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Data from: Deep learning four decades of human migration: datasets
zenodo.org
csv, nc
Updated Oct 13, 2025
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Thomas Gaskin; Thomas Gaskin; Guy Abel; Guy Abel (2025). Deep learning four decades of human migration: datasets [Dataset]. http://doi.org/10.5281/zenodo.17344747
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csv, ncAvailable download formats
Unique identifier
https://doi.org/10.5281/zenodo.17344747
Dataset updated
Oct 13, 2025
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Thomas Gaskin; Thomas Gaskin; Guy Abel; Guy Abel
License
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Description
This Zenodo repository contains all migration flow estimates associated with the paper "Deep learning four decades of human migration." Evaluation code, training data, trained neural networks, and smaller flow datasets are available in the main GitHub repository, which also provides detailed instructions on data sourcing. Due to file size limits, the larger datasets are archived here.

Data is available in both NetCDF (.nc) and CSV (.csv) formats. The NetCDF format is more compact and pre-indexed, making it suitable for large files. In Python, datasets can be opened as xarray.Dataset objects, enabling coordinate-based data selection.

Each dataset uses the following coordinate conventions:

Year: 1990–2023

Birth ISO: Country of birth (UN ISO3)

Origin ISO: Country of origin (UN ISO3)

Destination ISO: Destination country (UN ISO3)

Country ISO: Used for net migration data (UN ISO3)

The following data files are provided:

T.nc: Full table of flows disaggregated by country of birth. Dimensions: Year, Birth ISO, Origin ISO, Destination ISO

flows.nc: Total origin-destination flows (equivalent to T summed over Birth ISO). Dimensions: Year, Origin ISO, Destination ISO

net_migration.nc: Net migration data by country. Dimensions: Year, Country ISO

stocks.nc: Stock estimates for each country pair. Dimensions: Year, Origin ISO (corresponding to Birth ISO), Destination ISO

test_flows.nc: Flow estimates on a randomly selected set of test edges, used for model validation

Additionally, two CSV files are provided for convenience:

mig_unilateral.csv: Unilateral migration estimates per country, comprising:

imm: Total immigration flows

emi: Total emigration flows

net: Net migration

imm_pop: Total immigrant population (non-native-born)

emi_pop: Total emigrant population (living abroad)

mig_bilateral.csv: Bilateral flow data, comprising:

mig_prev: Total origin-destination flows

mig_brth: Total birth-destination flows, where Origin ISO reflects place of birth

Each dataset includes a mean variable (mean estimate) and a std variable (standard deviation of the estimate).

An ISO3 conversion table is also provided.
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Cite

Thomas Gaskin; Thomas Gaskin; Guy Abel; Guy Abel (2025). Deep learning four decades of human migration: datasets [Dataset]. http://doi.org/10.5281/zenodo.17344747

Data from: Deep learning four decades of human migration: datasets

Explore at:

csv, ncAvailable download formats

Unique identifier

https://doi.org/10.5281/zenodo.17344747

Dataset updated

Oct 13, 2025

Dataset provided by

Zenodohttp://zenodo.org/

Authors

Thomas Gaskin; Thomas Gaskin; Guy Abel; Guy Abel

License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This Zenodo repository contains all migration flow estimates associated with the paper "Deep learning four decades of human migration." Evaluation code, training data, trained neural networks, and smaller flow datasets are available in the main GitHub repository, which also provides detailed instructions on data sourcing. Due to file size limits, the larger datasets are archived here.

Data is available in both NetCDF (.nc) and CSV (.csv) formats. The NetCDF format is more compact and pre-indexed, making it suitable for large files. In Python, datasets can be opened as xarray.Dataset objects, enabling coordinate-based data selection.

Each dataset uses the following coordinate conventions:

Year: 1990–2023
Birth ISO: Country of birth (UN ISO3)
Origin ISO: Country of origin (UN ISO3)
Destination ISO: Destination country (UN ISO3)
Country ISO: Used for net migration data (UN ISO3)

The following data files are provided:

T.nc: Full table of flows disaggregated by country of birth. Dimensions: Year, Birth ISO, Origin ISO, Destination ISO
flows.nc: Total origin-destination flows (equivalent to T summed over Birth ISO). Dimensions: Year, Origin ISO, Destination ISO
net_migration.nc: Net migration data by country. Dimensions: Year, Country ISO
stocks.nc: Stock estimates for each country pair. Dimensions: Year, Origin ISO (corresponding to Birth ISO), Destination ISO
test_flows.nc: Flow estimates on a randomly selected set of test edges, used for model validation

Additionally, two CSV files are provided for convenience:

mig_unilateral.csv: Unilateral migration estimates per country, comprising:
- imm: Total immigration flows
- emi: Total emigration flows
- net: Net migration
- imm_pop: Total immigrant population (non-native-born)
- emi_pop: Total emigrant population (living abroad)
mig_bilateral.csv: Bilateral flow data, comprising:
- mig_prev: Total origin-destination flows
- mig_brth: Total birth-destination flows, where Origin ISO reflects place of birth

Each dataset includes a mean variable (mean estimate) and a std variable (standard deviation of the estimate).

An ISO3 conversion table is also provided.

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