AndreaBozzo/ceres-open-data-index huggingface dataset:
Burkina Faso: Présence Opérationnelle

La Présence Opérationnelle (3W) est un ensemble de données pour la coordination humanitaire. Il est essentiel de savoir où les organisations humanitaires travaillent, ce qu'elles font et leurs capacités afin d'identifier les lacunes, d'éviter la duplication des efforts et de planifier une future réponse humanitaire. Cet ensemble de données comprend une liste des organisations humanitaires opérant au Burkina Faso au niveau Admin 3.


Tags: hxl, operational capacity, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Burkina Faso
Libya Displacement - [IDPs, Returnees] - Baseline Assessment [IOM DTM]

This datasets has IDPs, Household & Returnees data at Admin3 level gathered through DTM Mobility Tracking Assessment.

In the context of the political instability that has prevailed since the uprising in Libya (October 2011) and culminated in the collapse of a fragile central authority accompanied by fragmentation and infighting among myriads of militias, with continued fighting since the mid-2014 escalations, estimates indicate that the number of Internally Displaced Per-sons (IDPs) in Libya has exceeded 400,000 individuals, some eight percent of the total population (HNO, September 2015). While the country struggles to achieve and maintain stability, thousands of migrants are also taking journeys to and through Libya in a desperate bid to seek a better life in Europe. These migrants are exposed to risks of being trafficked and exploited while traveling through dangerous routes in deserts and territories controlled by different armed groups, as well as dying during attempts to cross the Mediterranean Sea.

However, there has been no standardized mechanism in place to verify and regularly update IDP and migrant numbers. Given that most humanitarian and international organizations operate remotely from Tunis since mid-July 2014 due to the deteriorating security situation, maintaining access to reliable and updated data on the humanitarian situation in Libya has been challenging.

Tags: affected population, demographics, displacement, geodata, hxl, internally displaced persons-idp, migration, populated places-settlements, returnees
Organization: International Organization for Migration (IOM)
Mozambique: COD Admin 0 geojson simplified geometries from gistmaps live service source

This dataset is of simplified geometries from COD live services deployed June 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and  based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is.

Tags: geodata
Organization: ITOS (inactive)
Guyana - Age and gender structures

Age and gender structures: WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in <a href="https://www.nature.com/articles/sdata20174"  target="_blank">Tatem et al</a>, and a description of the modelling methods used found in <a href="https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11"  target="_blank">Tatem et al</a> and <a href="https://www.nature.com/articles/sdata201789"  target="_blank">Pezzulo et al</a>. The '<i>Global per country 2000-2020</i>' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020 structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The '<i>individual countries</i>'  datasets represent older efforts to map population age and gender counts for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The '<i>whole continent</i>'  datasets are mosaics of the individual countries datasets.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076).

Tags: baseline population, demographics
Organization: WorldPop
Missing Migrants Project Data

Missing Migrants Project draws on a range of sources to track deaths of migrants along migratory routes across the globe. Data from this project are published in the report “Fatal Journeys: Tracking Lives Lost during Migration,” which provides the most comprehensive global tally of migrant fatalities since 2014.

##What is included in Missing Migrants Project data?
Missing Migrants Project counts migrants who have died at the external borders of states, or in the process of migration towards an international destination, regardless of their legal status. The Project records only those migrants who die during their journey to a country different from their country of residence.

Missing Migrants Project data include the deaths of migrants who die in transportation accidents, shipwrecks, violent attacks, or due to medical complications during their journeys. It also includes the number of corpses found at border crossings that are categorized as the bodies of migrants, on the basis of belongings and/or the characteristics of the death. For instance, a death of an unidentified person might be included if the decedent is found without any identifying documentation in an area known to be on a migration route. Deaths during migration may also be identified based on the cause of death, especially if is related to trafficking, smuggling, or means of travel such as on top of a train, in the back of a cargo truck, as a stowaway on a plane, in unseaworthy boats, or crossing a border fence. While the location and cause of death can provide strong evidence that an unidentified decedent should be included in Missing Migrants Project data, this should always be evaluated in conjunction with migration history and trends.

