AndreaBozzo/ceres-open-data-index huggingface dataset:
Sudan: 2021 HRP-Response Monitoring (4Ws)

The data set contains the number of people in need, people targeted and people reached by humanitarian assistance in Sudan during the period January-December 2021.It contains the overall reached and the sector breakdowns too. The data is provided by admin 2 level.

Tags: education, food security, health, hxl, nutrition, people in need-pin, protection, who is doing what and where-3w-4w-5w
Organization: OCHA Sudan
Humanitarian Access Dataset

ACAPS' Humanitarian Access Dataset puts together all the pieces of information on Humanitarian Access Constraints of the first half of 2021.
The report resulting from this dataset is the Humanitarian Access Overview, which outlines how access to humanitarian assistance continues to be restricted for crisis-affected populations in more than 60 countries.

Data from the dataset is coded according to access dimensions, indicators and sub-indicators, then scored on a 0 to 5 severity scale.

The dataset displays:

- data collected, coded in "log" tab with its "data dictionary"
- aggregation of data by country, scored per "indicator"
- country scores (pillars, overall access score and information gaps) in "Scores" tab
- gis compatible clean tab with ISO codes


According to this data, we identified the following:

Extreme access constraints (Level 5) for: Eritrea, Libya, Syria, Yemen.

Very high access constraints (Level 4) for: Afghanistan, Bangladesh, Cameroon, Democratic Republic of Congo (DRC), Ethiopia, Iraq, Mali, Myanmar, Nigeria, Palestine, Somalia, South Sudan, Venezuela.

High access constraints (Level 3) for: Azerbaijan, Burkina Faso, Central African Republic (CAR), Chad, Colombia, Democratic People’s Republic of Korea (DPRK), Honduras, India, Iran, Lebanon, Mozambique, Nicaragua, Niger, Pakistan, Sudan, Turkey, Ukraine.

For more information, download the dataset.
To access ACAPS' Humanitarian Access Overview, please visit: https://www.acaps.org/en/thematics/all-topics/humanitarian-access


Tags: displacement, geodata, humanitarian access, hxl, indicators, people in need-pin
Organization: ACAPS
Sudan: 2022 HRP-Response Monitoring (4Ws)

The data set contains the overall and sectors' people in need, people targeted and people reached by humanitarian assistance in Sudan  during the period January-June 2022 broken down by admin 1 and admin 2 levels.

Tags: education, food security, gender-based violence-gbv, health, hxl, non-food items-nfi, nutrition, people in need-pin, protection, shelter, water sanitation and hygiene-wash, who is doing what and where-3w-4w-5w
Organization: OCHA Sudan
Martinique - Subnational Population Statistics

Martinique administrative level 0 (territory), 1 (arrondissement), and 2 (commune) 2016 sex and age dissaggregated population statistics

REFERENCE YEAR:  2016

These tables are suitable for database or GIS linkage to the [Martinique administrative level 0-2 boundaries](https://data.humdata.org/dataset/cod-ab-mtq).

Version history:
17 February:  Update from IGN
 9 September 2017:  Initial upload from www.gadm.org


Tags: baseline population, gazetteer
Organization: OCHA Latin America and the Caribbean (ROLAC)
Grenada - Subnational Population Statistics

Grenada administrative level 0-1 2011 sex and age disaggregated population statistics

REFERENCE  YEAR:   2011

These tables are suitable for database or GIS linkage to the [Grenada - Subnational Administrative Boundaries](https://data.humdata.org/dataset/cod-ab-grd).

Tags: baseline population, gazetteer
Organization: OCHA Latin America and the Caribbean (ROLAC)
Nigeria Displacement - [IDPs] - Location Assessment [IOM DTM]

DTM location assessment is to collect data on population presence in defined locations identified through the baseline area assessment. The assessment identifies where people are living and informs targets sites for more detailed site assessments.

To get the complete data of the assessment round, kindly download the corresponding Site Assessment data here: https://data.humdata.org/dataset/nigeria-site-assessment-data.

Tags: complex emergency-conflict-security, displacement, hxl, internally displaced persons-idp, migration
Organization: International Organization for Migration (IOM)
Madagascar Displacement Data - Baseline Assessment - Drought in Grand Sud [IOM DTM]

The Grand Sud of Madagascar has been affected by consecutive droughts during the rainy seasons from 2019 to 2021. In 2021, 36% of the Grand Sud was classified as severe drought and 1% as extreme drought. Nearly 1.47 million people were severely food insecure (IPC 3+) and four districts – Amboasary Atsimo, Ambovombe Androy, Tsihombe and Ampanihy West – were in IPC Phase 4 (Emergency).

