Name: UNESCO Institute of Statistics (UIS)
Creator: World Bank Group
Published: 2025-08-04

The BOOST initiative is a Bank-wide collaborative effort launched in 2010 to facilitate access to budget data and promote effective use for improved decision-making processes, transparency and accountability.

BOOST - Public Expenditure Database

This collection contains datasets that may be useful for analysis, response or modelling for the Coronavirus (COVID-19) pandemic.

Coronavirus (COVID-19) Related Datasets

The Data360 initiative aims to integrate high-value data and knowledge curated in the Bank’s verticals into a user-centered data platform. 

Data 360

The Development Data Partnership platform facilitates formation of public-private partnerships for solving development challenges with technology. Specifically, the Development Data Partnership Working Group organizes opportunities for WBG staff to work with technology companies who offer pro-bono data and resources.

Development Data Partnership

This collection contains discrepancy indexes for UN COMTRADE data that aims to capture both the frequency of missed reporting and its impact on overall recorded trade value

Discrepancy Index

A collection of datasets produced through partnership between the World Bank and the European Space Agency (ESA) Earth Observation for Sustainable Development (EO4SD) initiative.

Earth Observation for Sustainable Development

Open data and analytics for a sustainable energy future.

Energy Data Info

This collection features datasets to support building policies, institutions and investments for inclusive and sustainable growth.

Equitable Growth, Finance and Institutions

Project Page: https://worldbank.github.io/GEEST/README.html 

As part of the “Geospatial Assessment of Women Employment and Business Opportunities in the Energy Sector” project, open-source Gender-related spatial data was collected for 31 Small Island Developing States (SIDS) across the globe, resulting in curated and thoroughly documented geodatabases (GDBs) that are now ready to be explored! 
Fifty-nine spatial layers were identified and then researched for each country, covering the following categories: Demographics and Population | Renewable Energy | Energy Access | Education | Jobs and Finance | Digital Inclusion | Transportation | Safety | Amenities | Climate/Earth | Law/Policy/Government. 


However, not every country GDB contains all 59 data layers, as this was dependent on the availability of open-source data in each SIDS. Users are encouraged to check the accompanying metadata excel file for more information on the datasets in each GDB, the vintage, and the

Gender Spatial Data - Small Island States

A collection of datasets that contain geospatial data. These datasets have one or more resources in a geospatial data format.

Geospatial Datasets

Collection of useful datasets from IMF made available to Bank staff via <a href=http://mydatabank.worldbank.org>myDataBank</a>

IMF Dataset

A collection of datasets to help finance the global infrastructure gap.

Infrastructure Finance Datasets

Data and dataset subscriptions managed by the Library Network on agriculture, business, economics, energy, finance, health, risk, water, and more..

Library Databases

The LinkedIn-World Bank partnership offers data to help governments and researchers understand rapidly evolving labor markets with detailed and dynamic data. It allows leaders to benchmark and compare labor markets across the world; analyze skills, occupations, migration, and industries; and leverage real-time data to make policy changes.Visualizations for many of these data are available at <a href=https://linkedindata.worldbank.org/>linkedindata.worldbank.org</a>

LinkedIn Data for Development

Collection of merchandise trade data available to World Bank staff.

Merchandise Trade Data

This collection includes datasets associated with research organized under the Bank, <a href=http://prwp.worldbank.org target='_blank' title='Opens in a new window'>Policy Research Working Papers</a>.

Policy Research Working Papers

This collection contains data on disaster and climate risk assessments curated by the Global Facility for Disaster Reduction and Recovery (GFDRR).

Risk Data Library

This collection presents software tools and models developed by the World Bank to support monitoring, planning, programming and the economic evaluation of roads and highways works.

Road Software Tools

This spatial database, a product of the South Asia Region Chief Economist's (SARCE) Office, presents data collected from official sources and harmonized into different spatial levels. Data includes economic and environmental data across 12 topic areas, and includes data from four countries in South Asia (Bangladesh, Bhutan, India, and Nepal) for both 2001 and 2011.

