Population dataset by administrative boundaries

Example: Population count data aggregated by administrative units (e.g., districts, municipalities) from census surveys or estimates.

Step-by-step guidance

1. Dataset-level metadata

Select the following values when describing your dataset:

  • Risk data type: exposure

  • Title: “Population data for [region]”

  • Description: Brief description of the population data source, survey year, and aggregation level

  • Publisher: National statistical office or organization providing the data

  • License: Appropriate license

2. Resources

Add resources for your population data files:

  • Format: csv, shapefile, geopackage, or geojson

  • Spatial resolution: Administrative level (e.g., ADMIN2, ADMIN3)

  • Coordinate reference system: EPSG:4326 (if spatial) or not applicable for tabular data

3. Exposure metadata

Under the Exposure section:

Category

  • Category: population

Metrics

Define what is being measured:

Metric 1 - Population count:

  • Dimension: population

  • Quantity kind: count

  • Unit: people or 1 (dimensionless count)

Metric 2 - Population density (optional):

  • Dimension: population

  • Quantity kind: density

  • Unit: people/km2

Temporal information

  • Reference year: Year of census or population estimate

  • Projection scenario (if applicable): Baseline, SSP scenarios, etc.

4. Spatial coverage

Define the geographic extent:

  • Scale: national or sub-national

  • Countries: Select applicable ISO 3166-1 alpha-3 country codes

  • Administrative regions: Specify the administrative level (e.g., provinces, districts, municipalities)

  • Gazetteer entries: Link to administrative unit identifiers

Example data structure

Your population dataset should include:

  • Administrative unit ID/code

  • Administrative unit name

  • Geometry (polygon) or link to spatial boundaries

  • Total population count

  • Disaggregation by age groups (optional)

  • Disaggregation by gender (optional)

  • Urban/rural classification (optional)

Key considerations

  • Clearly specify the reference year for population data

  • Document the source of data (census, survey, model estimate)

  • Include information about disaggregation (age, gender) if available

  • For projected populations, specify the scenario and methodology

  • Link to official administrative boundary codes where possible (e.g., ISO 3166-2)