AndreaBozzo/ceres-open-data-index huggingface dataset:
Uganda- Mukono District: Operational Presence

This dataset contains Who, What, Where and When (4W) data for the district of Mukono in Uganda. The operational presence of the various organisations (who) by sector (what), location (where) at the province level and when the information was collected (when). 

Tags: hxl, operational partners, operational presence, who is doing what and where-3w-4w-5w
Organization: Fields Data
Somalia Regions hit by 2012 Tropical Cyclone Murjan

<p>On October 25, 2012 Cyclonic Storm Murjan struck Bayla District of eastern Somalia, bringing heavy rainfall of over 40 mm (1.6 in) and gusty winds to the country and neighboring Ethiopia. This layer shows the occurence of TC Murjan in Bari Region.&nbsp;</p>

<p>TC Murjan formed over the south Arabian Sea in association with an active inter tropical convergence zone during last week of October 2012. It was the first cyclone over the north Indian Ocean during that year. Moving west southwestwards, it crossed Somalia coast between 1700 and 1800 UTC of 25th October near lat. 9.80N and long. 50.80E. &nbsp;Though the Ocean Heat Content was less over the southwest Arabian Sea (50-80 KJ/cm2) and further less near Somalia coast (less than 50 KJ/cm2) as well as SST (26-280C), the system could maintain its intensity of cyclonic storm till landfall, basically due to low to moderate vertical wind shear.</p>
<p>TC Murjan brougt heavy rainfalls to Somalia. This resulted to flash flooding which washed away livestock and bridges in Bari region, causing some fatalities. A total of 100,000 livestock died. Districts impacted in the region included Bossasso, Ishkushban, Bandar Beyla, Garowe and Eyl Districts.</p>

Tags: geodata, hazards and risk
Organization: IGAD Climate Prediction and Applications Center (ICPAC)
2013 Tropical Cyclone 03A Path

<p>This layer shows the movement path of Tropical Cyclone 03A. 2013 TC03A formed off the north-east coast of Somalia across the Indian Ocean, moving directly towards the coast of the country in the following days. The storm produced a wind speed of 74 kph (46 mph) and (100-200)mm of rain. It caused heavy rains with flooding and gale force winds in the Somali region of Puntland.</p>

<p>The cyclone caused loss of human lives and the destruction of assets including livestock and fishing boats, destroyed numerous settlements, service centers, roads, schools, communication and electrical installations. The most affected areas included, Dangorayo, Bandar Beyla, Garowe and Eyl districts. Other areas affected include the coastal villages in Bari region including Hafun, Iskushuban, Bargal, Qandala and Allula districts.&nbsp;</p>
<p>It was estimated that overall, 142,380 persons were affected by the disasters, with 8,523 households being worst hit and 1,435 households having lost all their livestock. It was also reported that there were approximately 80 deaths mostly of children and the elderly who were most vulnerable to hypothermia and exposure. Makeshift structures for pastoralists were conspicuously absent or just frames, likely destroyed or damaged by high winds and rains. Numerous water sources were flooded, no longer serviceable or contaminated in some areas. There were unconfirmed disease outbreaks and contamination of water sources from decaying animal remains. Thousands of livestock were reported dead as a consequence of icy rain, which was noted in the aerial assessment. FAO estimated 800,000 livestock were in the affected area. Anecdotal evidence suggested a less than 10 per cent survival rate for livestock in the hardest hit areas.</p>

Tags: flooding, geodata, hazards and risk
Organization: IGAD Climate Prediction and Applications Center (ICPAC)
Public Hospitals in Myanmar

Approximate centre point location dataset of public hospitals/hospital grounds in Myanmar as of 2020. Produced by CDE Myanmar based on publicly available reference lists and local knowledge and improving geographic coordinates using mostly large scale satellite/google satellite.

Spatial dataset created based on 1:5.000 - 1:2.000 scaled imagery. Smaller facilities often only be village location or best guess hospital-like looking features near the original coordinate/settlement.

Original dataset title: Public Hospitals in Myanmar as of 2020

Tags: geodata, health
Organization: Myanmar Information Management Unit (MIMU)
Uganda- Butaleja District: Operational Presence

This dataset contains Who, What, Where and When (4W) data for the district of Butaleja in Uganda. The operational presence of the various organisations (who) by sector (what), location (where) at the province level and when the information was collected (when). 

Tags: hxl, operational partners, operational presence, who is doing what and where-3w-4w-5w
Organization: Fields Data
Facebook Social Connectedness Index

We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) quantifies the relative probability that two individuals from different geographies are Facebook friends, providing a large-scale measure of social ties across regions.

This release updates the SCI with substantially expanded global coverage and finer geographic resolution, including new subnational units across 178 countries. Details on the underlying data and index construction are provided in the “The Social Connectedness Index.pdf.” A companion GitHub repository, available [here](https://github.com/social-connectedness-index/social-connectedness-index), provides code to generate maps from the SCI with minimal setup.