SARCE Spatial Database

A collection of country Small Area Estimation (SAE) and Poverty Mapping that contains papers, shapefiles, and datasets produced through partnerships between the World Bank and country statistics offices.

Small area estimates / Poverty mapping

This collection consists of datasets compiled and created by the World Bank Data Lab in response to a request by the Syria Economic Monitor Team to explore alternative data sources to better understand changing trends in trade and economic activity, focusing on: surface cross-border transport routes, changes in observed agricultural production, observed nighttime lights, and reported conflict.

Syria Economic Monitor

A collection of relevant datasets to support operations in Ukraine.

Ukraine datasets

Catalogue lists all the data produced under the partnership contracts between the World Bank Group and the European Space Agency

World Bank (WBG) - European Space Agency (ESA) Database

A collection of datasets to help achieve universal access to reliable and fast internet services for all.

World Bank Digital Development Data

A collection of datasets to help achieve sustainable energy for all.

World Bank Energy Datasets

A collection of datasets to help achieve sustainable mobility for all.

World Bank Transport Data

From Data to a Water-Secure World for All. World Bank Water Data surrounding the three pillars of Sustain Water Resources, Deliver Services and Build Resilience.

World Bank Water Data

The World Development Report 2021: Data for Better Lives explores the tremendous potential of the changing data landscape to improve the lives of poor people, while also acknowledging its potential to open back doors that can harm individuals, businesses, and societies. To address this tension between the helpful and harmful potential of data, this Report calls for a new social contract that enables the use and reuse of data to create economic and social value, ensures equitable access to that value, and fosters trust that data will not be misused in harmful ways. The data used in the WDR2021 are curated as a collection here.

World Development Report 2021

The World Development Report 2022: Finance for an Equitable Recovery examines the central role of finance in the economic recovery from the COVID-19 pandemic. In doing so, it looks into the consequences of the crisis most likely to affect emerging economies and proposes a set of policies to mitigate the interconnected financial risks stemming from the pandemic and to steer economies toward a sustainable and equitable recovery. The data used in the WDR2022 are curated as a collection here.

World Development Report 2022

The World Settlement Footprint Collection includes country datasets describing the evolution of the built-area across the globe at a ~30m resolution.

World Settlement Footprint

R scripts for accessing UIS API

This file provides the mapping between UIS indicator codes and EdStats/WDI indicator codes. It is required to run the script "fetch.uis_stat.data.R".

Mapping file between UIS and EdStats/WDI indicator codes (QS file)

Mapping file between UIS and EdStats/WDI country codes (QS file)

Mapping file between UIS and WB aggregation (regional/income) codes (QS file)

The UIS data and footnotes as of Sep 22 2025.   

Notes on accessing UIS API

World

Education dataset disseminated by the UNESCO Institute of Statistics (UIS)

English

Education Indicators from UNESCO Institute of Statistics (UIS)

UNESCO Institute of Statistics (UIS)

Education

People - Education Global

Gross enrolment ratio for tertiary education, male (%)

Educational attainment rate, completed post-secondary non-tertiary education or higher, population 25+ years, both sexes (%)

Educational attainment rate, completed upper secondary education or higher, population 25+ years, male (%)

Out-of-school rate for children of primary school age, female (%)

Proportion of teachers with the minimum required qualifications in secondary education, female (%)

Gross enrolment ratio for tertiary education, female (%)

Survival rate to Grade 5 of primary education, both sexes (%)

The folder contains the data and footnotes downloaded from UIS for the WDI May 2024 update. Please refer to the accompanying Word document for an explanation.

UIS data for WDI (May 2024)

