AndreaBozzo/ceres-open-data-index huggingface dataset:
Global - Subnational Administrative Boundaries (Historic)

Global administrative level 1-4 boundaries (COD-AB) dataset for 46 countries / territories, historic versions.  
  
This is an aggregation of [subnational administrative boundaries](https://data.humdata.org/dataset/?cod_level=cod-enhanced&res_format=GeoJSON) available in 3 variations:  
  
**Edge-Matched**: Subnational boundaries are aligned to fit international boundaries. This process results in simplification at the international border, but gaps and overlaps are eliminated. The internal resolution of each subnational boundary layer is not modified by this process. Recommended to use for most use cases.  
  
**Original**: Subnational boundaries are unmodified from their original source. There will be gaps and overlaps at the international border. Recommended if maintaining the integrity of the initial source is important.  
  
**Extended**: This is an intermediate step in the process before edge-matching. Recommended for organizations with specific international boundary needs.  
  
Metadata about sources used is also available as a table.  
  
A version of this dataset is also available with [latest boundaries](https://data.humdata.org/dataset/cod-ab-global).

Tags: administrative boundaries-divisions
Organization: HDX
Philippines - Earthquake on Jul 06 2026

**ADAM ID: **[sm\_us6000tadc](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_eq_events/items?uid=sm_us6000tadc)  Magnitude 5.8 earthquake at 35.0 depth occurred on Jul 06 2026 48km S of Sarangani. The epicentre of the earthquake was located at latitude 4.9886 longitude 125.326. It impacted 26037 people within 50km.    
    
WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

Tags: affected population, earthquake-tsunami, geodata
Organization: WFP Automated Disaster Analysis & Mapping
Myanmar - Agricultural Performance Survey (MAPS), Round 8

The Myanmar Agricultural Performance Survey (MAPS) is a nationwide phone-based panel survey of approximately 5,000 households designed to collect biannual data on farm characteristics, agricultural assets, cultivated area and crops planted, access to agricultural inputs, crop marketing, and constraints affecting agricultural activities. MAPS respondents are drawn as a sub-sample of the Myanmar Household Welfare Survey (MHWS), with the objective of achieving representativeness at the agro-ecological zone level. The survey is implemented twice annually—following the monsoon season and after the summer/dry season—and has completed eight rounds to date, beginning with Round 1 (February–March 2022, 4,553 observations) through Round 7 (August–October 2025, 4,845 observations). By generating high-frequency data on crop production and sales, input use, crop marketing, farm and livestock assets, and access to agricultural services, MAPS serves as an important monitoring instrument for assessing the agricultural sector in Myanmar amid overlapping challenges related to conflict, economic instability, and climate stressors.</p>

 MAPS Round 8 was implemented by phone by Myanmar Survey Research (MSR) between January and March 2026. The survey collected information on household characteristics, total cultivated area, crops grown, security-related challenges, input use, farm management practices, yields, sales, output prices, and marketing behavior. Round 6 focused specifically on the agricultural activities of crop farmers during the 2024/2025 dry season (post-/pre-monsoon period). </p>

The Round 8 sample was drawn primarily from respondents interviewed in MHWS Round 9 and supplemented with respondents from previous MAPS rounds until a total of 4,553 respondents was achieved.

Tags: agriculture-livestock, livelihoods, socioeconomics
Organization: International Food Policy Research Institute (IFPRI)
Myanmar - Agricultural Performance Survey (MAPS), Round 6

The Myanmar Agricultural Performance Survey (MAPS) is a nationwide phone-based panel survey of approximately 5,000 households designed to collect biannual data on farm characteristics, agricultural assets, cultivated area and crops planted, access to agricultural inputs, crop marketing, and constraints affecting agricultural activities. MAPS respondents are drawn as a sub-sample of the Myanmar Household Welfare Survey (MHWS), with the objective of achieving representativeness at the agro-ecological zone level. The survey is implemented twice annually—following the monsoon season and after the summer/dry season—and has completed eight rounds to date, beginning with Round 1 (February–March 2022, 4,553 observations) through Round 8 (January–March 2026, 4,553 observations). By generating high-frequency data on crop production and sales, input use, crop marketing, farm and livestock assets, and access to agricultural services, MAPS serves as an important monitoring instrument for assessing the agricultural sector in Myanmar amid overlapping challenges related to conflict, economic instability, and climate stressors.
</p>
MAPS Round 6 was implemented by phone by Myanmar Survey Research (MSR) between July and September 2024. The survey collected information on household characteristics, total cultivated area, crops grown, security-related challenges, input use, farm management practices, yields, sales, output prices, and marketing behavior. Round 6 focused specifically on the agricultural activities of crop farmers during the 2023/2024 dry season (post-/pre-monsoon period).
</p>
The Round 6 sample was drawn primarily from respondents interviewed in MHWS Round 7 and supplemented with respondents from previous MAPS rounds until a total of 4,740 respondents was achieved.