## What is excluded?
The count excludes deaths that occur in immigration detention facilities or after deportation to a migrant’s homeland, as well as deaths more loosely connected with migrants´ irregular status, such as those resulting from labour exploitation. Migrants who die or go missing after they are established in a new home are also not included in the data, so deaths in refugee camps or housing are excluded. The deaths of internally displaced persons who die within their country of origin are also excluded. There remains a significant gap in knowledge and data on such deaths. Data and knowledge of the risks and vulnerabilities faced by migrants in destination countries, including death, should not be neglected, but rather tracked as a distinct category.

Tags: asylum seekers, gender and age disaggregated data-gadd, migration, refugees
Organization: IOM Missing Migrants Project
Indicator 6.3.2: Proportion of bodies of water with good ambient water quality (percent)

Series EN_H2O_WBAMBQ: Proportion of bodies of water with good ambient water quality (%) Indicator 6.3.2: Proportion of bodies of water with good ambient water quality Target 6.3: By 2030, improve water quality by reducing pollution, eliminating dumping and minimizing release of hazardous chemicals and materials, halving the proportion of untreated wastewater and substantially increasing recycling and safe reuse globally Goal 6: Ensure availability and sustainable management of water and sanitation for all Release Version: 2018.Q2.G.01

Tags: geodata, sustainable development goals-sdg, water sanitation and hygiene-wash
Organization: Esri
EVD Cases by district

This data is made available from the WHO - Global Health Observatory.  Data on new probable and confirmed cases by epi week and district. There is a file for each country Liberia, Sierra Leone, and Guinea.

All the data from the countries can be found at:
 http://apps.who.int/gho/data/node.ebola-sitrep.ebola-country?lang=en

There are 2 values for each district. One is from the Ministry of Health SitRep. The other is from the patient database maintained in country. There is latency in getting the patient database is updated therefore the numbers are lower in the latest weeks. 


Tags: disease, health
Organization: World Health Organization
Dominican Republic - Subnational Edge-matched Administrative Boundaries

Dominican Republic administrative level 0-4 edge-matched gazetteer, shapefiles, geodatabase, and geoservice.

COD-EM datasets do not replace the authoritative [COD-AB available here](https://data.humdata.org/dataset/cod-ab-dom); however COD-EM datasets may be preferred for cartographic purposes.  See caveats.

These layers are suitable for database or GIS linkage to the [Dominican Republic - Subnational Population Statistics](https://data.humdata.org/dataset/cod-ps-dom) administrative level 0-2 tables using the ADM0, ADM1, and ADM2_PCODE fields.

Vetting by [Information Technology Outreach Services (ITOS)](https://www.uga.edu/) with funding from USAID.

Organization: OCHA Field Information Services Section (FISS)
Uganda Commercial Facilities

These are commercial centres of Uganda which include markets (daily,Weekly & Monthly types),Trading Centres and major shops.The layer was produced by UBOS between 2009 to 2012 under the National Census Mapping Programme.

 More detail about this dataset and more downloadable formats can be found here: http://ubos.geo-solutions.it/layers/geonode:commercial_facilities

Tags: facilities-infrastructure, geodata, markets
Organization: American Red Cross (inactive)
Geodata of Damage to Agricultural Fields, Gaza Strip - Occupied Palestinian Territory

This map illustrates satellite-detected changes in agricultural fields of the Gaza Strip resulting from ongoing violence in the area. Using a satellite image collected 30 July 2014 by the Landsat-8 satellite, and compared with a pre-crisis Landsat-8 image collected 7 July 2014, UNOSAT analyzed the Normalized Difference Vegetation Index for agricultural fields to locate areas of significant change. UNOSAT analysis indicates that ~2000 ha hectares of agricultural fields that have likely been razed or heavily damaged in the intervening period. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR/UNOSAT.

Tags: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Tropical cyclone: Hazard Data for Disaster Risk Assessment (selected countries)

Tropical cyclone wind footprints (m/s) at 150 arcsec (approx 4 kilometers at equator) resolution. Available as global files and per country; available for historically observed records, and synthetically created, probabilistic events, from various modelling sources, for present and future climate scenarios.