Tags: displacement, drought, hxl, internally displaced persons-idp, migration, returnees
Organization: International Organization for Migration (IOM)
Health Facilities in Sub-Saharan Africa

This master list of health facilities was developed from a variety of government and non-government sources from 50 countries in sub-Saharan Africa. It uses multiple geocoding methods to provide a comprehensive spatial inventory of 98 745 public health facilities. Each data record represents a health facility and has 8 descriptive variables – Location identifiers including: country, first level administrative division, latitude, longitude and LL source (source of the coordinates). Coordinates are rounded off to four decimal places for uniformity, allowing an accuracy of 5–10 metres in decimal degrees coordinate format. 

This geocoded master facility list has been made publicly and freely available through both the [figshare repository](https://ndownloader.figshare.com/files/14379593) and through the [World Health Organization’s Global Malaria Programme](https://www.who.int/teams/global-malaria-programme) in Microsoft Excel format.



Tags: facilities-infrastructure, geodata, health, health facilities
Organization: HDX
Barbados - Subnational Population Statistics

Barbados administrative level 0 sex and age disaggregated 2022 projected population statistics

REFERENCE YEAR:  2022

This table is suitable for database or GIS linkage to the [Barbados administrative level 0 (national) and 1 (parish) boundary polygons and lines](https://data.humdata.org/dataset/cod-ab-brb) using the ADM0_PCODE field.

Tags: baseline population, gazetteer
Organization: OCHA Latin America and the Caribbean (ROLAC)
Colombia: People in Need (PiN) del Clúster en Seguridad Alimentaria y Nutrición (SAN-SP)

Esta base de datos contiene los cálculos de People in Need (PiN) del Clúster de Seguridad Alimentaria y Nutrición realizados en el marco del Ciclo de Programación Humanitaria de Colombia para 2023. El PiN  se calcula a partir de la información disponible del % de población en inseguridad alimentaria y de las prevalencias de desnutrición aguda y bajo peso al nacer. En la estimación, se prioriza una parte de la población con inseguridad alimentaria moderada y la totalidad de la severa en las zonas del país en donde se reportan las mayores brechas poblacionales y de acceso. La población con necesidades en SAN es menor que el % de población en inseguridad alimentaria y de desnutrición aguda/bajo peso.

Tags: food security, hxl, nutrition, people in need-pin
Organization: OCHA Colombia
Colombia: Desnutrición Aguda Infantil

Esta base cuenta con el número de casos de desnutrición aguda en niños y niñas menores de 5 años por departamentos de manera acumulada hasta la semana 48 del 2022, también incluye el número de casos de Bajo peso al nacer y las prevalencias respectivamente.
 

Tags: hxl, malnutrition, severe acute malnutrition-sam
Organization: OCHA Colombia
Georeferenced Sectorial data for Sotik and Chepalungu Subcounties of  Bomet  County

This is primary data collected using kobo toolbox in the two sub-counties for data readiness support in the Community Epidemic and Pandemic Preparedness (CP3) Program. Involved in the data collection are mainly; the Community Health Volunteers, the administration team, and the Animal Health Assistants.

Tags: agriculture-livestock, education facilities-schools, health, health facilities, trade, transportation, water sanitation and hygiene-wash
Organization: International Federation of Red Cross and Red Crescent Societies (IFRC)
Honduras: Humanitarian Needs Overview

This data has been produced by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) on behalf of the Humanitarian Country Team and partners. The data provides the Humanitarian Country Team’s shared understanding of the crisis, including the most pressing humanitarian need and the estimated number of people who need assistance. It represents a consolidated evidence base and helps inform joint strategic response planning. 

Tags: humanitarian needs overview-hno, people in need-pin
Organization: OCHA Latin America and the Caribbean (ROLAC)
OCHA Global Humanitarian Operational Presence Who, What, Where (3W) Portal

Raw Global 3W national data visualized in the [Global Humanitarian Operational Presence Who, What, Where (3W) Portal](https://3w.unocha.org/) as of  08  June 2023.

Fields:

  'country code' -- example 'UKR' for Ukraine

'sector' -- example 'CCCM' = Camp Coordination / Management

 'organization' -- Organization name provided in the field inputs

  'type' -- INGO (International NGO), NNGO (National NGO), UN (United Nations), 'Undefined', or 'Other'

  'COVID 19' -- 'yes' / 'no' (pertaining to the context): Field DISCONTINUED as of November 2021!!!!