Tags: agriculture-livestock, socioeconomics
Organization: International Food Policy Research Institute (IFPRI)
Myanmar - Agricultural Performance Survey (MAPS), Round 7

The Myanmar Agricultural Performance Survey (MAPS) is a nationwide phone-based panel survey of approximately 5,000 households designed to collect biannual data on farm characteristics, agricultural assets, cultivated area and crops planted, access to agricultural inputs, crop marketing, and constraints affecting agricultural activities. MAPS respondents are drawn as a sub-sample of the Myanmar Household Welfare Survey (MHWS), with the objective of achieving representativeness at the agro-ecological zone level. The survey is implemented twice annually—following the monsoon season and after the summer/dry season—and has completed eight rounds to date, beginning with Round 1 (February–March 2022, 4,553 observations) through Round 8 (January–March 2026, 4,553 observations). By generating high-frequency data on crop production and sales, input use, crop marketing, farm and livestock assets, and access to agricultural services, MAPS serves as an important monitoring instrument for assessing the agricultural sector in Myanmar amid overlapping challenges related to conflict, economic instability, and climate stressors.</p>

MAPS Round 7 was implemented by phone by Myanmar Survey Research (MSR) between August and October 2025. The survey collected information on household characteristics, total cultivated area, crops grown, security-related challenges, input use, farm management practices, yields, sales, output prices, and marketing behavior. Round 6 focused specifically on the agricultural activities of crop farmers during the 2024/2025 dry season (post-/pre-monsoon period).</p>

The Round 7 sample was drawn primarily from respondents interviewed in MHWS Round 9 and supplemented with respondents from previous MAPS rounds until a total of 4,845 respondents was achieved.

Tags: agriculture-livestock, livelihoods, socioeconomics
Organization: International Food Policy Research Institute (IFPRI)
Ethiopia - The Effects of a Secondary School Scholarship on School Progression and Youth Outcomes: Endline Survey

This dataset contains responses from 2,005 youth and their households collected through the endline survey of the randomized controlled trial (RCT) study, The Effects of a Secondary School Scholarship on School Progression and Youth Outcomes, conducted in rural Ethiopia. The study examines the impact of providing secondary school scholarships to youth from the poorest households in relatively remote and food-insecure kebeles on school enrollment, educational progression, and a range of non-academic outcomes.</p>

The follow-up survey was conducted between June and July 2025, approximately 28 months after the <a href="https://doi.org/10.7910/DVN/DOVZNY">baseline survey</a>. Data were collected on educational attainment and progression, participation in economic activities, marriage and family formation, non-cognitive skills, and educational aspirations. To minimize attrition, the survey team extensively tracked participants who had migrated to urban areas within the study regions or to Addis Ababa.</p>

The endline survey successfully interviewed 2,005 youth, resulting in an attrition rate of approximately 6 percent. The dataset provides evidence on the effectiveness of scholarship support in improving educational and life outcomes among vulnerable youth in rural Ethiopia.</p>

Tags: africa, eastern africa, education, education facilities-schools, poverty, socioeconomics, youth
Organization: International Food Policy Research Institute (IFPRI)
Global - Subnational Administrative Boundaries

Global administrative level 1-4 boundaries (COD-AB) dataset for 111 countries / territories, latest versions.  
  
This is an aggregation of [subnational administrative boundaries](https://data.humdata.org/dataset/?cod_level=cod-enhanced&res_format=GeoJSON) available in 3 variations:  
  
**Edge-Matched**: Subnational boundaries are aligned to fit international boundaries. This process results in simplification at the international border, but gaps and overlaps are eliminated. The internal resolution of each subnational boundary layer is not modified by this process. Recommended to use for most use cases.  
  
**Original**: Subnational boundaries are unmodified from their original source. There will be gaps and overlaps at the international border. Recommended if maintaining the integrity of the initial source is important.  
  
**Extended**: This is an intermediate step in the process before edge-matching. Recommended for organizations with specific international boundary needs.  
  
Metadata about sources used is also available as a table.  
  
A version of this dataset is also available with [historic boundaries](https://data.humdata.org/dataset/cod-ab-global-historic).  
  
