AndreaBozzo/ceres-open-data-index huggingface dataset:
Ukraine - Subnational Administrative Gazetteer

This Ukraine administrative level 0-4 enhanced gazetteer contains all available useful attribute information for every current Ukrainian administrative feature.   It is compatible with the gazetteer provided in the [Ukraine - Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-ukr) dataset, the [Ukraine - Subnational Population Statistics](https://data.humdata.org/dataset/cod-ps-ukr) dataset, and the [Ukraine - Subnational Edge-matched Administrative Boundaries](https://data.humdata.org/dataset/cod-em-ukr) dataset.  However, it extends that gazetteer with the following information (for each administrative level, as appropriate).  (Please note that the spreadsheet contains a table of the field names.)

POLYGON PARTS - the number of individual polygons comprising each administrative feature

ADMx_COUNT - the number of administrative features in each lower administrative level per administrative feature

ORIENTATION - the recommended cartographic neatline orientation based on the ratio of the X and Y extent

ADMx_RP_LON / LAT representative point latitude / longitude derived by QGIS “Pole of inaccessibility” tool

ADMx_CAPITAL 'Y' if the (ADM4 only) feature is an ADM0, 1, 2, or 3 capital

FAO P-CODE

FAO -EN name

UNICEF P-CODE

UNICEF EN name

CODETOPO legacy Ukrainian administrative feature code

ADMx_TYPE_EN, ADMx_TYPE_UA administrative feature type

KOATUU legacy Ukrainian administrative feature code

Minregion legacy Ukrainian administrative feature code

Tags: gazetteer
Organization: OCHA Field Information Services Section (FISS)
Pakistan Subnational Population and Housing Data Tables with Administrative Boundaries, Based on National Census and Surveys

The geodatabase contains boundaries for the national, first-, second-, third-, and fourth-order administrative divisions, aligned to the Large Scale International Boundaries dataset from the U.S. Department of State. The feature classes are suitable for linking to the attribute data provided.

The tabular data contain total population for 2017 (census), as well as five-year age group and sex, and information relating to households, housing units, amenities, nationality, religion, language, information and communication technology, livestock, and agriculture.

Organization: U.S. Census Bureau
Central America - Risk Prices

A summary table is established at the municipal level with the list of threats per product calculated from the product price indicators shown in the Vulnerability panel. For each column, the threat category in which the municipality would find itself is defined (No risk, Mild threat, Moderate threat, Severe threat), and the final column represents the general summary of the global threats, obtained using the 20% rule. The calculation within each category is established through a cross-conditional matrix.

Tags: development, indicators, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Yemen: Acute Malnutrition

This dataset shows the IPC AMN analysis.  The IPC Acute Malnutrition (IPC AMN) classification was introduced in Yemen in 2020. However, due to limited data availability, the initial analysis relied on Mid-Upper Arm Circumference (MUAC) screening data and historical information. Overall, the trend shows a deterioration in the nutrition situation in the GoY areas, reflecting the worsening economy, rising food prices, long-term effects of conflict, chronic displacement, and limited access to basic services and infrastructure

Tags: global acute malnutrition-gam, severe acute malnutrition-sam
Organization: HDX
Flood: Hazard Data for Disaster Risk Assessment (selected countries)

Flood footprint of historical events at a 200m x 200m resolution based on the cloud to street database with events from years 2000-2018 (see https://floodbase.com). The events have been processed into one hazard dataset per country.



Tags: geodata, hazards and risk, humanitarian response plan-hrp, hxl
Organization: ETH Zürich - Weather and Climate Risks
Earthquakes: Hazard Data for Disaster Risk Assessment (selected countries)

Earthquake hazard sets at 150 arcsec (ca. 4km) resolution, available for the entire globe and per country. Available as historic records from the USGS epicentres database and as a simple probabilistic sampling starting from the historic earthquake catalog, with 9 synthetic events per historic record. The presented data are maximum intensity on the Modified Mercalli intensity scale (MMI) over the historic record 1904-2017.



Tags: geodata, hazards and risk, humanitarian response plan-hrp, hxl
Organization: ETH Zürich - Weather and Climate Risks
Afghanistan: Humanitarian Situation Monitoring (HSM) Round 5 KII (Analysis)

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. 
This round of HSM also seeks to complement the annual household-level 2023 Whole of Afghanistan Assessment, which assesses the multi-sectoral and sectoral needs of target populations in the Humanitarian Needs and Response Plan (HNRP), by filling in information gaps and enhancing response capacity for district-level prioritization.


