory fades quickly. Details you think you will remember — the exact words someone used, the order of events, the tone of an interaction — disappear within hours. Carry a notebook or use a phone to capture quick notes in real time, then expand them into full field notes the same day.

Field notes are not objective. They are filtered through your perspective, shaped by what you notice and what you miss, influenced by your assumptions and biases. Acknowledge this. If you are a young, white, able-bodied researcher observing a low-income neighborhood, your field notes will reflect your positionality. You may feel safe in a place where others do not. You may overlook barriers you do not personally experience. Reflective practice means naming your standpoint and recognizing its limits.

Field notes are also confidential. Do not include people's real names or identifying details unless you have explicit permission. Use pseudonyms or codes. Store field notes securely. Treat them as the private, protected data they are.

Over time, patterns emerge from field notes. You notice the same issue recurring in multiple locations, or the same story being told by different people. These patterns guide analysis. Field notes are not just a record of what happened — they are a tool for thinking.

21.8 Community Diaries

Community diaries are a participatory method where residents document their own experiences over time — daily, weekly, or in response to prompts. Participants might record where they go, what barriers they face, what they observe, or how they use space. Diaries can be text-based, photo-based, voice-recorded, or multimodal.

Diaries shift the burden of observation from the researcher to the participant. Instead of a researcher observing a bus stop once, a participant records their experience every time they use it — over a week, a month, or longer. This produces longitudinal data that captures variation, patterns, and lived reality in ways that one-time observation cannot.

Diaries are particularly valuable for understanding experiences that are time-sensitive, private, or difficult for outsiders to access. A senior's experience navigating healthcare appointments across the city. A parent's daily route to drop off children, go to work, and pick up groceries. A youth's perception of which streets feel safe at different times of day. These are not experiences a researcher can observe easily — but a diary can capture them.

The challenge is participant burden. Keeping a diary requires time, literacy, and motivation. Compensation is essential — and not just at the end. Consider providing small weekly payments or incentives to sustain engagement. Make the task manageable: a five-minute daily voice memo is easier than an hour of writing. Provide clear prompts to guide entries but leave room for participants to share what matters to them.

Diaries also require clear ethical agreements. Who owns the diary? Can participants share personal or sensitive information that they later regret? Build in check-ins where participants can review their entries, redact content, or withdraw. Treat diaries as living documents, not fixed data.

When analyzing diaries, look for both individual patterns and cross-case themes. One participant's diary shows their unique experience. Ten participants' diaries reveal shared barriers, common workarounds, and systemic patterns. Diaries are inherently subjective — that is their strength. They give you insight into lived experience, not objective truth.

21.9 Participatory Research

Participatory research treats community members as co-researchers, not data sources. Participants help define the research question, design the methods, collect data, interpret findings, and decide how results are used. This approach is rooted in principles of equity, justice, and community empowerment. It recognizes that those who live in a place are experts on that place — and that extractive research, where outsiders take data and leave, perpetuates harm.

Participatory research in Community Mapping takes many forms. A participatory asset mapping project might involve residents identifying assets, drawing maps, validating findings, and presenting results to decision-makers. A participatory photovoice project might train community members to document barriers, facilitate group discussions about the photos, and create an advocacy campaign. A participatory walking audit might pair residents with researchers to co-observe, co-interpret, and co-recommend changes.

The distinguishing feature is shared power. Researchers do not control the process — the community does, or at the very least, decisions are made collaboratively. This requires researchers to let go of traditional expert authority, acknowledge what they do not know, and trust community knowledge.

Participatory research is slower and messier than extractive research. Decisions take longer when they are made collectively. Data collection is less standardized when community members bring different approaches. Analysis requires negotiation when interpretations diverge. But the trade-off is worth it. Participatory research produces findings that are more accurate (because they are grounded in local knowledge), more legitimate (because the community validates them), and more actionable (because the community is invested in using them).

Compensation and capacity-building are non-negotiable. Community members who serve as co-researchers are doing skilled labor. Pay them fairly. Provide training in research methods, data collection, and ethics. Create opportunities for skill development that participants can use beyond this project.

