A map can make a public-data question look simple: shade each district by a number, then compare the colors. But a figure about schools, roads, population, or flood impacts only means something when its geography, date, and definition are clear.
Match the boundary first
Check whether a dataset reports at the province, district, subdistrict, or village level. A provincial total cannot explain conditions in an individual community, and a district figure can hide substantial variation within its boundary. Before comparing two maps, confirm that they use the same administrative units.
Read the date and definition
A count of classrooms is not the same as a measure of school access, just as a record of flood events is not a measure of every household affected. Look for the original dataset’s definition, collection period, and publication date. If those details are missing, mark the comparison as limited instead of presenting it as a clean trend.
Compare with care
For questions about infrastructure or recovery, place the data beside the relevant project records or local reporting, and keep the source links close to the chart. That helps readers distinguish a documented change from an interpretation of why it happened. A useful map does not merely show where a number is high or low; it makes clear what the number can and cannot tell us.