AndreaBozzo/ceres-open-data-index huggingface dataset:
HDX HAPI Data for Senegal

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, economics, education, food security, funding, hazards and risk, health, indicators, markets, poverty, refugees, returnees
Organization: HDX Humanitarian API Data
Somalia Regions hit by 2020 Tropical Cyclone Gati

<p>Tropical Cyclone Gati originated from the Bay of Bengal. On 22 November 2020 at around 13:00 UTC, TC Gati became the strongest ever documented tropical storm to hit Somalia. Gati made landfall at Ras Hafun (Northeast of Somalia) with maximum sustained winds of 170Km/hr and was classified as a Category 2 storm (or category 2 hurricane on the Saffir-Simpson scale).</p>
<p>This layers shows the occurence of TC Gati in two regions of Somali, Sanaag and Bari Regions.</p>

<p>TC Gati primarily impacted parts of Bari region in Puntland State and then Sanaag region in Somaliland. Authorities reported rainfall totals from the storm to be greater than the amounts normally seen for the whole year. In a 24-hour period, Bosaso recorded 128mm of rain and Balidhidin 103mm. By 25<sup>th </sup>November 2020, TC Gati had dissipated but it left trail of destruction across Bari and Sanaag regions of Somalia.</p>
<p>Authorities estimated 180,000 people (30,000 households) had been affected in Puntland Regional State, with 42,000 people (7,000 households) displaced and at least eight people killed and unknown number injured, with considerable damages reported to infrastructure, livelihoods, and social services (telecommunication, electricity, roads, schools). Resultant flooding bursted the sewerage system and increased risk of diseases among the affected population. By the end of December, the storm had killed 9 people and over 63 000 livestock (sheep and goats), and affected around 183 000 people.&nbsp;</p>
<p>The heavy rains caused the Ceel-Daahir River in Puntland to flood, blocking vehicles from bringing crucial supplies. In some towns such as Xaafun, Hurdiye, and Karduush people reported losing their entire herds of livestock. There were also reports of the destruction of 120 fishing vessels in these areas resulting in the loss of livelihood for an estimated 460 fishermen.</p>
<p>&nbsp;</p>

Tags: geodata, hazards and risk
Organization: IGAD Climate Prediction and Applications Center (ICPAC)
Somalia Districts hit by 2015 Tropical Cyclone Chapala

<p>This layer show two Somalia Districts struck by 2015 Tropical Cyclone Chapala, Berbera and Bossaso Districts. On November 2, 2015 TC Chapala entered the Gulf of Aden in Somalia as the strongest tropical cyclone on record. 2015 TC Chapala prduced maximum wind speeds of 130knots. It brought rainfall in Northern Bari Region in Bossaso Districts.</p>
<p>The villages struck within the recorded districts include, Baargaal, Bander, Bareeda, Butiyaal, Caluula, Murcanyo, Qandalla, Xaabo, Biycad, Bulahar, Ceelsheik, Shacable, Xaafun.</p>

<p>According to a joint inter-agency rapid assessment more than 500 families (4,000 people) were affected by Tropical Cyclones Chapala and Megh, most affected lived in Gardaful Region, Puntland. No human loss of life was reported, but the rainfall and waves destroyed people&rsquo;s homes, washed fishing boats and nets, killed livestock (an estimated 3,000 sheep and goats, as well as 200 camels) and caused damage/destruction to public infrastructure including hospitals, roads and schools.</p>
<p>It was estimated that 4,000 people had been displaced, with 1,129 people being worst affected, having lost their homes and livelihoods (business, fishing boats, engines and nets), which were swept away by waves. It was reported that there had been extensive damage/destruction to people&rsquo;s livelihoods, with 80 per cent of villages in Alula and 60 per cent of villages in Af Kalahay Bareda, BiyoCade, Boolimoog, Dhurbo, Fagoora, Geesalay, Murcanyo, Murcanyo, Sayn Weyn, Sayn Yar, Toxiin and Xaabo experiencing loss of livestock and damage to crops and fisheries.</p>

Tags: geodata, hazards and risk
Organization: IGAD Climate Prediction and Applications Center (ICPAC)
HDX HAPI Data for Sudan

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, displacement, economics, education, food security, funding, hazards and risk, health, humanitarian needs overview-hno, indicators, internally displaced persons-idp, markets, migration, operational presence, people in need-pin, poverty, refugees, returnees, who is doing what and where-3w-4w-5w
Organization: HDX Humanitarian API Data
Kachin State Village Tract Boundaries MIMU v9.4

Polygons of Village Tract boundaries (Admin4) for the Kachin State, based on the latest MIMU Pcode version 9.4 . Place names from General Administration Department (GAD), are available in Myanmar Unicode. Transliteration in roman script by MIMU.

Place names are in line with the general cartographic practice to reflect the names of such places as designated by the host governments. The United Nations encourages authorities to review place names which include terms that may be viewed or perceived as derogatory.  