Dataset: Sustainable Development Goal 4Release date: 2024-02Data extracted on: 2024-02-16 11:52:41 - [Introduction](#introduction)- [Intended Audience](#intended-audience)- [Contact information](#contact-information)- [Archive Content](#archive-content)- [Data Model](#data-model)- [Metadata](#metadata)- [License](#license)- [CHANGELOG all annotated changes for previous year](#changelog-all-annotated-changes-for-previous-year) # IntroductionThis archive consists of the latest official data disseminated by the UNESCO Institute of Statistics (UIS) for a specific dataset. This dataset was compiled using the latest data as of the date appearing at the beginning of this file. The UIS periodically updates this dataset. To find out when the next update will occur please visit http://uis.unesco.org. # Intended Audience This archive is a result of a rigorous data production activity that ensures a high level of data quality. In order to expose the dataset to the largest audience possible and reduce its complexity the UIS has normalized and compiled it using comma-separated values (CSV) format. Please note all files utilize UTF-8 encoding. This allows both beginners and seasoned data professionals to understand and work with it. More information about this data and tutorials can be found on the UIS Developer Portal here: https://apiportal.uis.unesco.org/ # Contact informationIf you have any questions or comments about this archive please contact us at: UNESCO Institute for Statistics3500 De Maisonneuve Boulevard West, RS-1100Montreal, Quebec, Canada H3Z 3C1Tel: +1 514 343 6880Email: uis.datarequests@unesco.org # Archive ContentThis archive contains the following files: ## DATASET_README_RELEASE_YEAR_Month.mdThe README filename is composed of: &nbsp;The abbreviation for the dataset as a prefix, and the year and month of the release as a suffix. The README file also incorporates a header at the beginning of the file which identifies: the full title of the dataset contained in the archive, the month and year that the data was released by the UIS, and the date that the data was extracted to create the archive. The README file also details the contents of each file in the archive, as well as the data component layout and schema. &nbsp;The README file is in MARKDOWN format (https://www.markdownguide.org/). ## DATASETNAME_LABEL.csvThis file is a list of all indicator codes and their descriptive labels:|Field Name|Field Description||--|--||INDICATOR_ID |Indicator code||INDICATOR_LABEL_EN|Indicator code English label| ## DATASETNAME_DATA_NATIONAL.csvThis file contains all the national data available for this dataset and includes the following fields: |Field Name|Field Description||--|--||INDICATOR_ID|Indicator code||COUNTRY_ID|ISO 3166-1 alpha-3 country code||YEAR |Year of the measured value||VALUE |Measured value||MAGNITUDE |Metadata describing the NATURE of the measured value (see metadata section below)||QUALIFIER|Metadata describing the QUALITY of the measured value (see metadata section below)| ## DATASETNAME_DATA_REGIONAL.csvThis file contains all the regional data available for this dataset and includes the following fields: |Field Name|Field Description||--|--||INDICATOR_ID|Indicator code||REGION_ID|ISO 3166-1 alpha-3 country code||YEAR |Year of the measured value||VALUE |Measured value||MAGNITUDE |Metadata describing the NATURE of the measured value (see metadata section below)||QUALIFIER|Metadata describing the QUALITY of the measured value (see metadata section below)| ## DATASETNAME_METADATA.csvThis file contains all the metadata associated to the NATIONAL and REGIONAL data files above and includes the following fields: |Field Name|Field Description||--|--||INDICATOR_ID|Indicator code||COUNTRY_ID|ISO 3166-1 alpha-3 country code||YEAR |Year of the metadata value||TYPE |Type of metadata||METADATA|Metadata value| ## DATASETNAME_COUNTRY.csvThis file lists all country codes and their descriptive labels:|Field Name|Field Description||--|--||COUNTRY_ID|ISO 3166-1 alpha-3 country code||COUNTRY_NAME_EN|UNSTATS M49 STANDARD English country name (https://unstats.un.org/unsd/methodology/m49/)| ## DATASETNAME_REGION.csvThis file lists all regions and the countries that belong to each region:|Field Name|Field Description||--|--||REGION_ID|Label is composed of the name (acronym) of the organization that is responsible for the regional composition + ': ' + name of the region|COUNTRY_ID|ISO 3166-1 alpha-3 country code||COUNTRY_NAME_EN|UNSTATS M49 STANDARD English country name (https://unstats.un.org/unsd/methodology/m49/)| # Data ModelThe National (and Regional when available) data files can be linked with the: - **label file** using the “INDICATOR_ID” variable as the matching key.- **metadata file** (when available) using the “INDICATOR_ID”+”COUNTRY_ID”+”YEAR” variables combined as the matching key. Be aware that multiple metadata entries can match a unique data point from the data file i.e. there can be multiple metadata rows for a specific INDICATOR_ID/COUNTRY_ID/YEAR combination. Note that there can also be multiple entries within the same INDICATOR_ID/COUNTRY_ID/YEAR/TYPE combination. # Metadata## Indicator MetadataMost indicators have a Glossary entry that can be accessed on the UIS website at http://uis.unesco.org/en/glossary containing the indicators’: definition, interpretation, purpose, quality standards, calculation, types of disaggregation and limitation. ## MagnitudeMAGNITUDE describes the NATURE of the data point. Possible values are: - **NIL** – The value will be 0, and should be treated as NIL.- **NA** – The value will be 0. &nbsp;This data point is NOT APPLICABLE for the submitting nation.- **SUPP** - &nbsp;The value will be BLANK. &nbsp;The data point was SUPPRESSED by request of the submitting nation.- **LOWREL** – The value will be NUMERIC. &nbsp;The data point is of LOW RELIABILITY.- **INCLUDED** – The value will be BLANK. This data is INCLUDED in ANOTHER data point.- **INCLUDES** – The value will be NUMERIC. &nbsp;This data point INCLUDES data from another data point. ## QualifierQUALIFIER describes the QUALITIES of the data point. Possible values are:- **NAT_EST** – The value will be NUMERIC. &nbsp;This data point is a NATIONAL ESTIMATE.- **UIS_EST** – The value will be NUMERIC. &nbsp;This data point is an ESTIMATE produced by the UNESCO INSTITUTE FOR STATISTICS. # LicenseThis dataset is licensed under the Creative Commons Attribution-ShareAlike 3.0 IGO License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/igo/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. # CHANGELOG all annotated changes for previous year