Tags: geodata, hazards and risk, humanitarian response plan-hrp, hxl
Organization: ETH Zürich - Weather and Climate Risks
Haiti - Windrow and Bin Composting Operational Data [SOIL]

This dataset includes operational data from SOIL’s CBS treatment system, from bin and windrow composting processes. There are eight tabs within the dataset as follows:

Tab title: Temperature
Description: This dataset includes the temperature (F) measured at six different points in the six windrow piles that were tested, with the number of the pile and date of the measure. It includes the minimum temperature reached for each pile and date in Celsius degree.
Time period: July 19, 2021 to February 25, 2022
Caveats or comments: A few data were corrected as indicated as comments in the dataset.

Tab title: pH conduct e. coli
Description: This dataset includes the pH and conductivity values, and the E. coli test results (positive or negative), measured for the six windrow piles that were tested, at multiple dates.
Time period: August 3, 2021 to February 22, 2022

Tab title: Maturing time
Description: This dataset includes the date the waste was emptied into the compost treatment process, and the date the compost was mature, for both bin and windrow processes. It includes the number of the pile and if the pile is from the bin or windrow process.
Time period: January 14, 2021 to May 9, 2022

Tab title: Containers emptied
Description: This dataset includes the number of 20L containers of waste emptied on the piles, for both bin and windrow processes. It includes the number of the pile and if the pile is from the bin or windrow process.
Time period: January 14, 2021 to December 8, 2021

Tab title: Weight compost
Description: This dataset includes the weight of compost produced in pounds per pile, for both bin and windrow processes. It includes the number of the pile and if the pile is from the bin or windrow process.
Time period: August 8, 2021 to May 9, 2022

Tab title: Volume water
Description: This dataset includes the volume of water in liter added to each pile, for both bin and windrow processes. It includes the number of the pile and if the pile is from the bin or windrow process.
Time period: January 14, 2021 to April 20, 2022

Tab title: Costs
Description: This dataset includes the number of households included in the service per month, and the direct and capex costs (USD) of the service per month for the bin and the windrow processes. It is used to calculate the cost of the service per household per month.
Time period: August 2021 to February 2022

Tab title: Windrow scale up
Description: This dataset includes the date the waste was emptied into the compost treatment process, and the date the compost was mature, for eleven windrow piles. It also includes the number of 20L containers of waste emptied on the piles, and the weight of compost produced in pounds per pile.
Time period: December 27, 2022 to April 4, 2024
Caveats or comments: This is data from the windrow composting scale up following the initial experiment.

Tags: environment, facilities-infrastructure, health, water sanitation and hygiene-wash
Organization: Sustainable Organic Integrated Livelihoods
COD Admin 1 Benin geojson simplified geometries from gistmaps live service source

This dataset is of simplified geometries from COD live services deployed August 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list: https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx


Tags: geodata
Organization: ITOS (inactive)
UNHCR Statistical Yearbook Data

This dataset contains data from UNHCR's comprehensive annual statistical yearbooks. The yearbooks are a rigorous review of refugee figures on that year. It also contains reviews on figures about asylum seekers, IDPs, and other population groups. 

Original reports are also available on [UNHCR's Statistical Yearbook website](http://www.unhcr.org/pages/4a02afce6.html).

Tags: internally displaced persons-idp, refugees, returnees
Organization: UNHCR - The UN Refugee Agency
Internally Displaced Persons Shelters in Maungdaw Township of Rakhine State in Myanmar

This map illustrates satellite-detected internally displaced persons shelters in the village tract of Nyaung Pin Gyi, Maungdaw Township, Rakhine State. Using satellite imagery collected on 6 November 2017 UNOSAT identified a total of 457 shelters in a beach area 7 km south of Maungdaw town, next to the mouth of the Naf River between Myanmar and Bangladesh. Several unidentified trucks are observed on the road located adjacent to the internally displaced persons settlement. As of 11 November 2017, 307 shelters were identified which represents a 33 percent decrease from 6 November. Additionally, several likely rafts are observed by the shoreline on 11 November 2017. Additional imagery analysis indicates this settlement began before 6 October and grew quickly, with shelters starting to decrease after 11 November as noted. A smaller camp is located 7 km southeast in the village tract of Ka Nyin Tan Alel Than Kyaw Ka Nyin Tan with approximately 200 shelters as of 11 November 2017. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.

