Search for a Dataset - Humanitarian Data Exchange

Yemen: Areas of control

ACAPS

11000+ Downloads

Time Period of the Dataset [?]: August 18, 2021-October 24, 2024 ... More

This dataset updates: Every two weeks

This bi-weekly dataset provides an overview of the latest areas of control in Yemen and includes a map, excel spreadsheet and GIS layer. All datasets are fully PCODED to Admin 2 district level, enabling interoperability with other datasets. Through understanding the latest areas of control, it is possible to enhance analysis in areas such as political-economy through adjusting tools to take into account the current geographic situation. This dataset forms part of the Yemen CrisisInsight product suite which includes the Yemen Core Dataset, Yemen: Crisis Impact Overview and Yemen Risk Overview.

SHP

Peace and Security Pillar: Police Personnel in Missions

United Nations Peace and Security Data Hub

50+ Downloads

Time Period of the Dataset [?]: January 01, 2010-January 25, 2025 ... More

This dataset updates: Every month

Summary of total contributions of formed police units and individual police by Member States to UN Missions broken down by gender. UN police personnel are contributed to serve under the blue flag from over 100 countries to carry out the mandates defined by the Security Council.

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Peace and Security Pillar: Latest Uniformed Personnel Contribution By Country

United Nations Peace and Security Data Hub

4500+ Downloads

Time Period of the Dataset [?]: December 01, 2023-December 31, 2023 ... More

This dataset updates: Every month

Summary of total contributions of uniformed personnel by Member States to UN Missions broken down by rank. UN police and military personnel are contributed to serve under the blue flag from over 100 countries to carry out the mandates defined by the Security Council.

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Peace and Security Pillar: Historical Uniformed Personnel Contribution

United Nations Peace and Security Data Hub

2500+ Downloads

Time Period of the Dataset [?]: January 01, 2010-January 25, 2025 ... More

This dataset updates: Every month

Summary of total contributions of uniformed personnel by Member States to UN Missions broken down by gender. UN police and military personnel are contributed to serve under the blue flag from over 100 countries to carry out the mandates defined by the Security Council. Data is typically updated approximately six weeks after the conclusion of each month.

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Northeast Nigeria - Humanitarian Profile

OCHA Nigeria

800+ Downloads

Time Period of the Dataset [?]: June 01, 2021-December 31, 2024 ... More

This dataset updates: Every year

In the humanitarian context / humanitarian profiling, it demonstrates a strong evidence base, positive impact on resource allocation, and forms the basis and reference point of any relief operation aiming to deliver aid according to the population’s needs. This data gives the total size of population for Borno, Adamawa, and Yobe states (BAY) and disaggregated by sex and age (SADD) for each population category. The population category is grouped into: • Internally displaced people (IDP) • Returnees • Host community • Inaccessible areas

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Afghanistan: Humanitarian Situation Monitoring (HSM) Round 6 KII (Analysis)

REACH Initiative

Time Period of the Dataset [?]: February 11, 2024-March 07, 2024 ... More

This dataset updates: Every three months

The Humanitarian Situation Monitoring (HSM) is a quarterly community-level multi-sectoral needs assessment. It builds upon the previously implemented Hard-to-Reach assessment and expanded its geographic coverage to encompass the entire country in early 2022, due to the shift in context. HSM aims to collect and then triangulate information regarding service provision, sectoral needs, and vulnerabilities in Afghan communities regularly, in order to support geographical and sectoral prioritizations, particularly in light of the rapidly evolving context in Afghanistan. HSM assesses the sectoral and multi-sectoral needs of populations in all districts by filling in information gaps and enhancing response capacity for district-level prioritization.

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Sahel Prediction Death Animals

Acción contra el hambre - GIS4tech

Time Period of the Dataset [?]: January 01, 2018-September 30, 2024 ... More

This dataset updates: As needed

The model trains with the actual data of the variables to be predicted and uses their correlation with agroclimatic indicators, biomass, and violence to predict said variable where there is no actual data, at the level of Commune/Municipality for all of Senegal and Mauritania. This information belongs to the Food and Nutrition Security Monitoring and Prediction System in the Sahel (PREDISAN) Project, funded by the Agencia Andaluza de Cooperación Internacional para el Desarrollo (AACID) and the University of Granada (UGR). The PREDISAN AI-SAHEL Project focuses on the Monitoring and Prediction System for Humanitarian Vulnerability of Pastoral and Agro-pastoral Populations in the Western Sahel, based on GIS Analysis and Artificial Intelligence. For more information, contact GIS4Tech at info@gis4tech.com or visit the PREDISAN platform at https://predisan.gis4tech.com/sahel.

