AndreaBozzo/ceres-open-data-index huggingface dataset:
Argentina - Data on Conflict Events

This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.  
Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532  
Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University

Tags: conflict-violence, hxl
Organization: HDX
Angola - Data on Conflict Events

This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.  
Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532  
Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University

Tags: conflict-violence, hxl
Organization: HDX
Algeria - Data on Conflict Events

This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.  
Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532  
Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University

Tags: conflict-violence, hxl
Organization: HDX
Albania - Data on Conflict Events

This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.  
Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532  
Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University

Tags: conflict-violence, hxl
Organization: HDX
Afghanistan - Data on Conflict Events

This dataset is UCDP's most disaggregated dataset, covering individual events of organized violence (phenomena of lethal violence occurring at a given time and place). These events are sufficiently fine-grained to be geo-coded down to the level of individual villages, with temporal durations disaggregated to single, individual days.  
Sundberg, Ralph, and Erik Melander, 2013, “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, vol.50, no.4, 523-532  
Högbladh Stina, 2019, “UCDP GED Codebook version 19.1”, Department of Peace and Conflict Research, Uppsala University

Tags: conflict-violence, hxl
Organization: HDX
Ukraine Displacement Data/Report - Conditions of Return Assessment (CoRA) [IOM DTM]

The CoRA employs a multi-sectoral location-level assessment (MSLA) methodology conducted with local authority key informants at the settlement or city-raion level.

The assessment is based on 20 indicators divided into five ‘drivers’: 
(1) livelihoods, 
(2) utilities and services 
(3) residential destruction, 
(4) safety and security, and 
(5) public life. 

The indicators describe the critical or minimum conditions required for sustainable return and reintegration in Ukraine. The scores of each indicator and driver are grouped into three categories: low, medium, and high severity of living conditions. 

For more information on the methodology, please refer to the full report. When requesting the dataset, please specify if you would like to receive the report as well.

Tags: internally displaced persons-idp, severity
Organization: International Organization for Migration (IOM)
Nepal - Results Monitoring Survey and Socio-Sconomic Assessment 2022

The survey streamlines data collection and monitoring of impact and outcome level results as part of multi-year country strategy. Monitoring progress towards education enrollment and sustainable livelihoods results is vital to inform course correction in the operation’ annual implementation plan and budgeting. 
  The RMS and SEA are to be representative of persons of concern (PoC).
  This exercise was part of the 2022 RMS pilot.

Tags: education, health, livelihoods, needs assessment, protection, survey
Organization: UNHCR - The UN Refugee Agency
Tanzania: Market Price Survey for Essential Commodities

The dataset contains market price benchmarking results from a Market Price Survey conducted across selected regions of Tanzania in December 2025. It includes validated price data for essential commodity items such as construction materials, agricultural inputs, transport services, and selected health and education items, disaggregated by region and market location.

The survey was conducted to provide reliable and up-to-date pricing benchmarks to support humanitarian procurement, budget planning, and the design of cash-based programming and livelihood interventions. The data aims to strengthen transparency, value for money, and responsiveness to market dynamics, including inflation and supply chain disruptions, while providing standardized market reference prices for humanitarian and development actors operating in Tanzania.

Tags: economics, indicators, livelihoods, markets
Organization: HELP Logistics
Kyrgyzstan - Results Monitoring Survey 2022

The UNHCR Results Monitoring Survey (RMS) is a household-level survey on persons of concern (PoC) to UNHCR directly or indirectly assisted by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR’s multi-year strategies to key stakeholders.

The RMS can be implemented in any operational context. A standard structured questionnaire has been developed for the RMS, which can be conducted as a stand-alone survey or flexibly integrated with other data collection exercises. The data includes indicators collected at both the household and individual (household-member) level, and results are statistically representative.

Tags: education, health, livelihoods, nutrition, survey
Organization: UNHCR - The UN Refugee Agency
Kazakhstan - Results Monitoring Survey, 2022

The UNHCR Results Monitoring Survey (RMS) is a household-level survey for person for and with whom UNHCR works, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR’s multi-year strategies to key stakeholders.

The RMS can be implemented in any operational context. A standard structured questionnaire has been developed for the RMS, which can be conducted as a stand-alone survey or flexibly integrated with other data collection exercises.  The questionnaire was adapted to the Kazakhstan context and programme objectives and focused on health, education and employment. The data includes indicators collected at both the household and individual (household-member) level. The survey covered 89 household containing 363 individuals.