Tags: complex emergency-conflict-security, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Mexico - Recursos en salud

Fuente: Secretaría de Salud, Dirección General de Información en Salud. Formato de captación: Plataforma web y formatos Excel. Periodicidad de actualización: Anual. Es o no información oficial: Es información oficial. Contenido de la base de datos: La base de datos contiene información de los establecimientos en salud (unidades médicas, establecimientos de apoyo y de asistencias social), con datos de ubicación geográfica y domiciliaria, institución y tipo de establecimiento. Uso e interpretación de la información publicada: Identificación de la infraestructura en salud instalada a nivel nacional, orientada a la prestación de servicios de salud. Descripción de los catálogos auxiliares: Se utiliza el catálogo CLUES, el catálogo de instrumental y equipo del Consejo de Salubridad General.

Tags: cyclones-hurricanes-typhoons, geodata
Organization: National Digital Strategy Unit at the Office of the President of Mexico (inactive)
Flood analysis for Myanmar (12 August 2015)

This is "Flood vectors - ALOS PALSAR (12 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 4,755 satellite detected water bodies with a spatial extent of 225.31 square kilometers derived from the ALOS PALSAR image ac...

Tags: geodata
Organization: United Nations Satellite Centre (UNOSAT)
COD Admin 1 Dem. Rep. of the Congo geojson simplified geometries from gistmaps live source

This dataset is of simplified geometries from COD live services deployed September 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list: https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx

Tags: geodata
Organization: ITOS (inactive)
COD Admin 1 geojson simplified geometries from gistmaps live service source

This dataset is of simplified geometries from COD live services deployed June 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list:  https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx

Tags: geodata
Organization: ITOS (inactive)
Flood analysis for Myanmar (10 August 2015)

This is "Flood vectors - TerraSAR-X (10 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 36,947 satellite detected water bodies with a spatial extent of 1,398.96 square kilometers derived from the TerraSAR-X image a...

Tags: geodata
Organization: United Nations Satellite Centre (UNOSAT)
Flood analysis for Myanmar (17 August 2015)

This is "Flood vectors - Radarsat-2 (17 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 17,249 satellite detected water bodies with a spatial extent of 1,052.18 square kilometers derived from the Radarsat-2 image a...

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
Flood analysis for Myanmar (10 July 2015)

This is "Flood vectors - Radarsat-2 (10 July 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 41,369 satellite detected water bodies with a spatial extent of 690,073.54 square kilometers derived from the Radarsat-2 image a...

Tags: geodata
Organization: United Nations Satellite Centre (UNOSAT)
Nepal Earthquake Topline Figures

Topline figures dataset for the Nepal Earthquake crisis page.

Figures for Number of People in Need of Assistance are sourced from the UN RCO (Nepal) [situation reports](https://www.humanitarianresponse.info/en/operations/nepal/documents/document-type/situation-report/organizations/united-nations-resident-coordinators-office/organizations/united-nations-office-coordination-humanitarian-affairs).



Tags: earthquake-tsunami, indicators
Organization: HDX
Flood analysis for Myanmar (06 August 2015)

This is "Flood vectors - Radarsat-2 (06 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 21,526 satellite detected water bodies with a spatial extent of 1,187.49 square kilometers derived from the Radarsat-2 image a...

Tags: flooding, geodata
Organization: United Nations Satellite Centre (UNOSAT)
West African Health Centres - 3 word addresses

We have provided the 3 word addresses of each health centre within the West African Region. 

what3words is a simple, real-time, location referencing system which solves many of the key logistical issues facing aid and humanitarian organisations, for whom street addresses, GPS co-ordinates, and other systems don't exist or are problematic.

Using words means non-technical people can find any location more accurately and most importantly, communicate it more quickly, more easily and with less ambiguity than any other system.

For more information, to get our API or batch encode your coordinates visit http://www.developer.what3words.com

Tags: africa, disease, geodata, health, health facilities, west africa
Organization: what3words (inactive)
Flood analysis for Myanmar (16 August 2015)

This is "Flood vectors - ALOS PALSAR (16 August 2015)" of the Flood analysis for Myanmar which began on 03 July 2015. It includes 4,739 satellite detected water bodies with a spatial extent of 750.49 square kilometers derived from the ALOS PALSAR image ac...

Tags: geodata
Organization: United Nations Satellite Centre (UNOSAT)
COD Admin 3 geojson simplified geometries from gistmaps live service source

This dataset is of simplified geometries from COD live services deployed June 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list: https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx

Tags: geodata
Organization: ITOS (inactive)