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Sahel - Cattle Theft Probability Prediction

Acción contra el hambre - GIS4tech

Time Period of the Dataset [?]: January 01, 2018-September 30, 2024 ... More

This dataset updates: As needed

The model trains with the actual data of the variables to be predicted and uses their correlation with agroclimatic indicators, biomass, and violence to predict said variable where there is no actual data, at the level of Commune/Municipality for all of Senegal and Mauritania. This information belongs to the Food and Nutrition Security Monitoring and Prediction System in the Sahel (PREDISAN) Project, funded by the Agencia Andaluza de Cooperación Internacional para el Desarrollo (AACID) and the University of Granada (UGR). The PREDISAN AI-SAHEL Project focuses on the Monitoring and Prediction System for Humanitarian Vulnerability of Pastoral and Agro-pastoral Populations in the Western Sahel, based on GIS Analysis and Artificial Intelligence. For more information, contact GIS4Tech at info@gis4tech.com or visit the PREDISAN platform at https://predisan.gis4tech.com/sahel.

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Sahel - Abnormal Herd Movements Prediction

Acción contra el hambre - GIS4tech

Time Period of the Dataset [?]: January 01, 2024-September 30, 2024 ... More

This dataset updates: As needed

The model trains with the actual data of the variables to be predicted and uses their correlation with agroclimatic indicators, biomass, and violence to predict said variable where there is no actual data, at the level of Commune/Municipality for all of Senegal and Mauritania. This information belongs to the Food and Nutrition Security Monitoring and Prediction System in the Sahel (PREDISAN) Project, funded by the Agencia Andaluza de Cooperación Internacional para el Desarrollo (AACID) and the University of Granada (UGR). The PREDISAN AI-SAHEL Project focuses on the Monitoring and Prediction System for Humanitarian Vulnerability of Pastoral and Agro-pastoral Populations in the Western Sahel, based on GIS Analysis and Artificial Intelligence. For more information, contact GIS4Tech at info@gis4tech.com or visit the PREDISAN platform at https://predisan.gis4tech.com/sahel.

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Sahel Nightlights

Acción contra el hambre - GIS4tech

Time Period of the Dataset [?]: January 01, 2018-August 31, 2024 ... More

This dataset updates: As needed

Information on nightlights in Senegal and Mauritania. This measurement of visible and near-infrared nighttime lights generated by human activity has been used to create the nighttime light indices, and it is categorized by country, departments, and municipalities. This information belongs to the Food and Nutrition Security Monitoring and Prediction System in the Sahel (PREDISAN) Project, funded by the Agencia Andaluza de Cooperación Internacional para el Desarrollo (AACID) and the University of Granada (UGR). The PREDISAN AI-SAHEL Project focuses on the Monitoring and Prediction System for Humanitarian Vulnerability of Pastoral and Agro-pastoral Populations in the Western Sahel, based on GIS Analysis and Artificial Intelligence. For more information, contact GIS4Tech at info@gis4tech.com or visit the PREDISAN platform at https://predisan.gis4tech.com/sahel

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Sahel Biomass by ACH-GIS4Tech

Acción contra el hambre - GIS4tech

Time Period of the Dataset [?]: January 01, 2020-September 30, 2024 ... More

This dataset updates: As needed

Information on biomass in Senegal and Mauritania contains the Gross Primary Productivity index (GPP), which indicates the kilograms of carbon dioxide stored by plants in one square meter, and it is categorized by country, departments, and municipalities. This information belongs to the Food and Nutrition Security Monitoring and Prediction System in the Sahel (PREDISAN) Project, funded by the Agencia Andaluza de Cooperación Internacional para el Desarrollo (AACID) and the University of Granada (UGR). The PREDISAN AI-SAHEL Project focuses on the Monitoring and Prediction System for Humanitarian Vulnerability of Pastoral and Agro-pastoral Populations in the Western Sahel, based on GIS Analysis and Artificial Intelligence. For more information, contact GIS4Tech at info@gis4tech.com or visit the PREDISAN platform at https://predisan.gis4tech.com/sahel