Finally, participatory research requires accountability. If residents invest time and energy in research, they deserve to see results. Share findings in accessible formats. Follow through on commitments. If the research leads to recommendations, support the community in advocating for them. Participatory research is not a one-time transaction — it is the beginning of a relationship.

21.10 Coding and Thematic Analysis

Qualitative data — transcripts, field notes, photos, diaries — is rich but unstructured. Coding and thematic analysis are systematic methods for organizing, interpreting, and drawing meaning from qualitative data.

Coding is the process of labeling segments of data with descriptive tags. A transcript from an interview about food access might be coded with labels like "transportation barrier," "cost," "store quality," "informal food sources," "community support," and "seasonal variation." Codes can be deductive (predetermined based on the research question) or inductive (emerging from the data itself). Most Community Mapping projects use a mix: start with a few broad codes based on what you expect to find, then add new codes as unexpected themes emerge.

Coding is interpretive work. Two researchers coding the same transcript may assign different codes, because they notice different things or interpret meaning differently. This is why inter-rater reliability matters. In team-based research, multiple coders work on the same data, then compare and discuss their coding. Disagreements are not failures — they are opportunities to refine definitions, clarify codes, or acknowledge that the data supports multiple interpretations.

After coding, the next step is thematic analysis: grouping codes into broader themes, identifying patterns across the dataset, and interpreting what the themes mean. A theme is not just a topic — it is an idea or pattern that captures something significant about the data in relation to the research question. For example, individual codes like "long travel time," "no bus route," and "car required" might be grouped into a theme: "Spatial barriers to food access."

Grounded theory is one influential approach to thematic analysis (Strauss & Corbin, 1998). It emphasizes building theory from the data itself, rather than testing pre-existing hypotheses. Researchers code data, write memos about emerging patterns, and iteratively refine categories until a coherent framework emerges. Grounded theory is rigorous but time-intensive — it works best when you have substantial qualitative data and the time to engage in deep, iterative analysis.

Member checking strengthens thematic analysis. Share your themes and interpretations with participants. Do they recognize their experience in your analysis? Do they disagree with your interpretation? Do they see patterns you missed? Member checking is not about getting participants to "approve" your findings — it is about ensuring that your interpretation is grounded in their reality.

Software tools like NVivo, Atlas.ti, and Dedoose support qualitative analysis by helping researchers organize codes, visualize patterns, and track analytic decisions. These tools do not do the thinking for you — coding and theming still require human judgment — but they make managing large datasets more feasible.

One caution: coding can fragment data. A single interview, when broken into coded segments, loses its narrative coherence. Balance coding with holistic reading. Return to full transcripts or field notes regularly to remember the context and the person behind the codes.

21.11 Synthesis and Implications

Qualitative data methods — interviews, focus groups, observation, oral histories, photo and video documentation, field notes, community diaries, participatory research, and thematic analysis — give Community Mapping its human voice. They answer the questions that spatial data and census figures cannot: What does this place mean? How do people experience barriers? What stories shape identity? What relationships sustain community life?

Effective Community Mapping integrates qualitative data with quantitative and spatial analysis. A map showing food deserts is more powerful when paired with resident interviews about the real barriers they face: the store that technically exists but sells expired food, the bus route that runs infrequently, the cultural disconnect between available food and what people actually eat. A service ecosystem map gains depth when paired with focus group discussions about how referrals actually work, where people get stuck, and what informal supports fill the gaps.

Qualitative data is not a supplement to "real" data. It is real data. It requires rigor, transparency, and ethical care. A poorly conducted interview produces misleading information. A badly facilitated focus group silences dissent. An unethical photo documentation process causes harm. Qualitative research is not easier or less rigorous than quantitative work — it is differently rigorous.

Community Mapping grounded in qualitative data is more accurate, more accountable, and more useful. It respects lived experience. It centers community voice. It acknowledges complexity and contradiction. It makes space for stories that do not fit neatly into databases or GIS layers. It treats people as experts on their own lives.

The practical implications for Community Mapping practitioners are clear. Learn qualitative methods. Practice them. Budget time and resources for them. Train community members to use them. Triangulate qualitative findings with spatial and numeric data. Share findings in ways that honour the voices of those who shared their stories. Use qualitative data not just to describe the world, but to change it.

