AndreaBozzo/ceres-open-data-index huggingface dataset:
SALW Guide

With its **SALW guide**, BICC provides a non-specialist, user-friendly and multi-language platform to inform about different categories and types of small arms and light weapons, their whereabouts in the world, and where possible, by whom they are held. It is designed to build knowledge on how to recognize different types, makes and models of commonly used SALW; to collect data on the global and country-specific spread of these SALW; and to describe some of their visual and technical specifications. The guide is not an exhaustive list of all SALW that are used around the world.

Global SALW control relies on, among other things, data and knowledge of the weapons themselves. Our aim is that the Guide will be used to support national reporting duties on SALW holdings; facilitate and ameliorate the collection of data on SALW; and increase general knowledge of global distribution of SALW. Thus, the guide addresses researchers, journalists, photographers as well as civil servants, officials and policymakers dealing with the aforementioned challenges of SALW control.

The underlying database of the SALW guide can be queried by either a geographical or weapon specific search term. In total, the guide contains visual images, markings and descriptions on 131 types of small arms or light weapons worldwide. The main source of the guide, the Small Arms and Light Weapons Guide (2016) by the German Bundeswehr Verification Center (BWVc), has been validated by various institutions and databases. [See project website for more information ](https://salw-guide.bicc.de)


Tags: conflict-violence
Organization: Bonn International Centre for Conflict Studies (BICC)
Yemen: Hard-to-Reach Districts | 29 April 2019

Please see [the method summary](https://data.humdata.org/dataset/fb7a8285-912b-4fb5-a6cf-c5ed6b0ae2c2/resource/d5a56a55-d9df-475a-b79c-fed433da8bbd/download/yemen_hard-to_reach_framework_4_june_2019.pdf "Yemen Hard-to-reach framework")

Tags: humanitarian access, hxl
Organization: OCHA Yemen
Fiji - Population Data

These are selected indicators from the 2007 Fijian Census. Some of the data is projected to 2015. These indicators were selected to identify potentially vulnerable households.

Original dataset and more information can be found in the [Fiji Bureau of Statistics](http://fiji.popgis.spc.int/) website: http://fiji.popgis.spc.int/

Tags: disability, population, shelter, water sanitation and hygiene-wash
Organization: OCHA Office of the Pacific Islands
Democratic Republic of the Congo: Operational plan  in North Kivu-South Kivu and Ituri provinces

Data compiled by the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) to identify and assess the most critical humanitarian needs and estimate the number of people who need assistance in North Kivu, South Kivu and Ituri provinces.

Tags: education, health, humanitarian response plan-hrp, hxl, people in need-pin, protection
Organization: OCHA Democratic Republic of the Congo (DRC)
Somalia: Internally Displaced Persons (IDPs)

Data collated by UNHCR - Protection and Return Monitoring Network (PRMN), contains internally displaced persons. The data includes regions (departure and arrival), districts (departure and arrival), reasons of displacements and the IDPs from January 2016 - October 2022.

Tags: baseline population, displacement, internally displaced persons-idp, refugees
Organization: UNHCR - The UN Refugee Agency
Burkina Faso: Roads

This dataset contains roads data from OpenStreetMap for which attributes and classifications have been enhanced using maps from the government.
The new classifications added based on the government maps are using the attribute igb_class:

-  Igb_class = 2: for Major roads
-  Igb_class = 1 or 3 : for Minor roads


Tags: geodata, roads
Organization: OCHA Burkina Faso
Dominica - Requirements and Funding Data

FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's [Financial Tracking Service](https://fts.unocha.org/), is encoded as utf-8 and the second row of the CSV contains [HXL](http://hxlstandard.org) tags.

Tags: covid-19, funding, hxl
Organization: OCHA Financial Tracking System (FTS)
Philippines: Pantawid Indigenous People (IP) Data

The data covers all registered Pantawid IP beneficiaries regardless of their program status. The Modified Conditional Cash Transfer Program (MCCT) is a sub-component of Pantawid Pamilyang Pilipino Program which is uses modified approach in implementing the CCT program for poor families including homeless, Indigenous People and Families in Need of Special Protection (FNSP). 

