Effective Date: August 22, 2026

At VizAtlas, data is at the heart of what we do.

Our articles, maps, rankings, infographics, charts, comparisons, and visual stories frequently rely on statistics and information published by governments, international organizations, research institutions, academic sources, and other reputable organizations.

This page explains where our information comes from, how we select and process data, how we create rankings and visualizations, and how we communicate uncertainty and limitations.

Our objective is simple:

Make complex information easier to understand while preserving the context necessary to understand it correctly.

1. Our Approach to Data

VizAtlas generally follows five principles when working with data:

1. Source First

We aim to identify the underlying source of important statistics rather than relying solely on secondary summaries.

2. Verify Before Publishing

Important figures are reviewed against their underlying sources wherever reasonably possible.

3. Preserve Context

A number without its definition, date, unit, or methodology can be misleading. We therefore aim to provide relevant context alongside important statistics.

4. Explain Our Calculations

When VizAtlas performs calculations or creates an original ranking, we aim to explain the methodology sufficiently for readers to understand how the result was produced.

5. Acknowledge Limitations

No dataset is perfect. Where methodological limitations could materially affect interpretation, we aim to identify them.

2. Primary Sources

Whenever practical, VizAtlas prioritizes primary and authoritative sources.

These may include:

National statistical agencies;
Government ministries and departments;
Central banks;
International organizations;
Intergovernmental organizations;
Academic institutions;
Peer-reviewed research;
Official regulatory bodies;
Research institutions; and
Original datasets.

Examples include:

World Bank;
International Monetary Fund;
United Nations;
World Health Organization;
OECD;
UNESCO;
International Labour Organization;
International Energy Agency;
International Monetary Fund;
World Trade Organization;
Food and Agriculture Organization;
UN agencies;
National statistical offices; and
Government data portals.

The appropriate source depends on the subject being analyzed.

3. Secondary Sources

Primary sources are not always available or sufficient.

When necessary, VizAtlas may use reputable secondary sources such as:

Academic publications;
Research institutions;
Established statistical databases;
Industry research;
Reputable news organizations;
Specialized publications; and
Expert analysis.

Secondary sources may be used to provide context, identify relevant research, explain complex subjects, or supplement primary data.

When secondary sources are used, we aim to evaluate their credibility and, where possible, trace important claims back to the original source.

4. Source Selection

When selecting between multiple sources, we generally consider:

Authority

Who produced the information?

Methodology

How was the information collected or calculated?

Recency

How current is the information?

Geographic Coverage

Does the dataset cover the countries or regions being compared?

Consistency

Are the definitions and measurement methods comparable?

Transparency

Does the source explain how the data was produced?

Revision History

Does the source revise or update its data over time?

A newer source is not automatically a better source if its methodology is less appropriate for the question being analyzed.

5. Data Years and Reference Periods

The year shown in a VizAtlas infographic or ranking may refer to different concepts depending on the underlying dataset.

For example, it may represent:

The year the data was collected;
The year the statistic refers to;
The year the dataset was published;
The year of an index edition;
A financial year; or
A multi-year period.

We aim to clearly identify the relevant reference year or period whenever it materially affects interpretation.

Readers should not assume that the publication date of an article is necessarily the year represented by the data.

6. Data Revisions

Official statistics are frequently revised.

A dataset may change because of:

New information;
Improved surveys;
Revised estimates;
Updated methodologies;
Population censuses;
Changes in geographic boundaries;
Statistical corrections; or
Reclassification of data.

As a result, a figure published by VizAtlas today may differ from a figure previously published for the same indicator.

Where significant revisions affect an existing article or visualization, we may update the relevant content.

7. Different Definitions

Comparisons between countries or regions can be complicated because apparently similar indicators may use different definitions.

For example:

Unemployment may be measured differently;
Poverty thresholds may differ;
GDP estimates may use different methodologies;
Population figures may be estimates rather than censuses;
Internet access may be defined differently;
Forest coverage may use different classifications.

Where differences in definitions materially affect a comparison, VizAtlas aims to identify them rather than presenting the figures as perfectly equivalent.

8. Units and Conversions

Data may originally be published in different:

Currencies;
Units of measurement;
Time periods;
Population bases; or
Statistical formats.

Where necessary, VizAtlas may convert data into a common unit to make comparisons easier.

Conversions may involve:

Currency conversion;
Percentage calculations;
Per-capita calculations;
Unit conversion;
Inflation adjustments;
Purchasing-power adjustments; or
Other standard transformations.

The original source and relevant methodology should be considered when interpreting converted values.

9. Currency Conversions

When comparing economic figures across countries, VizAtlas may use different approaches depending on the purpose of the comparison.