  '3W date' -- date of data applicability

  'Display Name' -- Organization name - standardized as much as possible

 
Note these intended to be cleaned and standardized, though language variations (such as "Acción Contra el Hambre" / "Action Against Hunger" / "Action Contre La Faim"), and national offices of international organizations (such as "Caritas Internationalis - Nigeria" / "Caritas Internationalis - Switzerland") are preserved.  

     
Note also that the names of some organizations working in Protection have been suppressed.
Users with questions are encouraged to use the 'Contact the contributor' button below.

Tags: hxl, who is doing what and where-3w-4w-5w
Organization: OCHA Field Information Services Section (FISS)
Global Humanitarian Overview 2023

As of mid-June 2023, the Global Humanitarian Overview requires $54.8 billion to assist 249 million of the 362 million people in need. The GHO is made up of 26 Humanitarian Response Plans (HRP), nine regional plans, five Flash Appeals, and other types of plans. Requirements this year are around $8.4 billion more compared to the mid-year point in 2022, representing an increase of 18 per cent, which is smaller than the almost 30 per cent increase experienced in the first semester of 2022.

Donors have provided $10.7 billion as of mid-year for the GHO plans, which represents 20 per cent of the total required this year. This is the same as the 20 per cent coverage in both mid-June of 2021 and 2022. However, coverage of the plans in the GHO varies widely. Twenty-five out of 43 inter-agency response plans (58 per cent) are currently funded below the global average of 20 per cent. This is about the same percentage as in 2022 and 2021, suggesting that the imbalance in funding coverage for appeals remains a protracted problem. In absolute terms, Afghanistan (- $950 million), Ukraine (- $600 million) and Syria ( - $60 million) have seen the sharpest decreases in funding compared to the same time last year. Conversely, the following plans have seen increases in both absolute funding and coverage compared to the same time last year: Burkina Faso, Burundi, DRC, El Salvador, Haiti,
Mali, Mozambique, Myanmar, Niger, Nigeria, Somalia, and South Sudan.

The gap between financial requirements and resources currently stands at $43 billion – the highest ever. This is more than double the entire requirements of the GHO ($20 billion) in 2016.

An additional $4.4 billion of humanitarian funding has been channelled outside the GHO, bringing total humanitarian funding to $15 billion. This is about the same as the $15 billion reported by donors and humanitarian partners at the same period last year.

More comparisons and trends can be found in the pages that follow. As always, trends at mid-year are indicative and the situations in countries and regions can fluctuate due to unforeseen disasters or the deterioration of existing crises.

Tags: funding, hxl, people in need-pin
Organization: OCHA HQ
Nigeria Displacement - [IDPs] - Baseline Assessment [IOM DTM]

Data set has IDPs, Households, geographic locations and reasons of displacement etc.
In response to the need for accurate information on internally displaced persons (IDPs) in Nigeria, the International Organization
for Migration (IOM) began implementing the Displacement Tracking Matrix (DTM) project in July 2014. The project is supporting
the Government of Nigeria and other humanitarian response partners to conduct IDPs assessments in a systematic way as well as
to establish a profile of the IDP population.

Tags: baseline population, complex emergency-conflict-security, displacement, hxl, internally displaced persons-idp, migration
Organization: International Organization for Migration (IOM)
Ethiopia Displacement - [IDPs] - Site Assessment - Tigray - [IOM DTM]

In early November 2020, conflict broke out in the north of Ethiopia and this has displaced many from their homes. From 11 December — 14 January 2021, the Displacement Tracking Matrix (DTM) deployed its Emergecny Site Assessment to capture internal displacement related to the Northern Ethiopia Crisis. This multisectoral location assessment assesses the number of internally displaced persons (IDPs) and collects basic information on the multisectoral needs of IDPs at site level. 

Tags: hxl, internally displaced persons-idp
Organization: International Organization for Migration (IOM)
CCCM Cluster Somalia: List of IDP sites in Somalia

The updated master list of IDP sites contains estimated population data, GPS coordinates, names of neighborhoods/umbrellas (sub-district locations) and unique codes for each verified site. Additionally, the Q1-2023 master list includes IDP sites/populations for proposed catchment areas located in Baidoa and Mogadishu to better enable the formulation of an area-based approach to humanitarian service delivery.

When possible, the CCCM Cluster urges partners to ensure that the names of IDP sites used by agencies are matching with that of the CCCM Cluster’s IDP Site Master List.