Sustainable Development Goal 4 (SDG) Metadata

Dataset: Education: Other Policy Relevant IndicatorsRelease date: 2024-02Data extracted on: 2024-02-16 11:51:12 - [Introduction](#introduction)- [Intended Audience](#intended-audience)- [Contact information](#contact-information)- [Archive Content](#archive-content)- [Data Model](#data-model)- [Metadata](#metadata)- [License](#license)- [CHANGELOG all annotated changes for previous year](#changelog-all-annotated-changes-for-previous-year) # IntroductionThis archive consists of the latest official data disseminated by the UNESCO Institute of Statistics (UIS) for a specific dataset. This dataset was compiled using the latest data as of the date appearing at the beginning of this file. The UIS periodically updates this dataset. To find out when the next update will occur please visit http://uis.unesco.org. # Intended Audience This archive is a result of a rigorous data production activity that ensures a high level of data quality. In order to expose the dataset to the largest audience possible and reduce its complexity the UIS has normalized and compiled it using comma-separated values (CSV) format. Please note all files utilize UTF-8 encoding. This allows both beginners and seasoned data professionals to understand and work with it. More information about this data and tutorials can be found on the UIS Developer Portal here: https://apiportal.uis.unesco.org/ # Contact informationIf you have any questions or comments about this archive please contact us at: UNESCO Institute for Statistics3500 De Maisonneuve Boulevard West, RS-1100Montreal, Quebec, Canada H3Z 3C1Tel: +1 514 343 6880Email: uis.datarequests@unesco.org # Archive ContentThis archive contains the following files: ## DATASET_README_RELEASE_YEAR_Month.mdThe README filename is composed of: &nbsp;The abbreviation for the dataset as a prefix, and the year and month of the release as a suffix. The README file also incorporates a header at the beginning of the file which identifies: the full title of the dataset contained in the archive, the month and year that the data was released by the UIS, and the date that the data was extracted to create the archive. The README file also details the contents of each file in the archive, as well as the data component layout and schema. &nbsp;The README file is in MARKDOWN format (https://www.markdownguide.org/). ## DATASETNAME_LABEL.csvThis file is a list of all indicator codes and their descriptive labels:|Field Name|Field Description||--|--||INDICATOR_ID |Indicator code||INDICATOR_LABEL_EN|Indicator code English label| ## DATASETNAME_DATA_NATIONAL.csvThis file contains all the national data available for this dataset and includes the following fields: |Field Name|Field Description||--|--||INDICATOR_ID|Indicator code||COUNTRY_ID|ISO 3166-1 alpha-3 country code||YEAR |Year of the measured value||VALUE |Measured value||MAGNITUDE |Metadata describing the NATURE of the measured value (see metadata section below)||QUALIFIER|Metadata describing the QUALITY of the measured value (see metadata section below)| ## DATASETNAME_DATA_REGIONAL.csvThis file contains all the regional data available for this dataset and includes the following fields: |Field Name|Field Description||--|--||INDICATOR_ID|Indicator code||REGION_ID|ISO 3166-1 alpha-3 country code||YEAR |Year