Tags: displacement, education, food security, health, internally displaced persons-idp, markets, mental health, needs assessment, non-food items-nfi, protection, shelter, water sanitation and hygiene-wash
Organization: REACH Initiative
Philippines - TM Open Buildings

Thinking Machines Data Science is releasing TM Open Buildings, a dataset of manually-drawn building outlines covering 12 Philippine cities with detailed annotations on building and roof attributes as seen over satellite imagery. We contribute the buildings in OpenStreetMap and also made available for download in Kaggle. This is made possible with the support from the [Lacuna Fund](https://www.mapbox.com/maps/satellite).

Tags: demographics, facilities-infrastructure, geodata, openstreetmap
Organization: Thinking Machines Data Science
Venezuela  - Percentage of households in poverty and extreme poverty in from 2002 to 2021

Since 2017, the share of households living under the poverty line in Venezuela has been surpassing 90 percent. In addition, more than six out of every ten households (67.97 percent) lived in extreme poverty in 2021. The overall household poverty rate in Venezuela has registered a steady growth from 2014 to 2019, after having remained relatively stable, below 40 percent, since 2005. Although poverty is widespread among the population as a whole, some groups are more vulnerable than others. That is the case of younger generations and particularly children: 98.03 percent of Venezuelans aged 15 or younger lived in poverty in 2021.

Tags: poverty
Organization: OCHA Venezuela
Afghanistan - Who does What Where (July to September 2023)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://response.reliefweb.int/afghanistan/who-does-what-where-3w?_gl=1*g902oc*_ga*MTYyOTk1NDg4OC4xNjc2NTM2NTk3*_ga_E60ZNX2F68*MTcwNDE3NzMzMC4xNDAuMS4xNzA0MTg0MTQ5LjU4LjAuMA). 

Tags: hxl, operational capacity, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
Datos de conexiones de Facebook para diferentes países en Latinoamérica

iMMAP localiza a los refugiados y migrantes venezolanos en América Latina mediante el uso de la "Application Programming Interface (API)" de datos publicitarios de Facebook. Mostrando las conexiones de cuentas de usuarios de Facebook que muestra dónde vivían en su país de origen y ahora viven en el extranjero.
 
Los datos de la API de Facebook se recolectan cada 15 días. Las estimaciones que se presentan en este documento se obtienen utilizando filtros específicos y basándose en el comportamiento de los usuarios de Facebook durante los últimos 30 días.
 
Los estimados presentados no están diseñados para coincidir con censos u otras fuentes oficiales. Facebook no proporciona censos o estadísticas en línea sobre refugiados y migrantes. En consecuencia estas estimaciones deben considerarse como una fuente de datos que puede utilizarse para la triangulación y la identificación de tendencias. Facebook sólo proporciona información sobre determinados grupos de población (en este caso los expatriados venezolanos). No proporciona datos estadísticos o históricos.

Tags: demographics, migration, social media data
Organization: iMMAP Inc.
Central America Walking Time to Public Order Buildings by ACH-GIS4Tech

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.

Tags: governance and civil society, services, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America Walking Time to Main Markets by ACH-GIS4Tech

Average time needed to get from a municipality to the nearest main market (supermarket, hypermarket, market, municipal market, grocery shop 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.

Tags: markets, services, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America Walking Time to Main Healthcare Centers by ACH-GIS4Tech

Average time needed to get from a municipality to the nearest health centre (clinics, hospitals, outpatient clinics, health centres, 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.

Tags: health facilities, services, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Walking Time to Higher Education Centers by ACH-GIS4Tech

Average time needed to walk from a municipality to the nearest Higher Education Centre (University). 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.

Tags: education facilities-schools, services, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America - Total Capital Stock in Rural Locations

The total volume of physical productive assets available in a municipality is represented by the total stock of capital in the rural population. 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.

Tags: economics, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America Time to Reach Order Building by Vehicle by ACH-GIS4Tech

Average time needed to get from a municipality to the nearest law enforcement building ( police station, barracks, command post, etc.), using a motor vehicle. 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.

Tags: protection, services, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America Time Needed to Reach a Main Market by Vehicle by ACH-GIS4Tech

Average time needed to get from a municipality to the nearest main market (supermarket, hypermarket, market, municipal market, grocery shop etc.), using a motor vehicle. 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.

Tags: markets, services, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America Time Needed to Reach an Main Healthcare by vehicle by ACH-GIS4Tech

Average time needed to get from a municipality to the nearest health centre (clinics, hospitals, outpatient clinics, health centres, etc.) using a motor vehicle. 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.

Tags: health facilities, services, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America - Time to Reach Educational Centre by Vehicle

Average time needed to get from a municipality to the nearest Higher Education Centre (University) by motor vehicle. 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.

