Datasets:
Data used as input, training targets, and validation
This folder 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.
This is a reminder that all data is stored in this repository using git LFS (large file storage); if you wish to clone the repository with the data, you should follow the instructions from the main README. You can still download the files manually from the webpage.
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.
Conflict deaths (UCDP_data)
This folder contains data on deaths in conflict provided by UCDP Georeferenced Event dataset. NaN values are filled with 0.