Tags: education, health, livelihoods, nutrition, survey
Organization: UNHCR - The UN Refugee Agency
Nepal - Results Monitoring Survey and Socio-Economic Assessment - 2023

The UNHCR Results Monitoring Survey (RMS) is a household-level survey covering people who are directly or indirectly assisted by UNHCR. In Nepal the survey covered refugees and Asylum Seekers. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter and social protection. The results contribute to an evidence base for reporting against UNHCR’s multi-year strategies to key stakeholders.

The RMS can be implemented in any operational context. A standard structured questionnaire has been developed for the RMS, which can be conducted as a stand-alone survey or flexibly integrated with other data collection exercises. The questionnaire was adapted to the Nepali context and programme objectives by removing, e.g. questions related to camp settings. Additionally, an extended module socio-economic markers was included. The data includes indicators collected at both the household and individual (household-member) level. The survey covered 361 household amounting to 1292 individuals.

Tags: education, health, livelihoods, needs assessment, protection, survey
Organization: UNHCR - The UN Refugee Agency
Mongolia: IBTrACS Storm Tracks

The International Best Track Archive for Climate Stewardship (IBTrACS) project is the most complete global collection of tropical cyclones available. It merges recent and historical tropical cyclone data from multiple agencies to create a unified, publicly available, best-track dataset that improves inter-agency comparisons.   
   
 Fields available:   
 SID: A unique storm identifier (SID) assigned by IBTrACS algorithm.  
 ISO_TIME: Time of the observation in ISO format (YYYY-MM-DD hh:mm:ss)   
 BASIN: Basin of the current storm position   
 SUBBASIN: Sub-basin of the current storm position   
 NATURE: Type of storm (a combination of the various types from the available sources)   
 NUMBER: Number of the storm for the year (restarts at 1 for each year   
 LAT: Mean position - latitude (a combination of the available positions)   
 LON: Mean position - longitude (a combination of the available positions)   
 WMO_WIND: Maximum sustained wind speed assigned by the responsible WMO agency   
 WMO_PRES: Minimum central pressure assigned by the responsible WMO agency.

Tags: cyclones-hurricanes-typhoons
Organization: HDX
Satellite detected waters in Cortes and Yoro departments of Honduras as of 18 November 2020

**UNOSAT code: TC20201116HND**  This map illustrates satellite-detected surface waters in Colon and Yoro Departments of Honduras as observed from a Sentinel-1 image acquired on 18 November 2020 at 18:06 Local time. Within the analyzed area of about 5,200 km2, a total of about 220 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 82,000 people are potentially exposed or living close to flooded areas.  
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. 
Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal. 

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Damage assessment of Old City, Mosul, Ninawa Governorate, Iraq (16 June 2017)

This map illustrates satellite-detected damage in Old City, Mosul, Ninawa Governorate, Iraq. Using satellite imagery acquired 16 June 2017, UNITAR - UNOSAT identified a total of 4,040 affected structures within this part of city. This marks an overall increase of 56% in damage affected structures from the assessment five days prior on 11 June. Approximately 196 of these were destroyed (5% of the total affected buildings), 2,107 severely damaged (52% of the total affected buildings) and 1,737 moderately damaged (43% of the total affected buildings). This marks a 28% increase in destroyed buildings, 17% in moderately damaged buildings and 121% severely damaged buildings from the 11 June assessment.  The most heavily impacted area appears to be the Bab al-Tub neighbourhood (see inset). Due to the densely constructed nature of this part of the city, these values might be underestimated. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Tags: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Damage Assessment in Providencia Island, Providencia and Santa Catalina Department, Colombia as of 21 November 2020

**UNOSAT code: TC20201123COL**  This map illustrates potentially damaged structures and buildings in Providencia Island, Providencia and Santa Catalina Department of Colombia as detected by satellite image acquired after landfall of the Tropical Cyclone IOTA on 17 November 2020.  
UNITAR-UNOSAT analysis used a WorldView-2 image acquired on 21 November 2020 as a post-event image. Within the Island boundary, UNITAR-UNOSAT identified in the cloud-free zones 1,110 damaged structures. Taking into account the pre-building footprints provided by Humanitarian OpenStreetMap, this represents about 90% of the total number of structures within the analyzed cloud-free areas. 

