Synthetic Data for an Imaginary Country, Full Population, 2023
A synthetic hierarchical dataset for simulation and training purposes
World, 2023
Get MicrodataCreated on
Jul 03, 2023
Last modified
Jul 03, 2023
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Identification
Survey ID Number
WLD_2023_SYNTH-CEN-EN_v01_M
Title
Synthetic Data for an Imaginary Country, Full Population, 2023
Subtitle
A synthetic hierarchical dataset for simulation and training purposes
Country/Economy
| Name | Country code |
|---|---|
| World | WLD |
Study type
Synthetic data
Series Information
This dataset is part of a collection of fully synthetic data generated, for training and simulation purposes, for an imaginary middle-income country. The dataset is available in English and French. A subset of 8,000 households is also available in English and French as a "synthetic survey dataset".
Abstract
The dataset is a relational dataset of 10,003,891 individuals (2,501,755 households), representing the entire population of an imaginary middle-income country. The dataset contains two data files: one with variables at the household level, the other one with variables at the individual level. It includes variables that are typically collected in population censuses (demography, education, occupation, dwelling characteristics, fertility, mortality, and migration) and in household surveys (household expenditure, anthropometric data for children, assets ownership). The data only includes ordinary households (no community households). The dataset was created using REaLTabFormer, a model that leverages deep learning methods. The dataset was created for the purpose of training and simulation and is not intended to be representative of any specific country.
A sample dataset of 8000 households was created out of this full-population dataset, and is also distributed as open data.
A sample dataset of 8000 households was created out of this full-population dataset, and is also distributed as open data.
Kind of Data
cen
Unit of Analysis
household, Individual
Version
Version Description
V. 2023-05-01 10M PP EN
Version Date
2023-05-01
Version Notes
Dataset generated using RealTabFormer (with 10,003,891 individuals and 2,501,755 households), with post-processing. English version.
Scope
Notes
The dataset is a synthetic dataset generated using a model that used data from IPUMS International, from the Demographic and Health Survey program, and from the World Bank Global Consumption Database (microdata) as training data. The detailed list of datasets used to create the training datasets is available in the Technical Documentation (document provided as an external resource).
Keywords
| Keyword |
|---|
| synthetic data |
| open data |
| safe data |
| demographics |
| education |
| mortality |
| fertility |
| child malnutrition |
| labor, employment |
| housing |
| dwelling |
| water and sanitation |
| household expenditure |
| migration |
Coverage
Geographic Coverage
The dataset is a synthetic dataset for an imaginary country. It was created to represent the full national population of this country, by province and district (equivalent to admin1 and admin2 levels) and by urban/rural areas of residence.
Geographic Unit
province (admin1), district (admin2)
Universe
The dataset is a fully-synthetic dataset representative of the resident population of ordinary households for an imaginary middle-income country.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Development Data Group, Data Analytics Unit | World Bank |
Funding Agency/Sponsor
| Grant number | Role | Name | Abbreviation |
|---|---|---|---|
| KP-P174174-TF0B5124 | Sponsored research work for the development of synthetic data for the purpose of assessing statistical disclosure risk measures. | UNHCR-World Bank Joint Data Center on Forced Displacement | JDC |
Sampling
Weighting
The dataset is the equivalent of a census dataset. No weighting applies.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2023 | 2023 |
Time periods
| Start date | End date |
|---|---|
| 2023 | 2023 |
Data Collection Mode
other
Questionnaires
Questionnaires
The dataset is a synthetic dataset. Although the variables it contains are variables typically collected from sample surveys or population censuses, no questionnaire is available for this dataset. A "fake" questionnaire was however created for the sample dataset extracted from this dataset, to be used as training material.
Data Processing
Data Editing
The synthetic data generation process included a set of "validators" (consistency checks, based on which synthetic observation were assessed and rejected/replaced when needed). Also, some post-processing was applied to the data to result in the distributed data files.
Access policy
Restrictions
The dataset was generated as a fully-synthetic dataset. The model used to create the synthetic observations includes multiple procedures to avoid overfitting and data-copying. Also, the data used for training the model went through processes of sampling and recoding that make it impossible to link a synthetic observation to an actual observation. The dataset is thus safe for dissemination. It can be used with no restriction and is shared as open data.
Access authority
| Name |
|---|
| World Bank, Microdata Library |
Location of Data Collection
World Bank Microdata Library
Disclaimer and copyrights
Disclaimer
The data are to be used for training or simulation purposes only. It is not intended to be representative of any particular country, and should not be used for inference purpose.
Metadata production
Producers
| Name | Affiliation |
|---|---|
| OD | World Bank |
Date of Metadata Production
2023-05-01
DDI Document version
1.0 EN