These may include:

Current exchange rates;
Constant exchange rates;
Purchasing power parity (PPP);
Local-currency values; or
Other standardized measures.

These methods answer different questions.

For example, nominal GDP converted using market exchange rates is not directly equivalent to GDP measured using purchasing power parity.

Where the distinction is important, VizAtlas aims to identify the methodology used.

10. Per-Capita Calculations

Some VizAtlas comparisons use per-capita measures.

A simplified calculation may be:

Total Value ÷ Population = Per-Capita Value

However, the population figure and reference period must correspond appropriately to the underlying dataset.

Per-capita statistics should not automatically be interpreted as describing the actual income, wealth, or experience of every individual.

11. Percentages and Growth Rates

VizAtlas may calculate:

Percentage changes;
Growth rates;
Shares;
Ratios;
Compound annual growth rates;
Differences between periods; and
Other derived indicators.

Unless otherwise specified, percentage changes generally compare the relevant values between two defined periods.

Where a calculation is particularly important to the conclusion of an article, we aim to explain the calculation or provide sufficient information for readers to reproduce it.

12. Rankings

VizAtlas publishes both:

External Rankings

Rankings produced by another organization or institution.

These are presented as the ranking of the original publisher.

VizAtlas Rankings

Rankings independently calculated by VizAtlas using selected datasets and criteria.

These are clearly distinguished from external indexes.

A VizAtlas ranking should not be interpreted as an official ranking unless the underlying source itself is an official ranking.

13. Creating VizAtlas Rankings

When creating an original ranking, the methodology may include:

Selecting indicators;
Identifying appropriate datasets;
Establishing the geographic scope;
Cleaning and standardizing data;
Handling missing values;
Normalizing indicators where necessary;
Applying weights where appropriate;
Calculating individual scores;
Combining scores into an overall score; and
Ranking entities according to the resulting values.

The exact process may vary between indexes.

The methodology used for each original index should be explained in the relevant article or dedicated methodology page.

14. Scoring and Normalization

When different indicators use different units, VizAtlas may normalize them before combining them into a composite score.

For example, one indicator may be measured in:

Dollars;
Percentages;
Years;
Kilometers; or
Per-capita units.

Normalization can place these different indicators onto a comparable scale.

Depending on the index, methods may include:

Min-max normalization;
Standardization;
Ranking-based scoring;
Percentile scoring; or
Other appropriate statistical methods.

The method selected depends on the purpose and characteristics of the index.

15. Weighting

Some VizAtlas indexes may assign different weights to different indicators.

For example:

Indicator A = 40%
Indicator B = 30%
Indicator C = 20%
Indicator D = 10%

The final score would then reflect the selected weighting system.

Where weighting is used, VizAtlas aims to disclose the weights and explain why they were selected.

A weighting system represents an analytical choice and may influence the final ranking.

16. Missing Data

Not every country or region has complete data for every indicator.

When data is missing, VizAtlas may:

Exclude the entity from a particular calculation;
Use an appropriate alternative dataset;
Use a documented estimation method; or
Clearly identify the limitation.

We do not intentionally create false precision by presenting unavailable information as if it were directly observed.

Where missing data materially affects a ranking, this limitation should be disclosed.

17. Estimates and Modeled Data

Some datasets are based on estimates or statistical models rather than direct measurements.

Examples may include:

Population estimates;
Economic forecasts;
Climate projections;
Poverty estimates;
Agricultural estimates;
Historical reconstructions; and
Other modeled datasets.

VizAtlas aims to distinguish estimates and projections from directly observed data when that distinction is important.

18. Maps and Geographic Data

VizAtlas maps may use geographic information from:

Government sources;
International organizations;
Open geographic datasets;
Licensed datasets;
Research institutions; and
Other lawful sources.

Maps may be simplified for visual communication.

A map’s boundaries, labels, colors, or geographic presentation should not automatically be interpreted as a legal or political position.

For disputed territories or boundaries, the relevant source and context should be considered.

19. Infographics and Visualizations

VizAtlas uses visual storytelling to make complex data easier to understand.

Our visualizations may include:

Bar charts;
Line charts;
Maps;
Choropleth maps;
Ranking tables;
Bubble charts;
Timelines;
Flow diagrams;
Geographic comparisons; and
Other visual formats.

We aim to ensure that visual design does not intentionally distort the underlying information.

Where appropriate, visualizations should identify:

Units;
Time period;
Source;
Geographic scope; and
Relevant definitions.

20. Data Visualization Choices

Visual choices can influence how information is perceived.

VizAtlas therefore aims to use appropriate:

Scales;
Axes;
Color systems;
Legends;
Labels;
Sorting methods; and
Data classifications.

In some cases, a visualization may intentionally focus on a particular range or subset of data for clarity.