Tags: cash voucher assistance-cva, demographics
Organization: OCHA Philippines
CAR Displacement Data - Bangui Floods Oct19 - Site Assessment [IOM DTM]

Following the rains that hit certain areas of the country as early as 21 October, flooding cases involving the displacement of populations are mentioned in some localities of the country. IOM through its Displacement Tracking Matrix (DTM) conducted rapid assessments in the districts of Bangui 2nd, Bangui 6th, Bangui 7th, and Bombo.

Tags: displacement, hxl, internally displaced persons-idp
Organization: International Organization for Migration (IOM)
Evaluación de necesidades de agua, saneamiento e higiene en el marco del flujo mixto de frontera, para el fortalecimiento de las mesas WASH en los departamentos de Arauca, Norte de Santander, La Guajira y Nariño.

Caracterización que realizó iMMAP y UNICEF entre Marzo y Mayo del 2019 en los departamentos de Arauca, La Guajira, Norte de Santander y Nariño. Se comparte un subgrupo de la muestra del estudio completo (incluye información de Asentamientos, Albergues y Refugios), que comprende información primaria recolectada por IMMAP. 

Tags: affected area, affected population, demographics, facilities-infrastructure, migration, refugees
Organization: iMMAP Inc.
Cobertura del servicio de alcantarillado, servicio de basuras y acueducto en Colombia

Base que contiene información acerca del Porcentaje de cobertura del servicio de alcantarillado,  Porcentaje de cobertura del servicio de basuras, y Porcentaje de cobertura del servicio de acueducto en 2018 por departamentos en Colombia,. Datos obtenidos de la Encuesta Nacional de Calidad de Vida DANE(2018). 

Tags: facilities-infrastructure, hxl, services, water sanitation and hygiene-wash
Organization: iMMAP Inc.
Yemen - Nutrition SMART Survey

This dataset contains a summary of the Standardized Monitoring and Assessment of Relief and Transitions (SMART) nutrition surveys carried out in Yemen in 2019. A collection of the SMART survey reports is available [here](https://www.humanitarianresponse.info/en/operations/yemen/document/smart-surveys-reports-2019).

Tags: global acute malnutrition-gam, malnutrition, nutrition, severe acute malnutrition-sam
Organization: OCHA Yemen
Indicadores y variables del Sector Salud

Base que contiene datos por departamento y municipio de variables e indicadores como, número de atención en abortos, partos y nacimientos. Causas externas de mortalidad, que incluye homicidios, suicidios y accidentes. Número de atenciones por planificación familiar y personas con VIH/SIDA; y costo de atención de partos. Todos los datos son de población tanto colombiana como de venezolanos residentes en Colombia. 

Tags: health, migration
Organization: iMMAP Inc.
Afghanistan - Who does What Where (July to September 2019)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://www.humanitarianresponse.info/en/operations/afghanistan/3w). 

Tags: hxl, operational presence, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
Isle of Man: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Isle of Man: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, health, women, youth
Organization: AI for Good at Meta
Slovenia: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Slovenia: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Andorra: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Andorra: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Afghanistan - Who does What Where (April to June 2019)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://www.humanitarianresponse.info/en/operations/afghanistan/3w). 

Tags: hxl, operational capacity, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
IOM Bangladesh Needs And Population Monitoring (NPM)  Round 15 Site Assessment Female Key Informant

Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings. 

This dataset presents the result of the NPM Round 15 Site Assessment exercise, which collected information from  female key informant form 1956 locations related to the Rohingya refugee population distribution and multisectoral needs during the months of 1st May – 24th June.

NPM [Site Assessment Round 15 Dataset](https://data.humdata.org/dataset/iom-bangladesh-needs-and-population-monitoring-npm-round-15-site-assessment#)

Rohingya refugee population distribution by para in Teknaf upazila. Please [click here.](https://data.humdata.org/dataset/iom-bangladesh-needs-and-population-monitoring-npm-teknaf-para-mapping)



Tags: camp coordination and camp management-cccm, displacement, refugee crisis, refugees
Organization: International Organization for Migration (IOM)
IOM Bangladesh - Needs and Population Monitoring (NPM) Round 15 Site Assessment

Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.

