Figure Designer

Heritage and scope

This is an original Open Science Skills workflow for figure production in social-science manuscripts. It is general — apply to any figure type (line, bar, point, density, map, network, small multiples). For figures whose interpretation depends on method-specific standards, also consult the relevant sibling skill (conjoint-design, conjoint-diagnostics, list-experiment, topic-modeling, text-classification, vlm-ocr-pipeline). For end-stage QA on a finished figure set, hand off to figure-table-audit.

A good figure earns its place in the manuscript: it makes a single comparison legible, it can be read without the surrounding text, and it can be regenerated from a script. If a figure cannot do all three, it is not yet ready.

Instructions

1. State the comparison before drawing

Write down, in one sentence, what the figure is supposed to let the reader see. Examples:

• "Treatment effect is larger among low-information respondents than among high-information respondents."
• "Vote share for Party A declines monotonically with district urbanization."
• "Topic 7 prevalence rises sharply after the 2024 election."

If you cannot state the comparison in one sentence, the figure has too many goals — split it into multiple panels or multiple figures.

2. Choose the chart type from the comparison

Match the geometry to the comparison, not to the data type:

• Comparing magnitudes across a small number of categories: bar chart (or dot/lollipop for many categories).
• Tracking a quantity over a continuous variable: line chart for ordered/continuous x; point + ribbon for uncertainty.
• Showing distribution: histogram (single), density (compare a few), boxplot/violin (compare many).
• Showing relationship between two continuous variables: scatter, with trend line + uncertainty band if a model is implied.