Where such choices could materially change interpretation, we aim to provide sufficient context.

21. AI-Assisted Research and Production

VizAtlas may use artificial-intelligence tools during content production.

AI may assist with:

Research;
Brainstorming;
Drafting;
Summarization;
Data organization;
Editing;
Visualization planning; and
Other production tasks.

However:

AI output is not treated as a primary source.

AI-generated claims, statistics, references, and interpretations may contain errors.

Important information is therefore intended to be checked against appropriate underlying sources before publication.

Where an AI tool provides a useful lead, VizAtlas aims to verify the underlying information independently rather than treating the AI response itself as evidence.

22. Editorial Review

Data-driven content may undergo review for:

Factual accuracy;
Source quality;
Calculations;
Definitions;
Dates;
Units;
Rankings;
Visual accuracy;
Internal consistency; and
Clarity.

The level of review may vary depending on the complexity and significance of the content.

23. Corrections and Updates

If we discover that published data or methodology contains a material error, we may:

Correct the article;
Update the infographic;
Revise calculations;
Replace incorrect figures;
Add clarification;
Update the methodology; or
Publish a correction.

Readers can report potential errors through the Submit a Correction page.

Corrections are evaluated based on available evidence and the underlying source material.

24. Sources on Individual Articles

Where practical, VizAtlas aims to provide relevant sources directly within individual articles and data visualizations.

Depending on the format, sources may appear:

Beneath an infographic;
At the end of an article;
In a methodology section;
In a source note;
Through a linked citation; or
On a dedicated methodology page.

The source should be interpreted alongside the relevant reference year and methodology.

25. Source Attribution

When using third-party data, VizAtlas aims to identify the relevant source.

Source attribution does not necessarily imply endorsement by the source organization.

Similarly, the appearance of an organization, country, company, institution, or dataset in a VizAtlas article does not imply that the organization has reviewed, approved, or endorsed the article.

26. Conflicting Sources

Different reputable sources may sometimes report different figures.

When this occurs, VizAtlas may consider:

Publication date;
Methodology;
Geographic scope;
Reference period;
Data revisions;
Definition of the indicator; and
Authority of the source.

Where the difference is significant enough to affect the conclusion, we may acknowledge the discrepancy rather than selecting a number without explanation.

27. Limitations of Cross-Country Comparisons

Global comparisons are inherently imperfect.

Countries may differ in:

Statistical capacity;
Data collection methods;
Definitions;
Population structures;
Geographic characteristics;
Economic systems;
Reporting standards; and
Availability of information.

A cross-country ranking therefore provides a structured comparison based on selected indicators rather than a complete representation of reality.

28. Reproducibility

For original VizAtlas calculations, we aim to provide enough methodological information for readers to understand the basic process used to produce the result.

Where appropriate, this may include:

Source datasets;
Formulae;
Variables;
Weights;
Reference periods;
Definitions; and
Important assumptions.

Not every calculation will be identical across all VizAtlas projects.

The methodology of a specific index or ranking takes precedence over this general methodology page where the two differ.

29. Changes to Methodology

Data methodologies may evolve.

VizAtlas may change:

Data sources;
Indicators;
Weightings;
Calculations;
Geographic coverage;
Normalization methods; or
Other methodological components.

When a significant methodology change occurs, we aim to identify it in the relevant project or article.

As a result, rankings from different editions may not always be directly comparable.

30. Data Integrity and Editorial Responsibility

VizAtlas aims to treat data as evidence rather than decoration.

We do not intend to manipulate statistics, selectively remove relevant context, or intentionally create misleading visualizations.

At the same time, every dataset involves choices about definitions, measurement, presentation, and interpretation.

Our responsibility is therefore not only to show numbers, but also to provide enough context for readers to understand what those numbers actually mean.

31. Important Limitation

Although VizAtlas strives for accuracy and transparency, we cannot guarantee that every dataset, calculation, visualization, or published figure will always be free from error.

Readers should consult the original source when precise, current, or authoritative information is required.

Where a source has subsequently revised its data, VizAtlas may not immediately reflect every revision.

32. Our Methodological Commitment

Our goal is to make data understandable without making it misleading.

We aim to:

Use credible sources.
Verify important information.
Explain our calculations.
Disclose meaningful limitations.
Distinguish fact from analysis.
Correct significant errors.
Keep methodologies transparent.

As VizAtlas grows, this methodology will evolve alongside the complexity of our data projects.

Contact

If you have questions about a source, calculation, ranking, visualization, or methodology used by VizAtlas, please contact us through our Contact Us page.

Potential factual or data errors can be reported through our Submit a Correction page.

Topic and research suggestions can be submitted through our Suggest a Topic page.

Website: VizAtlas.org

Last Updated: August 21, 2026