Skills Data Science Scientific Figure Rigor and Submission Guide

Scientific Figure Rigor and Submission Guide

v20260724
sci-figures
Provides comprehensive guidelines for designing high-impact scientific figures for major academic journals. It covers technical aspects like optimal sizing, font legibility, and colorblind safety, while also enforcing strict data visualization practices (e.g., using dot plots over bars, defining 'n', ensuring data integrity). Use this as a final quality check before submission to guarantee scientific rigor and maximize publication chances.
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Overview

Display Items (sci-figures)

When to trigger

  • Figure count exceeds the format budget (Report ≤4, Article ≤6).
  • Fonts are unreadable at print size, or colors are not colorblind-safe.
  • Bar charts hide the underlying data (no points, no n).
  • Panels are screenshots of software output pasted into the figure.

Sizing for Science columns

Design figures to render at final print width without rescaling text:

  • 1 column ≈ 5.5 cm wide
  • 2 columns ≈ 12 cm wide
  • Full page ≈ 18 cm wide
  • Minimum font in the final figure: ~6 pt (sans-serif, e.g., Helvetica/Arial). Text must stay legible after reduction.
  • Line weights ≥ 0.5 pt; avoid hairlines that vanish in print.

Show the data, not just the summary

  • Replace bar-of-means with dot plots / box+points / violins+points wherever n is small.
  • Always state n (and what n is: cells? animals? independent experiments?) in the legend.
  • Error bars must be defined in the legend (SD vs SEM vs 95% CI) — never undefined.
  • For images (blots, micrographs): show scale bars, and present full, uncropped key blots in Supplementary.

Color and accessibility

  • Use a colorblind-safe palette (avoid red/green as the only contrast).
  • Don't encode meaning by color alone — add shape/pattern/labels.
  • RGB color mode for online; ensure adequate contrast in grayscale.
  • No rainbow/jet colormaps for continuous data — use perceptually uniform maps (viridis, etc.).

Figure legend structure

Each legend: a short title sentence (the claim of the figure), then per-panel descriptions (A, B, C…), then statistics (test, n, error-bar definition, P values or exact values). The legend should let the figure stand alone.

Integrity rules (non-negotiable)

  • No selective deletion, splicing, or beautification of gels/blots/images without a labeled boundary; disclose any grouping.
  • Quantitative comparisons must come from the same experiment/exposure.
  • Keep unprocessed source images and source data — Science may request them (sci-data).

Multi-panel discipline

  • ≤ ~6 panels per figure; if more, split or move to Supplementary.
  • Consistent axis scales across comparable panels.
  • One message per figure; the legend title states it.

Figure pass for Science

Use this as a second-pass capability check. First lock the broad discovery claim, decisive evidence, uncertainty/limitations, and why the result belongs in a general-science weekly; then test whether the manuscript addresses general-science reviewers and editors who ask whether the result changes a broad field, is technically decisive, and can be understood outside the subdiscipline.

  • Primary move: Make each figure prove one claim for a broad reader: object, contrast, uncertainty, scale, and failure or limitation should be visible.
  • Decision ledger: return claim / evidence / blocker / next edit rows so the next pass can patch the manuscript directly.
  • Neighbor test: compare against Nature for similar broad-scope novelty, PNAS for academy-wide breadth, specialist journals when the claim is field-internal; if the neighboring outlet has the stronger audience claim, recommend re-routing before polishing.
  • Verification floor: before submission-ready advice, re-open resources/official-source-map.md for volatile rules and name the one unresolved fact that could change the recommendation.

Output format

【Item count】 N (budget: Report ≤4 / Article ≤6) → ok / over
【Sizing】 designed at 5.5 / 12 / 18 cm? fonts ≥6 pt? yes/no
【Data shown】 points + n + defined error bars? yes/no
【Colorblind-safe】 yes/no (palette used)
【Integrity】 scale bars / uncropped blots in SM / source data kept? yes/no
【Fixes】 [...]
【Next】 sci-statistics

Anti-patterns

  • Do not paste raw Stata/Prism/ImageJ screenshots as figures.
  • Do not use bars to hide n=3 with huge spread — show the points.
  • Do not leave error bars undefined or mix SD and SEM across panels.
  • Do not rely on red-vs-green as the sole encoding.
Info
Category Data Science
Name sci-figures
Version v20260724
Size 4.23KB
Updated At 2026-07-29
Language