For a list of P-codes for use in data collection such as ODK / Kobo, see [Global P-code List](https://data.humdata.org/dataset/global-pcodes)

Tags: administrative boundaries-divisions, crisis-greater-middle-east
Organization: HDX
Afghanistan - Flow Monitoring Counting (Since January 10, 2024 To July 04, 2026)

DTM Flow Monitoring, conducted by IOM Afghanistan, is designed to provide insights into the mobility patterns at Afghanistan’s border points with the Islamic Republic of Iran and Pakistan. 

It is important to note that DTM collects information on total movements at a given border point, not the number of unique individuals entering or leaving the country. As a result, if one individual both left and re-entered Afghanistan during the reporting period, this would count as one outflow movement and one inflow movement.

DTM FM is operational at four main crossing points (connected to Afghanistan’s National Highway) as well as six other crossing points with Islamic Republic of Iran and Pakistan.

Tags: hxl, migration
Organization: International Organization for Migration (IOM)
Venezuela - Network Coverage Maps

This map shows the density of 3G network coverage availability across areas in Venezuela affected by the June 25, 2026 Earthquake.

Please request access to this dataset by clicking the “Request data” below or by filling out the [**Request form**](https://ai.meta.com/ai-for-good/request-access/?dataset=1245666557377973)

**Note**: Only universities, nonprofits, and IGOs like the UN are eligible to use controlled-access datasets. This dataset is governed by AI for Good at Meta's time-limited retention policies and will be deleted one month after its release.

Tags: affected population, crisis-venezuela-earthquake, geodata
Organization: AI for Good at Meta
Syrian Arab Republic: Operational Presence

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working and what they are doing to identify gaps and plan for future humanitarian response. The datasets before 2025 were incomplete and did not cover the entire country.

Tags: hxl, operational capacity, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Syria
Venezuela Earthquakes: Damage Assessment using Sentinel-1 radar data

This dataset provides a rapid experimental Sentinel-1-based damage assessment product for the broader impacted area from the 24 June 2026 Venezuelan earthquakes. It includes both the entire analyzed area of the SAR analysis and the Overture Maps building footprints identified as likely damaged. 

This SAR product estimates 81,437 likely damaged buildings across the analyzed impacted area.

This preliminary damage proxy product is intended to support rapid screening and prioritization, targeting of follow-up assessment, triangulation with VHR optical and radar images, and other damage assessments and products.


Tags: crisis-venezuela-earthquake, damage assessment, earthquake-tsunami
Organization: REACH Initiative
Syria: Breast Cancer Quantitative Study

Primary data collected from routine medical data at SAMS idlib oncology hospital between 2017-2022 , shared in association with a research paper published in Avicenna Journal of Medicine :

https://www.sciencedirect.com/science/article/pii/S0277953624008189?via%3Dihub


Tags: affected population, health, women
Organization: Syrian American Medical Society
Viet Nam - Tropical storm on Jul 01 2026

**ADAM ID: **[1001281\_13](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_ts_events/items?event_id=1001281)  Tropical storm during the period Jul 01 2026-Jul 04 2026 in Viet Nam, China, Laos. The center of the storm was located near latitude 21.6 longitude 107.9.    
    
WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

Tags: affected population, cyclones-hurricanes-typhoons, geodata
Organization: WFP Automated Disaster Analysis & Mapping
Indonesia - Earthquake on Jul 03 2026

**ADAM ID: **[sm\_us6000t9r5](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_eq_events/items?uid=sm_us6000t9r5)  Magnitude 6.2 earthquake at 120.932 depth occurred on Jul 03 2026 33km W of Danau. The epicentre of the earthquake was located at latitude 1.8205 longitude 127.4916. It impacted 101523 people within 50km.    
    
WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

Tags: affected population, earthquake-tsunami, geodata
Organization: WFP Automated Disaster Analysis & Mapping
Afghanistan - Earthquake on Jul 01 2026

**ADAM ID: **[sm\_us6000t9gg](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_eq_events/items?uid=sm_us6000t9gg)  Magnitude 5.5 earthquake at 216.694 depth occurred on Jul 01 2026 39km W of Yamgan. The epicentre of the earthquake was located at latitude 36.5317 longitude 70.4468. It impacted 251950 people within 50km.    
    
WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

Tags: affected population, earthquake-tsunami, geodata
Organization: WFP Automated Disaster Analysis & Mapping
Papua New Guinea - Earthquake on Jun 30 2026

**ADAM ID: **[sm\_us6000t978](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_eq_events/items?uid=sm_us6000t978)  Magnitude 5.4 earthquake at 35.0 depth occurred on Jun 30 2026 20km W of Guama. The epicentre of the earthquake was located at latitude -5.727 longitude 150.9338. It impacted 44475 people within 50km.    
    
WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

Tags: affected population, earthquake-tsunami, geodata
Organization: WFP Automated Disaster Analysis & Mapping
GRID3 COD - Ituri - Geospatial Data Layers

The GRID3 COD–Ituri Geospatial Data Layers 20260629 data package provides geospatial layers for Ituri Province, Democratic Republic of the Congo, including:

    Settlement names
    Health facilities
    Health zones
    Health areas

This data package supersedes the earlier GRID3 COD–Ituri Geospatial Data Layers 20260611 version for health areas, health facilities, health zones, and settlement names layers for Ituri Province only. It does not supersede versions of these layers for other provinces or geographies.

This dataset may contain unintended omissions. It was developed under a compressed timeline to enable timely information sharing and to support teams engaged in emergency response efforts. 

Dataset citation:
Center for Integrated Earth System Information Network (CIESIN), Columbia University, Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of the Congo, and GRID3. 2026. GRID3 COD - Ituri - Geospatial Data Layers 20260629. New York: Columbia University. [URL here] Accessed [DAY MONTH YEAR].

Contacts and data queries: 
The authors welcome feedback on the data, including suggestions, reports of errors or omissions, difficulties using the data, and format preferences. For dataset-related questions, please contact: info@ciesin.columbia.edu.

Tags: crisis-ebola-bundibugyo-virus-disease, geodata, health facilities, populated places-settlements
Organization: GRID3
Children's Climate Risk

The [Children’s Climate Risk report](https://data.unicef.org/resources/childrens-climate-risk-report-2026/) and dataset (2026) provides the most detailed global picture to date of where children face the greatest climate. It establishes a global evidence base for child-centric climate risk analysis. This version includes data from the newly released Global Child Hazard Database, with updated data and models covering a broader range of hazards for most countries and territories and utilizes a pixel-level multi-hazard approach.

Key hazards analyzed include:

- Climate hazards: riverine floods, coastal floods, droughts (agricultural and meteorological), tropical storms, heatwaves, extreme heat, fires, sand and dust storms
- Climate-sensitive hazards: vector-borne diseases (malaria) and air pollution

Tags: children, climate hazards, hazards and risk
Organization: UNICEF Data and Analytics (HQ)
Pakistan - Earthquake on Jun 27 2026

**ADAM ID: **[sm\_us6000t8le](https://api.adam.geospatial.wfp.org/api/collections/adam.adam_eq_events/items?uid=sm_us6000t8le)  Magnitude 5.4 earthquake at 10.0 depth occurred on Jun 27 2026 53km NW of Rakhni. The epicentre of the earthquake was located at latitude 30.4545 longitude 69.6859. It impacted 111709 people within 50km.    
    
WFP’s Automated Disaster Analysis and Mapping (ADAM) system is an operational system for collecting, analysing and mapping geospatial and socio-economic information following sudden onset humanitarian emergencies.

Tags: affected population, earthquake-tsunami, geodata
Organization: WFP Automated Disaster Analysis & Mapping
Roads of Cuba

Road network across the region tagged `highway=*`: motorways, residential streets, service roads, footways, and trails. Useful for routing, accessibility analysis, and evacuation planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [highway](https://wiki.openstreetmap.org/wiki/Key:highway)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, roads, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Airports of Chile

Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [aeroway](https://wiki.openstreetmap.org/wiki/Key:aeroway), [building](https://wiki.openstreetmap.org/wiki/Key:building), [emergency](https://wiki.openstreetmap.org/wiki/Key:emergency)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: aviation, facilities-infrastructure, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Airports of Congo

Airports and aviation infrastructure: airports, heliports, helipads, runways, terminals, and emergency landing sites tagged via `aeroway`, `building`, or `emergency`. Useful for logistics, evacuation routing, and aerial-response planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [aeroway](https://wiki.openstreetmap.org/wiki/Key:aeroway), [building](https://wiki.openstreetmap.org/wiki/Key:building), [emergency](https://wiki.openstreetmap.org/wiki/Key:emergency)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: aviation, facilities-infrastructure, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Sea Ports of Eritrea

Sea ports and ferry terminals tagged via `amenity`, `building`, or `port`. Useful for maritime logistics, supply-chain analysis, and coastal access planning.

Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge.

- Source: [OpenStreetMap](https://www.openstreetmap.org), a free, collaborative world map
- Tags: [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [building](https://wiki.openstreetmap.org/wiki/Key:building), [port](https://wiki.openstreetmap.org/wiki/Key:port)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata, ports
Organization: Humanitarian OpenStreetMap Team (HOT)