CSV

Sahel Protected Areas by ACH-GIS4Tech

Acción contra el hambre - GIS4tech

Time Period of the Dataset [?]: October 01, 2024-October 01, 2024 ... More

This dataset updates: As needed

Information of protected areas in Senegal and Mauritania is expressed in square kilometres, and categorized by country, departments and municipality. This information belongs to the Food and Nutrition Security Monitoring and Prediction System in the Sahel (PREDISAN) Project, funded by the Agencia Andaluza de Cooperación Internacional para el Desarrollo (AACID) and the University of Granada (UGR). The PREDISAN AI-SAHEL Project focuses on the Monitoring and Prediction System for Humanitarian Vulnerability of Pastoral and Agro-pastoral Populations in the Western Sahel, based on GIS Analysis and Artificial Intelligence. For more information, contact GIS4Tech at info@gis4tech.com or visit the PREDISAN platform at https://predisan.gis4tech.com/sahel

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Philippines - Open, validated health, climate, environment and socioeconomic data

Thinking Machines Data Science

1500+ Downloads

Time Period of the Dataset [?]: January 01, 2003-March 31, 2024 ... More

This dataset updates: As needed

The Project Climate Change, Health, and Artificial Intelligence (Project CCHAIN) dataset is a validated, open-sourced linked dataset containing 20 years (2003-2022) of climate, environmental, socioeconomic, and health dimensions at the barangay (village) level across twelve Philippine cities (Dagupan, Palayan, Navotas, Mandaluyong, Muntinlupa, Legazpi, Iloilo, Mandaue, Tacloban, Zamboanga, Cagayan de Oro, Davao). The full documentation can be accessed here. The tables are designed in a way that users can choose variables that are most relevant to their focus city and use case, and link these variables to form a single dataset by merging using standard geography codes and calendar dates. This can be done using the provided linking notebook, or offline using the user's own code. Here are some tips on how make most use of this dataset: Focus on one location. Starting with a detailed analysis of one location allows for a better understanding of the local dynamics, which may differ across locations. Choose one health data source. Pick one of either a central or local data source. Using two different data health sources is not advised because it will lead to double/overcounting of disease cases. Do not use all variables at once- do a literature review first to identify possible key variables. to identify possible key variables. More often than not, using all variables is not necessary and may even yield subpar results. Check data availability on your focus location and make sure they fit the requirements of your study. This dataset also includes household surveys tables (see schema here and here) done on partner informal settlement communities in the cities of Muntinlupa, Davao, Iloilo, and Mandaue and administered on various dates up to 2024. Due to the sensitive nature of surveys and the vulnerability of the subjects involved, requests for access must be submitted for review and approval by the Philippine Action for Community-Led Shelter Initiatives, Inc. (PACSII). To submit a request, please use this form.

CSV

Zambia - One Meheba Local Area Plan - 2024

UNHCR - The UN Refugee Agency

Time Period of the Dataset [?]: January 13, 2024-January 17, 2024 ... More

This dataset updates: Never

The Meheba Local Area Plan (LAP) for 2024-2028, initiated by Kalumbila Town Council, Department of Resettlement (DoR) and Office of the Commissioner for Refugees (CoR) in Zambia, encompasses a comprehensive strategy to integrate and develop the Meheba region, which hosts refugees and local populations. This plan focuses on modernizing infrastructure, boosting agricultural productivity, and ensuring inclusive community development. Utilizing surveys and extensive stakeholder engagement, the LAP aims to capture data on demographic changes, economic conditions, and social services within Meheba. A total of 1,700 detailed surveys across key populations will assess the impact of interventions and guide future development strategies. By aligning with national policies and focusing on sustainable development, the LAP seeks to transform Meheba into a productive, self-reliant community, enhancing the quality of life for all residents. This dataset will be pivotal in monitoring progress and adjusting policies to better serve the diverse needs of the Meheba population.

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Yemen Core Dataset

ACAPS

2000+ Downloads

Time Period of the Dataset [?]: January 01, 2020-February 28, 2024 ... More

This dataset updates: As needed

This dataset brings together data from a range of sources to provide a greater overall and comparative understanding of the current situation and context inside each district. The core indicators consist of key drivers (conflict, basic commodity prices, exclusion and marginalization, and disrupted access to life-saving services and income sources) and their major expected humanitarian impacts (food insecurity, cholera).