of the measured value||VALUE |Measured value||MAGNITUDE |Metadata describing the NATURE of the measured value (see metadata section below)||QUALIFIER|Metadata describing the QUALITY of the measured value (see metadata section below)| ## DATASETNAME_METADATA.csvThis file contains all the metadata associated to the NATIONAL and REGIONAL data files above and includes the following fields: |Field Name|Field Description||--|--||INDICATOR_ID|Indicator code||COUNTRY_ID|ISO 3166-1 alpha-3 country code||YEAR |Year of the metadata value||TYPE |Type of metadata||METADATA|Metadata value| ## DATASETNAME_COUNTRY.csvThis file lists all country codes and their descriptive labels:|Field Name|Field Description||--|--||COUNTRY_ID|ISO 3166-1 alpha-3 country code||COUNTRY_NAME_EN|UNSTATS M49 STANDARD English country name (https://unstats.un.org/unsd/methodology/m49/)| ## DATASETNAME_REGION.csvThis file lists all regions and the countries that belong to each region:|Field Name|Field Description||--|--||REGION_ID|Label is composed of the name (acronym) of the organization that is responsible for the regional composition + ': ' + name of the region|COUNTRY_ID|ISO 3166-1 alpha-3 country code||COUNTRY_NAME_EN|UNSTATS M49 STANDARD English country name (https://unstats.un.org/unsd/methodology/m49/)| # Data ModelThe National (and Regional when available) data files can be linked with the: - **label file** using the “INDICATOR_ID” variable as the matching key.- **metadata file** (when available) using the “INDICATOR_ID”+”COUNTRY_ID”+”YEAR” variables combined as the matching key. Be aware that multiple metadata entries can match a unique data point from the data file i.e. there can be multiple metadata rows for a specific INDICATOR_ID/COUNTRY_ID/YEAR combination. Note that there can also be multiple entries within the same INDICATOR_ID/COUNTRY_ID/YEAR/TYPE combination. # Metadata## Indicator MetadataMost indicators have a Glossary entry that can be accessed on the UIS website at http://uis.unesco.org/en/glossary containing the indicators’: definition, interpretation, purpose, quality standards, calculation, types of disaggregation and limitation. ## MagnitudeMAGNITUDE describes the NATURE of the data point. Possible values are: - **NIL** – The value will be 0, and should be treated as NIL.- **NA** – The value will be 0. &nbsp;This data point is NOT APPLICABLE for the submitting nation.- **SUPP** - &nbsp;The value will be BLANK. &nbsp;The data point was SUPPRESSED by request of the submitting nation.- **LOWREL** – The value will be NUMERIC. &nbsp;The data point is of LOW RELIABILITY.- **INCLUDED** – The value will be BLANK. This data is INCLUDED in ANOTHER data point.- **INCLUDES** – The value will be NUMERIC. &nbsp;This data point INCLUDES data from another data point. ## QualifierQUALIFIER describes the QUALITIES of the data point. Possible values are:- **NAT_EST** – The value will be NUMERIC. &nbsp;This data point is a NATIONAL ESTIMATE.- **UIS_EST** – The value will be NUMERIC. &nbsp;This data point is an ESTIMATE produced by the UNESCO INSTITUTE FOR STATISTICS. # LicenseThis dataset is licensed under the Creative Commons Attribution-ShareAlike 3.0 IGO License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/igo/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. # CHANGELOG all annotated changes for previous year