PopAtlas is based on publicly available international datasets collected from multiple authoritative organizations. Each data source serves a specific role within the project and contributes to different analytical layers.

United Nations — Population Division

The primary source of population and demographic data in PopAtlas is the United Nations Population Division, mainly through the World Population Prospects (WPP) dataset.

These data provide internationally comparable estimates of population size, age structure, fertility, mortality, and population growth.

UN World Population Prospects (WPP)

WPP datasets include both historical estimates and future projections. In PopAtlas, WPP data is used for population totals, demographic indicators, and long-term trends.

Population projections represent modeled scenarios and should be interpreted as estimates rather than exact forecasts.

Pew Research Center — Religious composition

Data on religious composition is primarily based on datasets published by the Pew Research Center, including global estimates for 2010 and 2020.

These datasets provide country-level percentages of major religious groups. Religious data in PopAtlas reflects proportional composition rather than exact counts.

It is important to note that religious data is not updated annually and may lag behind current conditions. Newer releases may be incorporated as they become available.

Languages — ISO 639-3

Language reference data is derived from the ISO 639-3 standard, maintained by SIL International.

This dataset provides standardized language identifiers and serves as a structural reference for language-related data across the project.

Geographic indicators — World Bank

Geographic indicators such as land area are sourced from the World Bank through its public API.

These data complement demographic information by providing spatial context at the country level.

Data integration and limitations

Different sources vary in methodology, coverage, update frequency, and level of detail. PopAtlas integrates these datasets into a unified structure to support comparative and exploratory analysis.

Missing or incomplete data reflects limitations of the original sources and does not imply zero values.

All data sources are documented and maintained in an internal data inventory and may be updated as new releases become available.