| --- |
| license: gpl-3.0 |
| language: |
| - en |
| pretty_name: 'Deep learning four decades of human migration: datasets' |
| tags: |
| - arXiv:2506.22821 |
| --- |
| Deep learning four decades of human migration: datasets |
| --- |
|
|
| This repository contains all migration flow estimates associated with the paper [_"Deep learning four decades of human migration."_](https://arxiv.org/abs/2506.22821) Evaluation code, training data, trained neural networks, and smaller flow datasets are available in the [main GitHub repository](https://github.com/ThGaskin/Migration_flows), which also provides detailed instructions on data sourcing. Due to file size limits, the larger datasets are archived here. |
| The repository contains three folders: |
|
|
| # Estimates |
| This folder contains all the migration estimates. 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`](https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html) 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 |
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|
| 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). |
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| An ISO3 conversion table is also provided. |
|
|
| # Data |
| The `Data` contains all the data used to train, evaluate, and test the neural network. |
| It is stored thematically in different folders, and most folders again contains its own `README` file to further |
| explain the specific sources and imputation methods. All data is given *both* as a `.csv` file and a `.nc` file, and |
| follows the ISO3-naming convention outlined in the main README. |
|
|
| ## Training_data |
| This folder contains all the tensors used to train the neural network. All data is given as a PyTorch |
| tensor (`.pt`) and can be loaded using `torch.load()`. The folder contains targets, weights, masks, input covariates (scaled |
| and unscaled), and the edge indices of each input. See the folder README for further details. |
| |
| ## Net migration (`Net_migration`) |
| This folder contains net migration data, sourced from national statistical offices, together with a list of sources |
| and the UN WPP net migration figures. |
|
|
| ## GDP indicators (`GDP_data`) |
| This folder contains data on GDP/capita, GDP growth, nominal GDP, and other GDP-related indicators for all countries and |
| years included in the training period. |
| |
| ## Gravity covariates (`Gravity_datasets`) |
|
|
| ## Demographic indicators (`UN_WPP_data`) |
|
|
| ## Migrant stocks (`UN_stock_data`) |
|
|
| ## Refugee figures (`UNHCR_data`) |
| Total number of refugees, asylum-seekers, and other people in need of international protection, taken from the |
| [UNHCR dataset](https://www.unhcr.org/refugee-statistics/download). |
| |
| ## Conflict deaths (`UCDP_data`) |
| This folder contains data on deaths in conflict provided by |
| [UCDP Georeferenced Event](https://ucdp.uu.se/downloads/index.html#ged_global) dataset. |
| NaN values are filled with 0. |
|
|
| ## Bilateral flows (`Flow_data`) |
| |
| # Trained networks |
| Contains the ensemble of trained neural networks |
