Labs / Chapter 13
Chapter 13 turns thematic mapping into an explicit design trial. Students learn to ask not “How should this map look?” but “What kind of representational claim is this method allowed to make?”
Chapter 13 argues that thematic method selection is a representational decision, not a styling preference. This lab teaches you to match data structure, phenomenon, and communication goal to a thematic method while naming the method’s predictable distortions.
Use a dataset you know, a public dataset description, or a hypothetical dataset. You do not need GIS software; the work is method reasoning and prompt specification.
Dataset description Phenomenon: Data fields and units: Geometry: point / line / polygon / origin-destination / raster Data type: raw count / rate / category / ordinal / continuous / movement Collection method: Spatial resolution: Temporal resolution, if any: Communication goal: Audience: What the map must not imply:
Analyze this dataset description. Distinguish the real-world phenomenon from the data collected about it. Identify whether the phenomenon is discrete or continuous, abrupt or smooth. Then identify whether the data representation is discrete or continuous, abrupt or smooth. Explain any mismatch and why it matters for thematic mapping. Dataset description: [PASTE]
| Question | Answer | Mapping consequence |
|---|---|---|
| Phenomenon nature | Example: The pattern shifted east | Example: Use small multiples |
| Data nature | Example: The pattern shifted east | Example: Use small multiples |
Starter examples only; expand this in your own notes or submission document.
Recommend three thematic representation methods for this dataset and communication goal. Consider choropleth, proportional symbols, graduated symbols, dot map, heat map, hexbin/grid aggregation, isarithmic map, flow map, cartogram, multivariate map, linked views, or small multiples. For each method, explain why it fits, what it reveals, what it hides, and the default lie it carries. Dataset and goal: [PASTE]
Choose the most tempting but inappropriate method for this dataset. Put it on trial. Explain what false impression it would create, which data property it violates, which audience expectation it exploits, and what harm could result if it were published.
Write a detailed thematic method specification for the best method. Include: - method and justification - data field and units - classification or scaling approach, if applicable - projection requirement, if applicable - color or symbol encoding - legend requirements - tooltip content - uncertainty or limitation note - interaction or reference view needed - default lie and guardrail - what method alternatives were rejected and why Write this as a professional specification.
Choose the choice most relevant to your selected method: choropleth classification, proportional symbol scaling, heat-map smoothing/binning, isarithmic interpolation, flow filtering, cartogram distortion, or multivariate load.
Generate three design variants for my selected thematic method by changing the key representation decision. For each variant, explain what story it emphasizes, what it obscures, and whether it supports my communication goal. Selected method specification: [PASTE] Decision to vary: classification / scaling / smoothing / interpolation / filtering / distortion / multivariate load
| Variant | Story emphasized | Story obscured | Risk | Verdict |
|---|---|---|---|---|
| 1 | Example: Short note | Example: Short note | Example: Could overstate certainty | Example: Keep if explained |
| 2 | Example: Short note | Example: Short note | Example: Could overstate certainty | Example: Keep if explained |
| 3 | Example: Short note | Example: Short note | Example: Could overstate certainty | Example: Keep if explained |
Starter examples only; expand this in your own notes or submission document.
Add structural guardrails to this thematic map. Consider cautionary language, reference toggles, raw-value tooltips, standard map toggles, data collection point overlays, uncertainty layers, classification notes, smoothing parameters, or layer filters. Explain where each guardrail should appear and how it reduces overconfidence.
Compile my work into a production-ready thematic map prompt. Include data description, method selection with justification, rejected methods, classification/scaling/aggregation choices, palette or symbol rules, projection requirements, legend requirements, tooltip content, guardrails, accessibility requirements, and a self-check asking the assistant to identify the method’s default lie before implementation.
And once more, ad nauseam, with feeling: the prompt is not the judgment.
Do the tiny-but-mighty judgment check. If these answers are fuzzy, revise the map idea before polishing the prompt.
For use with Prompt Cartography: Interactive Web Map Design with LLMs, CRC Press. www.promptcartography.com
Prompt Cartography