Citations for data: 

- Bailey, M., Cao, R., Kuchler, T., Stroebel, J., & Wong, A. (2018). "Social Connectedness: Measurement, Determinants, and Effects." Journal of Economic Perspectives, 32(3), 259--280. [(Paper available here)](https://pages.stern.nyu.edu/~jstroebe/PDF/JEP_SCI.pdf)

- Johnston, D., Kuchler, T., Kulkarni, M., & Stroebel, J. (2026). "The Social Connectedness Index." [(Paper available here)](https://pages.stern.nyu.edu/~jstroebe/PDF/JKKS_SCI.pdf)

Learn more [here](https://ai.meta.com/ai-for-good/datasets/social-connectedness-index/).

Tags: social media data
Organization: AI for Good at Meta
Sudan Emergency: New arrivals from Sudan

Following the outbreak of armed conflict in Sudan on 15 April 2023, large numbers of civilians have been forced to flee, including people who were already internally displaced because of previous conflicts in Sudan and refugees from other countries who had sought safety in Sudan. In addition to new internal displacement, hundreds of thousands of people, including Sudanese refugees and refugees of other nationalities hosted by Sudan have fled Sudan to neighbouring countries or returned home in adverse circumstances – notably to Chad, South Sudan, the Central African Republic, Egypt and Ethiopia.

UNHCR Operational Data Portal for the Sudan Situation: https://data.unhcr.org/en/situations/sudansituation

Tags: border crossings, complex emergency-conflict-security, forced displacement, refugees, returnees
Organization: UNHCR - The UN Refugee Agency
IOM Bangladesh - Needs and Population Monitoring (NPM)     Cox's Bazar Rohingya Refugees Settlements UAV Imagery

NPM Bangladesh has produced a number of tools based on its regular data collection activities and drone flights.

SW Map package: for mobile use, this enables users to visualize the site maps and boundaries on their own mobile. Together with the relevant files, users can also find a manual showing step by step how to copy files from their own computer to SW Map running on another portable device. 

KMZ file: for desktop use, this enables users to visualize the site maps and boundaries on Google Earth. By adding or removing layers, it is possible to visualize each location assessed by NPM Baseline 10. These files are available on HDX.

Historical UAV imagery of Rohingya settlements in Cox Bazar in GIS, KML Google Earth, Mbtiles (SW Maps), format. Updates of imagery will be added on top of the list.

NPM has also produced individual packages by camps: 
- Please click [here] {https://data.humdata.org/dataset/iom-bangladesh-npm-drone-imagery-and-gis-package-by-camp-sept-oct-2018} to access the data by camp as of September 2018.
- Please click [here](https://data.humdata.org/dataset/iom-bangladesh-needs-and-population-monitoring-npm-drone-imagery-and-gis-package-by-camp-august-2018) to access the data by camp as of August 2018.
- Please click [here](https://data.humdata.org/dataset/iom-bangladesh-needs-and-population-monitoring-npm-drone-imagery-and-gis-package-by-camp-july-2018) to access the data by camp as of July 2018.
- Please click [here](https://data.humdata.org/dataset/iom-bangladesh-needs-and-population-monitoring-npm-drone-imagery-and-gis-package-by-camp-june-2018) to access the data by camp as of June 2018.
- Please click [here](https://data.humdata.org/dataset/gis-pakages-may2018) to access the data by camp as of May 2018.
- Please click [here](https://data.humdata.org/dataset/data-and-resources-by-camps) to access the data by camp as of April 2018.


All majhee blocks shapefiles are also available at the following link:

- Please click [here](https://data.humdata.org/dataset/iom-bangladesh-needs-and-population-monitoring-npm-majhee-blocks-mapping) to access the most current majhee block shapefiles, as well as all historical versions.

Tags: displacement, geodata, needs assessment, refugee crisis, refugees
Organization: International Organization for Migration (IOM)
World Bank Indicators of Interest to the COVID-19 Outbreak

World Bank Indicators of Interest to the COVID-19 Outbreak.
This [link](https://datacatalog.worldbank.org/search?search_api_views_fulltext_op=AND&f%5B0%5D=field_collection_field%3A2026) is to a collection in the World Bank data catalog that contains datasets that may be useful for analysis, response or modelling.

Tags: baseline population, covid-19, elderly, health, water sanitation and hygiene-wash
Organization: World Bank Group
Health Facilities of Central African Republic

Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping.

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), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, health, health facilities
Organization: Humanitarian OpenStreetMap Team (HOT)
Populated Places of Central African Republic

Settlements and residential areas: named cities, towns, villages, suburbs, and residential land (`place=*` and `landuse=residential`). Useful for demographic context, settlement-level targeting, and population analysis.

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: [place](https://wiki.openstreetmap.org/wiki/Key:place), [landuse](https://wiki.openstreetmap.org/wiki/Key:landuse)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, populated places-settlements
Organization: Humanitarian OpenStreetMap Team (HOT)
Railways of Cameroon

Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context.

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: [railway](https://wiki.openstreetmap.org/wiki/Key:railway)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata, railways, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Health Facilities of Cameroon

Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping.