21.12 Interview Guide Assignment

Purpose: Develop a semi-structured interview guide for a Community Mapping project that gathers lived experience, identifies barriers and assets, and produces data that can be spatially referenced and integrated with other data sources.

Materials Needed:

Research question or focus area for your Community Mapping project
Pen and paper or digital document
Example interview guides from community research projects (if available)

Steps:

Define your focus. What aspect of community life are you mapping? (Examples: food access, healthcare navigation, youth recreation, seniors' social connection, accessibility barriers, cultural assets.) Write a 2-3 sentence description of the project goal.
Identify your participants. Who has the lived experience you need to understand? Be specific about who you will recruit and why their perspective matters.
Develop your questions. Write 8-12 open-ended interview questions organized into sections:
- Introduction/rapport-building (1-2 questions): Easy, non-threatening questions to build trust. Example: "How long have you lived in this neighborhood?"
- Experience and practice (4-6 questions): Questions about what people do, where they go, what barriers they face. Example: "Where do you usually shop for groceries? How do you get there?"
- Meaning and perspective (2-3 questions): Questions about what matters, what needs to change, what works well. Example: "What would make it easier for you to access fresh food?"
- Spatial context (1-2 questions): Questions that elicit specific locations or spatial patterns. Example: "Can you describe the route you take to get there? Are there places along the way that feel unsafe or difficult to navigate?"
Include prompts. For each main question, write 2-3 follow-up prompts that you can use if the participant needs more guidance. Example: Main question: "What barriers do you face?" Prompts: "Are there times of day or year that are harder?" "Are there costs or transportation issues?" "Are there cultural or language barriers?"
Plan for consent and closure. Draft an introductory script that explains the project, how data will be used, and what protections are in place. Draft a closing script that thanks the participant, explains next steps, and provides contact information if they have follow-up questions or concerns.
Review for ethics and bias. Read through your guide and ask: Are any questions leading or judgmental? Are any questions too personal for an initial interview? Are any questions phrased in ways that assume the participant has certain experiences or identities? Revise as needed.

Deliverable: A 2-3 page interview guide with sections, questions, prompts, and introductory/closing scripts. Include a 1-paragraph reflection on what you learned from designing the guide and what challenges you anticipate in conducting the interviews.

Time Estimate: 90-120 minutes

Safety and Ethics Notes: Do not pilot your interview guide on vulnerable populations without ethics review. If your interview guide asks about sensitive topics (trauma, violence, stigmatized experiences), consult with a research ethics advisor or experienced community researcher before proceeding. Always prioritize participant safety and dignity over data collection.

Key Takeaways

Qualitative data captures lived experience, meaning, and context that quantitative data cannot.
Interviews, focus groups, observation, oral histories, photo and video documentation, field notes, and community diaries each serve distinct purposes and require distinct ethical care.
Indigenous oral histories are governed by community protocols, not researcher agendas; OCAP principles must guide all work involving Indigenous knowledge.
Photo and video documentation require informed consent, respect for privacy and dignity, and community control over images.
Participatory research treats community members as co-researchers, not data sources, and requires shared power, fair compensation, and accountability.
Coding and thematic analysis are systematic methods for interpreting qualitative data, requiring rigour, transparency, and often, member checking to validate findings.

Plain-Language Summary

Qualitative data methods are ways of gathering and understanding people's stories, experiences, and perspectives — not just numbers. In Community Mapping, this means interviewing residents, running group discussions, observing how places are used, recording oral histories, taking photos or videos, and working with community members as research partners.

These methods help answer the "why" questions: Why is food access hard? Why do people avoid certain streets? Why does this place matter? Numbers can show where services are missing, but stories show what it feels like to face those gaps every day.

Doing this work well requires care. You need people's permission to interview them, photograph them, or record their stories. You need to protect their privacy, honour their knowledge, and share findings in ways they can use. And you need to listen — really listen — to what people are telling you, even when it challenges your assumptions.

When qualitative data is combined with maps, census data, and other information, you get a fuller picture of how communities work and what they need. The stories give meaning to the numbers, and the numbers give weight to the stories.

End of Chapter 21.

Chapter 21. Qualitative Data Methods