Tags: education facilities-schools, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America Road Ratio by ACH-GIS4Tech

Sum of the lengths of all roads in the locality divided by the km2 of territory of each municipality, in order to know the road connectivity and local economic development. Data obtained from HumData and transformed by GIS4Tech. 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.

Tags: development, roads, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America Public Order Buildings per 100k inhabitants

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.

Tags: governance and civil society, services, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Central America Protected Areas by ACH-GIS4Tech

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.

Tags: climate-weather, governance and civil society, socioeconomics
Organization: Acción contra el hambre - GIS4tech
Latin America and the Caribbean - Regional Refugee and Migrant Response Plan 2024

Full dataset of the RMRP 2024 Update, including activities, partners, population projections, people in need, and target estimates disaggregated by age and gender, population type at Admin 1 level. 
More info on the R4V website: https://www.r4v.info/en/data

Tags: affected population, demographics, funding, humanitarian response plan-hrp, migration, operational partners, operational presence, people in need-pin, refugees
Organization: Inter-Agency Coordination Platform for Refugees and Migrants from Venezuela
South Sudan: Inter-Sector Needs Assessment (ISNA) Summary Data

South Sudan Inter-Sector Needs Assessment (ISNA) data includes demographic and cluster indicator data (provided by ICCG clusters). Data disaggregated by cluster indicator, by counties and by population groups (IDPs, IDP-returnees, host-communities). The ISNA processes follow the IASC guided multi-sector Need assessment approach.  The ISNA process consists of qualitative and quantitative components.  IOM led the quantitative data collection and REACH led the qualitative data collection (qualitative data not included in this dataset).  Entire process ISNA process managed by the ISAN technical working group (TWG) consists of IOM, REACH and OCHA. OCHA provided the overall coordination and engagement with the ICCG as guided by the Humanitarian coordinator and the HCT. 

Tags: africa, camp coordination and camp management-cccm, complex emergency-conflict-security, education, food security, health, indicators, needs assessment, non-food items-nfi, nutrition, protection, shelter, water sanitation and hygiene-wash
Organization: OCHA South Sudan
Ethiopia - Somali Region IDP Sites Per Woreda

These datasets and maps show the number of IDP sites per woreda in the Somali region, using DTM Site Assessment Round 36 as a reference. These IDP sites include various settlement types: collective centers, dispersed settlements, host communities, planned camps, and spontaneous camps/sites. More detailed information can be found at the following link: https://dtm.iom.int/ethiopia#producttabs.

Tags: displacement, internally displaced persons-idp
Organization: 3iS
Ethiopia Displacement Data - Village Assessment [IOM DTM]

A village assessment survey (VAS) is a sub-component of mobility tracking. It collects data on returning IDPs, IDPs, returned migrants and host community members. VAS evaluates the absorption capacity of villages to receive returning IDPs with a focus on accessibility of services, livelihoods and reintegration.

Tags: demographics, displacement, hxl, internally displaced persons-idp, migration, needs assessment, population, returnees
Organization: International Organization for Migration (IOM)
Ethiopia - Populated Places GeoNames

This dataset represents populated places in Ethiopia at the locality level, including villages, kebeles, towns, and other administrative divisions. Each entry is associated with XY coordinates and is integrated with Ethiopian administrative boundaries. The data originates from the National Geospatial-Intelligence Agency (NGA) and is accessible through their GeoNames platform(https://geonames.nga.mil/geonames/GNSData/).The dataset includes various types of populated areas such as: villages, kebeles and towns. This dataset is crucial for various applications, including urban planning to assist in the development of infrastructure and services based on population distribution, for research, and on disaster management to support humanitarian efforts by identifying populated areas during crises.

Tags: populated places-settlements, population
Organization: 3iS
Antigua and Barbuda: Copernicus Global Human Settlement Layer (GHSL)

Open and free data for assessing the human presence on the planet.  
The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources.    
The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

Tags: facilities-infrastructure, populated places-settlements, population
Organization: Copernicus
French Southern Territories: Copernicus Global Human Settlement Layer (GHSL)

Open and free data for assessing the human presence on the planet.  
The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources.    
The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

Tags: facilities-infrastructure, populated places-settlements, population
Organization: Copernicus
Northeast Nigeria - Humanitarian Profile

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

Tags: affected population, baseline population, governance and civil society, hxl, internally displaced persons-idp, migration, returnees
Organization: OCHA Nigeria
American Samoa: Copernicus Global Human Settlement Layer (GHSL)

Open and free data for assessing the human presence on the planet.  
The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources.    
The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

Tags: facilities-infrastructure, populated places-settlements, population
Organization: Copernicus