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), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, health, health facilities
Organization: Humanitarian OpenStreetMap Team (HOT)
Railways of Ethiopia

Railway lines and stations tagged `railway=*`: rail lines, tram tracks, and stations. Useful for transport accessibility analysis and basemap context.

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: [railway](https://wiki.openstreetmap.org/wiki/Key:railway)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata, railways, transportation
Organization: Humanitarian OpenStreetMap Team (HOT)
Sea Ports of Ethiopia

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)
Cultural Places of Madagascar

Cultural and historic places: museums, galleries, theatres, places of worship, monuments, and historic sites tagged via `tourism`, `amenity`, `historic`, or `heritage`. Useful for heritage protection, cultural mapping, and tourism context.

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: [tourism](https://wiki.openstreetmap.org/wiki/Key:tourism), [amenity](https://wiki.openstreetmap.org/wiki/Key:amenity), [historic](https://wiki.openstreetmap.org/wiki/Key:historic), [heritage](https://wiki.openstreetmap.org/wiki/Key:heritage)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata, points of interest-poi
Organization: Humanitarian OpenStreetMap Team (HOT)
Roads of Mali

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)
Financial Services of Haiti

Financial services: banks, ATMs, post offices, money transfer agents, and microfinance branches tagged via `amenity`. Useful for financial-inclusion mapping, cash-distribution planning, and economic analysis.

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)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: economics, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
Health Facilities of Madagascar

Health facilities: hospitals, clinics, pharmacies, doctors, and dentists tagged via `amenity` or `healthcare`. Useful for service-access analysis, emergency response, and healthcare gap mapping.

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), [healthcare](https://wiki.openstreetmap.org/wiki/Key:healthcare)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, health, health facilities
Organization: Humanitarian OpenStreetMap Team (HOT)
Populated Places of Madagascar

Settlements and residential areas: named cities, towns, villages, suburbs, and residential land (`place=*` and `landuse=residential`). Useful for demographic context, settlement-level targeting, and population analysis.

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: [place](https://wiki.openstreetmap.org/wiki/Key:place), [landuse](https://wiki.openstreetmap.org/wiki/Key:landuse)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, populated places-settlements
Organization: Humanitarian OpenStreetMap Team (HOT)
Sea Ports of Cameroon

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)
Sea Ports of Kenya

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)
Buildings of Central African Republic

Building footprints across the region: every feature tagged `building=*`, from residential homes to hospitals, schools, and places of worship. Useful for population estimation, damage assessment, and urban 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: [building](https://wiki.openstreetmap.org/wiki/Key:building)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: facilities-infrastructure, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
State of Palestine: Response Plan projects

Projects proposed, in progress, or completed as part of the annual State of Palestine Humanitarian Response Plans (HRPs) or other Humanitarian Programme Cycle plans. The original data is available on https://hpc.tools

**Important:** some projects in State of Palestine might be missing, and others might not apply specifically to State of Palestine. See _Caveats_ under the _Additional information_ tab.

Tags: humanitarian response plan-hrp, who is doing what and where-3w-4w-5w
Organization: OCHA Humanitarian Programme Cycle Tools (HPC Tools)
Somalia District hit by 2019 Tropical Cyclone Pawan

<p>2019 Tropical Cyclone Pawan struck Eyl and Qurdho Districts in Somalia. TC Pawan was intially named Tropical Storm 06A which originated from northern Indian Ocean. TC Pawan spread its clouds as far northwest as Oman and Yemen on its way to Somalia as observed by NASA Worldview, Earth Observing System Data and Information System (EOSDIS). It made landfall in Somalia on 7th December 2019 on the Coastal side of Puntland. The storm influenced Somalia's weather patterns. Heavy rain and wind gusts of 80 km/h were reported in the region.</p>
<p>Somali Water and Land Information Management (SWALIM) said some areas in Puntland recorded more than 3 times their long term mean annual rainfall during the storm. Eyl District recorded a total of 260mm in two days.</p>
<p>Villages struck by the storm include Dangorayo, Karkaar, Hafun, Iskushuban, Baargaal, Quandala and Alula in Bari Region.</p>

<p>2019 TC Pawan had adverse impacts on Somalia. It was reported that 35,600 households, representing a population of 213,600 people had been affected. 2 people died following floods in Las Qoray (Sanaag Region). Roads connecting the town to the rest of the region were damaged. In central Somalia, River Shabelle flooded displacing over 1,500 people.</p>
<p>Summary of impacts according to affected districts:</p>
<p>Eyl,Qardho, Qandala:</p>
<ol>
<li>People Affected: 213600 (35600 HH) i.e. pastoralists 15,000 HH, fishing communities 7500 HH, rural-urban settlements 11600 HH including IDPs, farmers 1500 HH</li>
<li>Household destroyed: 31500 (5250 households)</li>
</ol>
<p>&nbsp;</p>

Tags: geodata, hazards and risk
Organization: IGAD Climate Prediction and Applications Center (ICPAC)