Deep learning four decades of human migration: datasets

Gaskin, T. & Abel, G. ORCID: https://orcid.org/0000-0002-4893-5687 (2025). Deep learning four decades of human migration: datasets. 10.5281/zenodo.17344747.

Full text not available from this repository.

Abstract

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.

Item Type:	Data
Additional Information:	Creative Commons Attribution 4.0 International
Research Programs:	Population and Just Societies (POPJUS) Population and Just Societies (POPJUS) > Migration and Sustainable Development (MIG)
Depositing User:	Luke Kirwan
Date Deposited:	09 Jan 2026 10:12
Last Modified:	09 Jan 2026 10:12
URI:	https://pure.iiasa.ac.at/21182

Actions (login required)

View Item