Tags: camp coordination and camp management-cccm, displacement, geodata, hxl, internally displaced persons-idp, populated places-settlements
Organization: CCCM Cluster Somalia
Ethiopia Displacement - [IDPs] - Village Assessment Survey - Tigray - [IOM DTM]

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

Tags: affected population, displacement, hxl, internally displaced persons-idp, returnees
Organization: International Organization for Migration (IOM)
Argentina: subnational poverty

This table contains subnational multidimensional poverty data from the [data tables](https://ophi.org.uk/multidimensional-poverty-index/data-tables-do-files/) published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa [(2023)](https://ophi.org.uk/mpi-methodological-note-56/).

Tags: development, education, facilities-infrastructure, health, indicators, mortality, nutrition, poverty, water sanitation and hygiene-wash
Organization: Oxford Poverty & Human Development Initiative
Bolivia: subnational poverty trends

This table contains subnational multidimensional poverty trends data from the [data tables](https://ophi.org.uk/multidimensional-poverty-index/data-tables-do-files/) published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa [(2023)](https://ophi.org.uk/mpi-methodological-note-57/).

Tags: development, education, facilities-infrastructure, health, indicators, mortality, nutrition, poverty, water sanitation and hygiene-wash
Organization: Oxford Poverty & Human Development Initiative
Costa Rica: subnational poverty

This table contains subnational multidimensional poverty data from the [data tables](https://ophi.org.uk/multidimensional-poverty-index/data-tables-do-files/) published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa [(2023)](https://ophi.org.uk/mpi-methodological-note-56/).

Tags: development, education, facilities-infrastructure, health, indicators, mortality, nutrition, poverty, water sanitation and hygiene-wash
Organization: Oxford Poverty & Human Development Initiative
Belize: subnational poverty trends

This table contains subnational multidimensional poverty trends data from the [data tables](https://ophi.org.uk/multidimensional-poverty-index/data-tables-do-files/) published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa [(2023)](https://ophi.org.uk/mpi-methodological-note-57/).

Tags: development, education, facilities-infrastructure, health, indicators, mortality, nutrition, poverty, water sanitation and hygiene-wash
Organization: Oxford Poverty & Human Development Initiative
Democratic Republic of Congo : Epidemioliogical cases and deaths (Données épidémiologiques)

The file provides information on the cases, deaths, ... of the various pathologies on the extent of the national territory.
Le fichier renseigne sur les cas, décès, ... des différentes pathologies sur l'étendue du territoire national.

Tags: disease, epidemics-outbreaks
Organization: OCHA Democratic Republic of the Congo (DRC)
Guatemala: Humanitarian Needs Overview

This data has been produced by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) on behalf of the Humanitarian Country Team and partners. The data provides the Humanitarian Country Team’s shared understanding of the crisis, including the most pressing humanitarian need and the estimated number of people who need assistance. It represents a consolidated evidence base and helps inform joint strategic response planning.

Tags: humanitarian needs overview-hno, humanitarian response plan-hrp, people in need-pin
Organization: OCHA Latin America and the Caribbean (ROLAC)
Lao People's Democratic Republic: subnational poverty trends

This table contains subnational multidimensional poverty trends data from the [data tables](https://ophi.org.uk/multidimensional-poverty-index/data-tables-do-files/) published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa [(2023)](https://ophi.org.uk/mpi-methodological-note-57/).

Tags: development, education, facilities-infrastructure, health, indicators, mortality, nutrition, poverty, water sanitation and hygiene-wash
Organization: Oxford Poverty & Human Development Initiative
Lesotho: subnational poverty trends

This table contains subnational multidimensional poverty trends data from the [data tables](https://ophi.org.uk/multidimensional-poverty-index/data-tables-do-files/) published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa [(2023)](https://ophi.org.uk/mpi-methodological-note-57/).

Tags: development, education, facilities-infrastructure, health, indicators, mortality, nutrition, poverty, water sanitation and hygiene-wash
Organization: Oxford Poverty & Human Development Initiative
Tonga: subnational poverty

This table contains subnational multidimensional poverty data from the [data tables](https://ophi.org.uk/multidimensional-poverty-index/data-tables-do-files/) published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI methodology is detailed in Alkire, Kanagaratnam & Suppa [(2023)](https://ophi.org.uk/mpi-methodological-note-56/).

Tags: development, education, facilities-infrastructure, health, indicators, mortality, nutrition, poverty, water sanitation and hygiene-wash
Organization: Oxford Poverty & Human Development Initiative