This dataset presents the result of the NPM Round 15 Site Assessment exercise, which collected information related to the Rohingya refugee population distribution and multisectoral needs during the months of 1st May – 24th June.

Rohingya refugee population distribution by para in Teknaf upazila. Please [click here](https://data.humdata.org/dataset/iom-bangladesh-needs-and-population-monitoring-npm-teknaf-para-mapping)


Tags: camp coordination and camp management-cccm, displacement, needs assessment, refugee crisis, refugees
Organization: International Organization for Migration (IOM)
UNFPA State of World Population 2019

Global population data, including fertility rate, gender parity in school enrolment, information on sexual and reproductive health, and much more. Together, these data shine a light on the health and rights of people around the world, especially women and young people. The numbers here come from UNFPA and fellow UN agencies, and are updated annually.

Full report and dashboard available here: https://www.unfpa.org/swop-2019

Tags: baseline population, gender, health
Organization: HDX
UNHCR Global Trends: Forced Displacement in 2018 Data

This dataset contains 29 data tables on global trends in forced displacement in 2018. The data provide trends, national and sometimes sub-national levels and demographic composition on refugees, asylum-seekers, internally displaced persons (IDPs), returnees (refugees and IDPs), stateless persons, and other persons of concern to UNHCR.

Tags: asylum seekers, displacement, internally displaced persons-idp, population, refugees, returnees, stateless persons
Organization: UNHCR - The UN Refugee Agency
Wallis and Futuna Islands: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Wallis and Futuna Islands: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
North East Nigeria Nutrition Sector Partner Capacity Mapping as of June 2019

The zipped dataset contains a CSV file detailing capacity mapping in the Nutrition Sector in all three crisis-affected states of Borno, Adamawa and Yobe in north east Nigeria. The dataset constitutes a comprehensive mapping of organizations responding on nutrition interventions, implementation capacity, staff in need of nutrition-related training, staff with the capacity to facilitate a training and overall supply (of nutrition commodities to treat SAM, nutrition commodities to treat and prevent MAM, micronutrient supplements, routine medication, infant and young child feeding supplies, as well as assessment items).

Tags: nutrition, operational capacity
Organization: iMMAP Inc.
North East Nigeria Global Acute Malnutrition Prevalence, July 2018

The zipped CSV files details Global Acute Malnutrition (GAM) prevalence data resulting from Round V of the Nutrition and Food Security SMART survey conducted at the Local Government (LGA) Level in all three crisis-affected states of north east Nigeria, July 2018. Also featured is data on Moderate Acute Malnutrition (MAM), Severe Acute Malnutrition (SAM), and MAM prevalence among beneficiaries 15-49 years, including the respective severity ranking. 

Tags: global acute malnutrition-gam, malnutrition, nutrition, severe acute malnutrition-sam
Organization: iMMAP Inc.
North East Nigeria Gender-based Response Progress Monitoring by Indicator, Jan-May 2019

The zipped dataset contains a CSV file that provides a progress monitoring update of the Gender-Based Violence Sub-sector by indicator, during the period January to May 2019. The dataset presents progress monitoring on key indicators, including beneficiaries reached through provision of multi-sectorial specialized GBV response services; number of functional GBV referral pathways in place that includes multi-sectoral services for GBV survivors; number of persons benefitting from training/capacity building initiatives to improve quality of service provision; number of persons involved in and accessing information about availability of support services, referrals and reporting; number of persons reached through sensitization and capacity building on GBV principles and prevention; number of persons benefiting from empowerment, skills building and linkages to protective livelihood programs; number of beneficiaries accessing services through women and girls, youth friendly spaces (WGYFS) within the communities; number of persons benefitting from socio-economic assistance for Women and adolescent Girls (formerly) associated with armed groups (WAFAAG) and/or returning from captivity; and number of persons benefiting from capacity building on GBV integration including referral mechanisms and code of conduct.

