Why Are Figures, Tables, and Data Important in Peer Review?

Figures and tables are not merely visual additions to a research article. They represent the evidence on which scientific interpretations are based.

A peer reviewer should evaluate whether:

• Figures accurately represent the results described in the manuscript.
• Tables present numerical information clearly and consistently.
• Statistical analyses are appropriate for the study design.
• Data interpretation is supported by the presented evidence.
• Images and graphical materials maintain scientific integrity.
• The results are sufficiently transparent for readers to understand the research findings.

A discrepancy between the written results and the displayed data may affect the interpretation of the entire study.

Therefore, critical evaluation of research data is an essential part of responsible peer review.

1. How to Review Scientific Figures

Scientific figures may include photographs, graphs, microscopy images, diagnostic images, flowcharts, diagrams, and experimental illustrations.

When reviewing figures, the reviewer should assess both scientific accuracy and presentation quality.

A. Check Figure Relevance

Each figure should contribute meaningful information to the research question.

Ask:

• Does the figure directly support the study objectives?
• Is it necessary for understanding the findings?
• Does it provide information that is not already adequately presented elsewhere?
• Is the figure appropriately referenced in the manuscript?

Figures that do not contribute to the scientific interpretation may require revision or removal.

B. Evaluate Image Quality and Clarity

Figures should be sufficiently clear for accurate interpretation.

Reviewers should examine:

• Image resolution and readability.
• Axis labels and measurement units.
• Legends, annotations, and symbols.
• Scale bars in microscopy or imaging studies.
• Appropriate labeling of experimental groups.
• Consistency in figure formatting.

Poor-quality figures can make otherwise valid results difficult to evaluate.

C. Examine Image Integrity

Image integrity is particularly important in biomedical and experimental research.

Reviewers should look for potential concerns such as:

• Apparent duplication of images presented as different experimental results.
• Inconsistent backgrounds or unexpected image boundaries.
• Unexplained alterations to image contrast or brightness.
• Repeated image regions that appear inconsistent with the stated experiments.
• Missing controls or unclear image labeling.

Not every visual irregularity indicates misconduct. Reviewers should distinguish legitimate image processing from potentially inappropriate manipulation and request clarification when necessary.

Authors should disclose image processing where required and preserve the integrity of the original data.

2. How to Evaluate Research Tables

Tables help readers examine detailed numerical findings, comparisons, measurements, and statistical outcomes.

A reviewer should assess whether the table is accurate, complete, and understandable without requiring excessive interpretation from the surrounding text.

A. Verify Numerical Consistency

Compare the values in the tables with those reported in the Results section.

Check for:

• Differences between table values and manuscript text.
• Incorrect totals or percentages.
• Inconsistent sample sizes.
• Missing observations.
• Inconsistent decimal places.
• Incorrect units or measurement labels.

For example, if the manuscript reports 120 participants but a table accounts for only 115, the reviewer should request an explanation of the discrepancy.

B. Check Table Titles and Footnotes

A well-prepared table should contain:

• A descriptive title.
• Clearly identified rows and columns.
• Appropriate measurement units.
• Definitions of abbreviations.
• Explanations of statistical symbols.
• Relevant notes about missing data or analytical methods.

Statistical abbreviations such as SD, SE, CI, and p-values should be clearly explained where necessary.

C. Assess Data Presentation

Reviewers should consider whether the selected format is appropriate.

For example:

• Descriptive statistics should be clearly identified.
• Comparisons should use consistent categories.
• Percentages should have appropriate denominators.
• Tables should avoid unnecessary duplication of information already presented in figures.

The purpose is to improve clarity without changing the scientific meaning of the results.

3. Evaluating Statistical Data and Results

Statistical evaluation is one of the most important aspects of reviewing quantitative research.

A reviewer does not necessarily need to repeat every analysis, but should determine whether the statistical methods and reported findings are appropriate for the research question and study design.

A. Examine Statistical Methods

Consider whether:

• The statistical tests are appropriate for the data.
• The sample size and study design are adequately described.
• Assumptions of the selected statistical methods are addressed where relevant.
• The treatment of missing data is explained.
• The methods used for subgroup analyses are justified.
• Multiple comparisons are appropriately considered.

If the statistical approach is unclear or potentially unsuitable, the reviewer should explain the concern and request clarification or additional analysis.

B. Check P-Values and Confidence Intervals

Reviewers should examine whether reported statistical results are complete and consistently presented.

Where applicable, assess:

• Exact p-values rather than only threshold statements.
• Confidence intervals.
• Effect sizes.
• Measures of variability.
• Appropriate statistical notation.

A statistically significant result does not automatically indicate a clinically meaningful or practically important effect.

C. Evaluate Whether Conclusions Match the Data

One common concern in research manuscripts is overinterpretation.

For example, an observational association should not automatically be presented as proof of causation.

Reviewers should ask:

• Are the conclusions directly supported by the results?
• Are limitations acknowledged?
• Are causal claims justified by the study design?
• Are findings generalized beyond the studied population?
• Are uncertain results presented cautiously?

The discussion and conclusion should accurately reflect the strength and limitations of the evidence.

4. Cross-Check Figures, Tables, and Manuscript Text

An effective peer reviewer should not evaluate each component independently.

The figures, tables, abstract, Results section, and conclusions should present a consistent account of the research findings.

A systematic cross-check can identify:

This cross-check is especially useful for identifying reporting errors before publication.

5. Identifying Potential Data Integrity Concerns

Peer reviewers play an important role in protecting the reliability of scientific literature.

Potential warning signs may include:

• Repeated or apparently duplicated data.
• Inconsistent sample sizes across sections.
• Unexplained numerical discrepancies.
• Figures that do not correspond to the described methods.
• Inappropriate statistical interpretation.
• Missing information needed to understand the reported findings.
• Unexplained image modifications.

However, reviewers should avoid making unsupported allegations of research misconduct.

When concerns arise, they should document the specific observation and communicate it confidentially to the editor. The editorial team can then request original data, clarification, or further assessment as appropriate.

6. How to Write Constructive Reviewer Comments

Identifying an issue is only part of the review process. Reviewers should explain the concern clearly and suggest a reasonable way to address it.

Example 1: Figure Clarity