Proposal Figures

---
name: proposal-figures
description: Designing grant proposal figures — conceptual models, preliminary-data displays, and schematics that sell the science.
category: scientific
---

## Overview

Grant figures do different work than paper figures: they must convey the
idea, the evidence, and the plan to a tired reviewer in seconds. This
skill covers the three figure types every proposal needs (the conceptual
model, preliminary data, the experimental schema), designing for
skim-reading, and the visual honesty standards reviewers apply.

## When to use

- Planning figures for a grant proposal (before writing the text)
- Designing a conceptual/model figure that makes the hypothesis visual
- Presenting preliminary data for maximum credibility in minimum space
- Drawing experimental timelines and workflow schematics
- Fixing proposal figures that are too dense, too small, or confusing

## Core concepts

- **Three essential figures:** (1) the conceptual model — the hypothesis as a diagram; (2) preliminary data — proof you can do it; (3) the experimental schema — the plan as a flowchart. Every proposal needs all three; most weak proposals lack at least one.
- **Skim-first design:** reviewers look at figures before reading text — each figure must be interpretable standalone, with a legend/caption that states the takeaway.
- **The model figure's job:** turn the central hypothesis into a visual — boxes, arrows, and causal relationships. If you can't draw it, you don't understand it well enough to propose it.
- **Preliminary data curation:** show the single most convincing result per aim — one clean, well-labeled panel beats four cramped ones; error bars, n, and statistics included (reviewers check).
- **Schema clarity:** experimental plans as flowcharts with decision points ("if X, then Y; if not-X, then Z") — shows you've thought through contingencies, which is what the Approach score rewards.
- **Visual honesty:** no cherry-picked blots without replicates noted, no exaggerated effect sizes via truncated axes, no "representative image" that isn't representative — reviewers are primed to distrust.

- **The conceptual figure:** a single diagram showing the hypothesis — the system's components, the intervention, the predicted outcome — this figure does more persuasive work than any data panel.
- **Preliminary data triage:** show the minimum convincing evidence per aim — one clean, well-controlled result beats four cramped panels; reviewers equate clutter with desperation.
- **Timeline as figure:** a Gantt-style timeline showing aims, milestones, and decision points across the funding period — feasibility made visual; missing timelines read as missing planning.

## Practical workflow

### 1. Plan figures before text

1. Sketch all three essential figures on paper first — they become the proposal's skeleton; write text around them.
2. Allocate space deliberately: the model figure gets prominence (often page 1 of the Strategy); preliminary data integrated into each aim's rationale.
3. Storyboard the sequence: model → "we've already shown" (prelim) → "we will do" (schema) — repeated per aim.

### 2. Design the conceptual model figure

1. Show the system, the perturbation, and the predicted outcome — cause and effect visually explicit.
2. Use consistent visual grammar: same shapes for same entity types, arrow styles for activation vs inhibition (define them).
3. Label everything a non-specialist needs; move specialist detail to the caption.
4. Test: cover the caption — can a colleague state your hypothesis from the figure alone?

### 3. Present preliminary data

1. One key result per aim, shown at a size that's actually readable (no 6-panel micrographs shrunk to postage stamps).
2. Include the controls that make it convincing — a result without its control is a claim, not evidence.
3. Annotate directly on the figure: arrows to the key feature, p-values, effect sizes — don't make reviewers hunt.
4. State what's preliminary vs published (cite your own published work; label unpublished clearly).

### 4. Draw the experimental schema

1. Flowchart each aim: inputs → methods → readouts → decision points → contingencies.
2. Include timelines where relevant (Gantt-style for multi-year plans) — feasibility is visual.
3. Keep it high-level: the schema shows logic, not protocols — methods detail belongs in text.

### 5. Polish for the venue

1. Color: readable in both color and grayscale (many reviewers print); colorblind-safe palettes.
2. Fonts: ≥8 pt at final size; consistent with the proposal's typography.
3. Captions: each figure gets a caption stating what it shows and the takeaway — captions are read; use them.

### 5. Design figures for tired reviewers

1. Make every figure interpretable in 15 seconds: clear title, labeled axes, the takeaway in the caption's first sentence.
2. Use consistent visual language across figures — same colors for the same conditions, same symbols for the same groups; inconsistency forces relearning.
3. Test at print size and in grayscale — reviewers print, project, and skim; figures must survive all three.

## Common pitfalls

- **Missing model figure:** describing a complex hypothesis in text alone — if the idea needs a paragraph to explain, it needs a diagram.
- **Data dumping:** cramming every preliminary experiment into tiny panels — curate ruthlessly; one convincing result beats five marginal ones.
- **Unreadable figures:** shrunk to fit, 5 pt labels, cryptic abbreviations — a figure no one can read is worse than no figure.
- **Schema as decoration:** a flowchart that doesn't show decisions or contingencies — reviewers score the thinking, not the boxes.
- **Dishonest visuals:** selective cropping, missing controls, exaggerated scales — destroys credibility instantly when spotted.
- **Figure–text divorce:** figures never referenced in the narrative, or referenced out of order — integrate: "As shown in Figure 2...".
- **Data figures without controls:** a striking result with no control panel invites the obvious reviewer question — include the control or explain its absence.
- **Figure–text mismatch:** figures referenced out of order or never referenced — integrate figures into the narrative flow; orphaned figures get ignored.