Tags: cyclones-hurricanes-typhoons, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Sahel - Cattle Theft Probability Prediction

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.

Tags: agriculture-livestock, climate-weather, governance and civil society
Organization: Acción contra el hambre - GIS4tech
Sahel - Abnormal Herd Movements Prediction

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.

Tags: agriculture-livestock, climate-weather, governance and civil society
Organization: Acción contra el hambre - GIS4tech
Sahel Prediction Death Animals

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.

Tags: agriculture-livestock, climate-weather, governance and civil society
Organization: Acción contra el hambre - GIS4tech
Guatemala - Open spaces and green areas

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).   
Data on a) Average share of cities/urban areas in green areas (%), and b) Green area per capita (m2/person) for the periods 1990, 2000, 2010 and 2020.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Ethiopia - Open spaces and green areas

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).   
Data on a) Average share of cities/urban areas in green areas (%), and b) Green area per capita (m2/person) for the periods 1990, 2000, 2010 and 2020.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Colombia - Open spaces and green areas

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).   
Data on a) Average share of cities/urban areas in green areas (%), and b) Green area per capita (m2/person) for the periods 1990, 2000, 2010 and 2020.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Democratic Republic of the Congo - Open spaces and green areas

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).   
Data on a) Average share of cities/urban areas in green areas (%), and b) Green area per capita (m2/person) for the periods 1990, 2000, 2010 and 2020.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Cameroon - Open spaces and green areas

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).   
Data on a) Average share of cities/urban areas in green areas (%), and b) Green area per capita (m2/person) for the periods 1990, 2000, 2010 and 2020.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Central African Republic - Open spaces and green areas

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).   
Data on a) Average share of cities/urban areas in green areas (%), and b) Green area per capita (m2/person) for the periods 1990, 2000, 2010 and 2020.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Burkina Faso - Open spaces and green areas

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).   
Data on a) Average share of cities/urban areas in green areas (%), and b) Green area per capita (m2/person) for the periods 1990, 2000, 2010 and 2020.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Afghanistan - Open spaces and green areas

Data on a) Average share of urban areas allocated to streets and open public spaces, and b) Share of urban population with convenient access to an open public space (defined as share of urban population within 400 meters walking distance along the street network to an open public space).   
Data on a) Average share of cities/urban areas in green areas (%), and b) Green area per capita (m2/person) for the periods 1990, 2000, 2010 and 2020.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Housing, slums and informal settlements

Proportion of urban population living in slums or informal settlements per country, territory and region, based on 4 out of 5 main household shelter deprivations defined by UN-Habitat as indicators of informality: lack of access to improved water, lack of access to improved sanitation, lack of sufficient living area and quality/durability of structure. Security of tenure is the fifth deprivation that is not included due to data limitations.   
Proportion of urban population living in inadequate housing, calculated based on households with net monthly expenditure on housing exceeding 30% of their total monthly income.   
 Total urban population living in slums or informal settlements per country, territory and region, based on 4 out of 5 main household shelter deprivations defined by UN-Habitat as indicators of informality: lack of access to improved water, lack of access to improved sanitation, lack of sufficient living area and quality/durability of structure. Security of tenure is the fifth deprivation that is not included due to data limitations.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section
Yemen - Housing, slums and informal settlements

Proportion of urban population living in slums or informal settlements per country, territory and region, based on 4 out of 5 main household shelter deprivations defined by UN-Habitat as indicators of informality: lack of access to improved water, lack of access to improved sanitation, lack of sufficient living area and quality/durability of structure. Security of tenure is the fifth deprivation that is not included due to data limitations.   
Proportion of urban population living in inadequate housing, calculated based on households with net monthly expenditure on housing exceeding 30% of their total monthly income.   
 Total urban population living in slums or informal settlements per country, territory and region, based on 4 out of 5 main household shelter deprivations defined by UN-Habitat as indicators of informality: lack of access to improved water, lack of access to improved sanitation, lack of sufficient living area and quality/durability of structure. Security of tenure is the fifth deprivation that is not included due to data limitations.

Tags: sustainable development goals-sdg, urban
Organization: United Nations Human Settlements Programmes, Data and Analytics Section