Tags: gender-based violence-gbv
Organization: iMMAP Inc.
Solomon Islands: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Solomon Islands : (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Samoa: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Samoa: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Northern Mariana Islands: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Northern Mariana Islands: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Naura: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Nauru: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
North East Nigeria – Borno, Yobe and Adamawa States School List as of June 2019

The zipped CSV contains a dataset featuring a comprehensive list of schools at the Local Government Area (LGA) and Ward level in all three crisis-affected states of north east Nigeria. The list provides details of the school name, school type (Regular, Islamiyya, Nomadic, Special Needs, Vocational Training Center, etc.), level (Pre-Primary, Primary, Junior Secondary, Secondary, Science and Vocational, etc.), and school operational status (open or closed).

Tags: education, education facilities-schools
Organization: iMMAP Inc.
Kiribati: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Kiribati: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Afghanistan - Who does What Where (January to March 2019)

The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed [here](https://www.humanitarianresponse.info/en/operations/afghanistan/3w). 

Tags: hxl, operational capacity, who is doing what and where-3w-4w-5w
Organization: OCHA Afghanistan
Afghanistan - Casualties

Total number of civilian casualties documented in each of Afghanistan’s 34 provinces, the top three causes
of civilian casualties in each province, and the percentage increase or decrease compared to 2017. For more, refer to the [report](https://www.af.one.un.org/wp-content/uploads/2019/02/afghanistan_protection_of_civilians_annual_report_2018_final_24_feb_2019_v3.pdf) from [UNAMA](https://unama.unmissions.org/)

Tags: casualties, fatalities, hxl
Organization: OCHA Afghanistan
North East Nigeria Health Sector Progress Monitoring with Age-Sex Data Disaggregation, Jan-May 2019

The zipped dataset contains a CSV file detailing the number of beneficiaries reached with life-saving health services support up to the Local Government Area (LGA) and Ward level by month. The data is age and sex disaggregated, covering the three crisis-affected states of Borno, Adamawa and Yobe in north east Nigeria.

Tags: health
Organization: iMMAP Inc.
North East Nigeria Health Sector Partner Operational Presence as of May 2019

The zipped dataset contains a CSV file detailing the operational presence of the Health Sector partners at the Local Government Area (LGA) level. This mapping covers the three crisis-affected states of Borno, Adamawa and Yobe in north east Nigeria.

Tags: health, operational capacity, who is doing what and where-3w-4w-5w
Organization: iMMAP Inc.
French Polynesia: High Resolution Population Density Maps + Demographic Estimates

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in French Polynesia: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Tags: children, elderly, geodata, health, women, youth
Organization: AI for Good at Meta
Psycho-social Support Reach, Borno and Yobe States, North East Nigeria, Quarter 1, 2019

The zipped geometrical dataset contains a shapefile on the reach of psycho-social support services to children in Borno and Yobe States, in the first quarter of 2019. The provision of psycho-social support to children is part of the overall Child Protection in Emergencies support services in response to the humanitarian crisis in north east Nigeria.

Tags: geodata, health, protection
Organization: iMMAP Inc.
Mine Risk Education Reach, Borno State, North East Nigeria, Quarter 1, 2019

The zipped geometrical dataset contains a shapefile on the reach of mine risk education services to children in Borno State, in the first quarter of 2019. The provision of Mine Risk Education is part of the overall Child Protection in Emergencies support in response to the humanitarian crisis in north east Nigeria.

Tags: education, geodata, protection
Organization: iMMAP Inc.
Social-Economic Reintegration Reach, Borno and Adamawa States, North East Nigeria, Quarter 1, 2019

The zipped geometrical dataset contains a shapefile on the reach of social-economic assistance to children and adolescents who have suffered from grave child rights violations, including former children associated with armed groups (CAAG) in Borno and Adamawa States. The provision of socio-economic reintegration support to children and adolescents is one of the indicators upon which the Child Protection in Emergencies Working Group is directing its humanitarian response efforts in response to the crisis north east Nigeria.

Tags: children, protection, youth
Organization: iMMAP Inc.