Tags: administrative boundaries-divisions, geodata
Organization: Myanmar Information Management Unit (MIMU)
2020 Tropical Cyclone Gati Path

<p>This layer shows the movement path of 2020 Tropical Cyclone Gati in Somalia. TC Gati originated from the Bay of Bengal and became the strongest ever documented tropical storm to hit Somalia. It made landfall at Ras Hafun (Northeast of Somalia) with maximum sustained winds of 170Km/hr and was classified as a Category 2 storm.</p>

<p>Tropical Cyclone Gati was the strongest storm ever recorded in the northern Indian Ocean and wreaked unimaginable damage on people and property. GATI left a trail of destruction across Bari and Sanaag regions of Somalia, disproportionately affecting coastal communities.</p>
<p>Authorities estimated about 180,000 people (30,000 households) to have been affected in Puntland Regional State, with 42,000 people (7,000 households) displaced and at least eight people killed and unknown number injured, with considerable damage reported to infrastructure, livelihoods, and social services (telecommunication, electricity, roads, schools).</p>
<p>Resultant flooding burst the sewerage system and increased the risk of diseases among the affected population. The worst hit areas were Baargaal, Foocaar, Garduush, Hurdiya, and Xaafuun, Foocaar, Garduush and Garan Hoose were worst hit villages in the Indian Ocean, Bosaso / Qandala in the Gulf of Aden, and Baarmadowe.&nbsp;</p>

Tags: geodata, hazards and risk
Organization: IGAD Climate Prediction and Applications Center (ICPAC)
Uganda- Tororo District: Operational Presence

This dataset contains Who, What, Where and When (4W) data for the district of Tororo 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
Rakhine State Village Tract Boundaries MIMU v9.4

Polygons of Village Tract boundaries (Admin4) for the Rakhine State, based on the latest MIMU Pcode version 9.4 . Place names from General Administration Department (GAD), are available in Myanmar Unicode. Transliteration in roman script by MIMU.

Place names are in line with the general cartographic practice to reflect the names of such places as designated by the host governments. The United Nations encourages authorities to review place names which include terms that may be viewed or perceived as derogatory. 

Tags: administrative boundaries-divisions, geodata
Organization: Myanmar Information Management Unit (MIMU)
Chin State Village Tract Boundaries MIMU v9.4

Polygons of Village Tract boundaries (Admin4) for the Chin State, based on the latest MIMU Pcode version 9.4 . Place names from General Administration Department (GAD), are available in Myanmar Unicode. Transliteration in roman script by MIMU.

Place names are in line with the general cartographic practice to reflect the names of such places as designated by the host governments. The United Nations encourages authorities to review place names which include terms that may be viewed or perceived as derogatory.  

Tags: administrative boundaries-divisions, geodata
Organization: Myanmar Information Management Unit (MIMU)
Populated Places of Burkina Faso

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)
Financial Services of Kenya

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)
Cultural Places of Lebanon

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)
HDX HAPI Data for Rwanda

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, economics, education, food security, funding, hazards and risk, health, indicators, markets, poverty, refugees, returnees
Organization: HDX Humanitarian API Data
Cultural Places of Cameroon

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)
Education Facilities of Central African Republic

Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation.

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


Tags: education facilities-schools, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
HDX HAPI Data for Russian Federation

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: climate-weather, conflict-violence, economics, food security, funding, hazards and risk, indicators, markets, refugees, returnees
Organization: HDX Humanitarian API Data
Financial Services of Madagascar

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)
Railways of Central African Republic

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)
HDX HAPI Data for Réunion

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: conflict-violence, indicators
Organization: HDX Humanitarian API Data
Education Facilities of Cameroon

Education facilities: schools, kindergartens, colleges, and universities tagged via `amenity` or `building`. Useful for school-access mapping, education planning, and resource allocation.

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


Tags: education facilities-schools, geodata
Organization: Humanitarian OpenStreetMap Team (HOT)
HDX HAPI Data for State of Palestine

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, conflict-violence, crisis-opt-israel-hostilities, economics, education, food security, funding, hazards and risk, health, indicators, markets, poverty, refugees, returnees
Organization: HDX Humanitarian API Data
Roads of Cameroon

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)
Buildings of Madagascar

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)
Waterways of Mali

Water features across the region: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental 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: [waterway](https://wiki.openstreetmap.org/wiki/Key:waterway), [water](https://wiki.openstreetmap.org/wiki/Key:water), [natural](https://wiki.openstreetmap.org/wiki/Key:natural)
- Part of the [exports grid on HDX](https://data.humdata.org/organization/hot/) by [HOT](https://www.hotosm.org/)


Tags: geodata, hydrology, rivers
Organization: Humanitarian OpenStreetMap Team (HOT)
HDX HAPI Data for Paraguay

This dataset contains data obtained from the
[HDX Humanitarian API](https://hapi.humdata.org/) (HDX HAPI),
which provides standardized humanitarian indicators designed
for seamless interoperability from multiple sources.
The data facilitates automated workflows and visualizations
to support humanitarian decision making.
For more information, please see the HDX HAPI
[landing page](https://data.humdata.org/hapi)
and
[documentation](https://hdx-hapi.readthedocs.io/en/latest/).


Tags: baseline population, climate-weather, conflict-violence, economics, education, food security, funding, hazards and risk, health, indicators, markets, poverty, refugees
Organization: HDX Humanitarian API Data
Populated Places of Mali

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)
Financial Services of Cameroon

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)