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OXFORD COVID-19 Government Response Stringency index

Blavatnik School of Government, University of Oxford

8900+ Downloads

Time Period of the Dataset [?]: January 01, 2020-January 25, 2025 ... More

This dataset updates: Live

Governments are taking a wide range of measures in response to the COVID-19 outbreak. The Oxford COVID-19 Government Response Tracker (OxCGRT) aims track and compare government responses to the coronavirus outbreak worldwide rigorously and consistently. The OxCGRT systematically collects information on several different common policy responses governments have taken, scores the stringency of such measures, and aggregates these scores into a common Stringency Index. For more, please visit > https://www.bsg.ox.ac.uk/research/research-projects/oxford-covid-19-government-response-tracker

Central America Walking Time to Public Order Buildings by ACH-GIS4Tech

Acción contra el hambre - GIS4tech

80+ Downloads

Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More

This dataset updates: As needed

Average time needed to get from a municipality to the nearest law enforcement building (police station, police station, barracks, command, etc.) on foot. Data source: Humdata June 2020. Categorized by country, department and municipality. For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.

CSV

Central America Public Order Buildings per 100k inhabitants

Acción contra el hambre - GIS4tech

80+ Downloads

Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More

This dataset updates: As needed

Number of public order buildings per 100,000 inhabitants based on territorial analysis with GIS (own elaboration). Data source: Humdata June 2020 by country, department and municipality. For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.

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Central America Protected Areas by ACH-GIS4Tech

Acción contra el hambre - GIS4tech

80+ Downloads

Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More

This dataset updates: As needed

Information on protected areas in Central America is expressed in square kilometres. Categorized by country, departments and municipality. For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.

CSV

Afghanistan Core Dataset

ACAPS

400+ Downloads

Time Period of the Dataset [?]: September 20, 2022-January 25, 2025 ... More

This dataset updates: As needed

This dataset brings together data from a range of sources to provide a greater overall and comparative understanding of the current situation and context inside each district. The core indicators consist of key drivers (conflict, basic commodity prices, exclusion and marginalization, and disrupted access to life-saving services and income sources) and their major expected humanitarian impacts (food insecurity, cholera). ACAPS tracks changes in these indicators and alerts the humanitarian community to emerging trends or risks that could overwhelm local coping mechanisms in Afghanistan, triggering a humanitarian emergency.

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Government Revenue Dataset (GRD)

The United Nations University World Institute for Development Economics Research

90+ Downloads

Time Period of the Dataset [?]: January 01, 1980-October 31, 2022 ... More

This dataset updates: Every year

The UNU-WIDER Government Revenue Dataset (GRD) aims to present a complete picture of government revenue and tax trends over time and allows for analysis at the country, regional or cross-country level. The GRD provides data on government tax and non-tax revenues, social contributions, and grants in both local currency and as a percentage of GDP. It also highlights the portion of government revenues that accrue from natural resource extraction. The dataset covers the latest available tax and revenue data for the period from 1980—2019 (or —2020 where available) for 196 countries. The data can be accessed online through the GRD Explorer tool, which allows users to compare countries, regions, and indicators as well as to visualize the data, or by download in Stata and Excel formats. The dataset is updated annually based on changes or updates to the underlying data, as well as on feedback from users with regard to particular countries or regions. For more information please visit https://www.wider.unu.edu/project/grd

Ecuador: Crime for Corruption in Quito

Hub Latin America

20+ Downloads

Time Period of the Dataset [?]: January 01, 2019-December 31, 2020 ... More

This dataset updates: Every year

News registry for the crime of corruption

SHP

COVID-19 Cases Data in Moscow

Infoculture

200+ Downloads

Time Period of the Dataset [?]: January 06, 2020-February 04, 2021 ... More

This dataset updates: Every week

This dataset from original data of COVID-19 statistics collected from the official website of Moscow government.

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COVID-19 Cases Data in Russia

Infoculture

200+ Downloads

Time Period of the Dataset [?]: March 01, 2020-February 04, 2021 ... More

This dataset updates: Every day

Region-level data collected from the official website of Russian Federal Agency Rospotrebnadzor (https://стопкоронавирус.рф/). Dataset exists attributes: data, infected, recovered, died. The dataset contains information of 85 Russian regions.

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Registry of Russian NGO’s affected by COVID-19

Infoculture

100+ Downloads

Time Period of the Dataset [?]: June 30, 2020-January 25, 2025 ... More

This dataset updates: Every year

Registry of Russian social-oriented non profit organizations recognized by the government as affected by COVID-19 and that receive government support. The Ministry of Economic Development of Russia published the register of non profit non government organizations (NGOs) that will be provided with additional measures of support. Dataset columns: name of organization, OGRN, INN, Responsible government agency, Status, Orgform. The dataset contains information about 11 208 NGOs of 85 Russian regions.

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