United Nations Human Settlement Programmes, Global Urban Observatory - Demographic, Health, Education and Transport indicators
[1]
WFP - Food Prices
[1]
WFP - Integrated Context Analysis ICA
[1]
WFP - Landslide Risk
[1]
WFP - NDVI at Subnational Level
[1]
WFP - Rainfall Indicators at Subnational Level
[1]
WFP Advanced Disaster Analysis and Mapping - Cyclone Data
[1]
WFP Advanced Disaster Analysis and Mapping - Earthquake Data
[3]
WHO - WHO Health Indicators
[1]
Work of InterAction Members
[1]
World Bank - Agriculture and Rural Development
[1]
World Bank - Aid Effectiveness
[1]
World Bank - Climate Change
[1]
World Bank - Development
[2]
World Bank - Economic Social Environmental Health Education Development and Energy
[1]
World Bank - Economic and Social development
[6]
World Bank - Education
[1]
World Bank - Energy and Mining
[1]
World Bank - Environment
[1]
World Bank - Gender
[1]
World Bank - Health
[1]
World Bank - Infrastructure
[1]
World Bank - Poverty
[1]
World Bank - Social Protection and Labor
[1]
World Bank - Trade
[1]
World Pop - Population Counts
[1]
WorldPop - Age and sex structures
[1]
WorldPop - Births
[1]
WorldPop - Population Density
[1]
WorldPop - Pregnancies
[1]
LessMore
Locations:
Afghanistan
[22]
Albania
[10]
Algeria
[15]
American Samoa
[5]
Andorra
[3]
Angola
[15]
Anguilla
[3]
Antigua and Barbuda
[6]
Argentina
[15]
Armenia
[11]
Aruba
[7]
Australia
[9]
Austria
[9]
Azerbaijan
[11]
Bahamas
[6]
Bahrain
[7]
Bangladesh
[27]
Barbados
[7]
Belarus
[11]
Belgium
[9]
Belize
[8]
Benin
[15]
Bermuda
[4]
Bhutan
[11]
Bolivia (Plurinational State of)
[20]
Bonaire, Sint Eustatius and Saba
[1]
Bosnia and Herzegovina
[10]
Botswana
[10]
Brazil
[19]
British Indian Ocean Territory
[1]
British Virgin Islands
[3]
Brunei Darussalam
[6]
Bulgaria
[11]
Burkina Faso
[23]
Burundi
[23]
Cabo Verde
[8]
Cambodia
[15]
Cameroon
[25]
Canada
[10]
Cayman Islands
[6]
Central African Republic
[25]
Chad
[23]
Chile
[18]
China
[11]
China, Hong Kong Special Administrative Region
[8]
China, Macao Special Administrative Region
[5]
Colombia
[27]
Comoros
[9]
Congo
[16]
Cook Islands
[3]
Costa Rica
[17]
Croatia
[10]
Cuba
[5]
Curaçao
[4]
Cyprus
[6]
Czechia
[8]
Côte d'Ivoire
[16]
Democratic People's Republic of Korea
[9]
Democratic Republic of the Congo
[24]
Denmark
[8]
Djibouti
[15]
Dominica
[6]
Dominican Republic
[17]
Ecuador
[20]
Egypt
[16]
El Salvador
[15]
Equatorial Guinea
[11]
Eritrea
[10]
Estonia
[8]
Eswatini
[9]
Ethiopia
[26]
Falkland Islands (Malvinas)
[1]
Faroe Islands
[4]
Fiji
[9]
Finland
[9]
France
[11]
French Guiana
[5]
French Polynesia
[5]
Gabon
[13]
Gambia
[12]
Georgia
[10]
Germany
[10]
Ghana
[20]
Gibraltar
[3]
Greece
[10]
Greenland
[2]
Grenada
[5]
Guadeloupe
[6]
Guam
[6]
Guatemala
[17]
Guernsey
[2]
Guinea
[14]
Guinea-Bissau
[12]
Guyana
[10]
Haiti
[23]
Holy See
[1]
Honduras
[21]
Hungary
[8]
Iceland
[6]
India
[18]
Indonesia
[20]
Iran (Islamic Republic of)
[8]
Iraq
[23]
Ireland
[8]
Isle of Man
[4]
Israel
[8]
Italy
[11]
Jamaica
[11]
Japan
[12]
Jersey
[3]
Jordan
[19]
Kazakhstan
[11]
Kenya
[24]
Kiribati
[5]
Kosovo
[2]
Kuwait
[7]
Kyrgyzstan
[11]
Lao People's Democratic Republic
[15]
Latvia
[6]
Lebanon
[20]
Lesotho
[10]
Liberia
[15]
Libya
[19]
Liechtenstein
[3]
Lithuania
[8]
Luxembourg
[7]
Madagascar
[17]
Malawi
[18]
Malaysia
[16]
Maldives
[9]
Mali
[21]
Malta
[6]
Marshall Islands
[6]
Martinique
[6]
Mauritania
[14]
Mauritius
[8]
Mayotte
[3]
Mexico
[20]
Micronesia (Federated States of)
[5]
Monaco
[3]
Mongolia
[15]
Montenegro
[6]
Montserrat
[1]
Morocco
[10]
Mozambique
[22]
Myanmar
[23]
Namibia
[11]
Nauru
[5]
Nepal
[18]
Netherlands
[10]
New Caledonia
[5]
New Zealand
[9]
Nicaragua
[13]
Niger
[20]
Nigeria
[24]
Niue
[1]
North Macedonia
[11]
Northern Mariana Islands
[3]
Norway
[8]
Oman
[7]
Pakistan
[23]
Palau
[4]
Panama
[13]
Papua New Guinea
[12]
Paraguay
[17]
Peru
[20]
Philippines
[204]
Poland
[11]
Portugal
[10]
Puerto Rico
[4]
Qatar
[7]
Republic of Korea
[10]
Republic of Moldova
[9]
Romania
[13]
Russian Federation
[8]
Rwanda
[14]
Réunion
[4]
Saint Barthélemy
[1]
Saint Helena
[1]
Saint Kitts and Nevis
[3]
Saint Lucia
[8]
Saint Martin
[2]
Saint Vincent and the Grenadines
[7]
Samoa
[7]
San Marino
[3]
Sao Tome and Principe
[9]
Saudi Arabia
[10]
Senegal
[18]
Serbia
[11]
Seychelles
[6]
Sierra Leone
[13]
Singapore
[10]
Sint Maarten
[2]
Slovakia
[9]
Slovenia
[8]
Solomon Islands
[9]
Somalia
[17]
South Africa
[18]
South Sudan
[20]
Spain
[9]
Sri Lanka
[14]
State of Palestine
[16]
Sudan
[19]
Suriname
[9]
Sweden
[8]
Switzerland
[8]
Syrian Arab Republic
[16]
Taiwan (Province of China)
[9]
Tajikistan
[12]
Thailand
[19]
Timor-Leste
[8]
Togo
[14]
Tokelau
[1]
Tonga
[5]
Trinidad and Tobago
[10]
Tunisia
[15]
Turkmenistan
[5]
Turks and Caicos Islands
[4]
Tuvalu
[4]
Türkiye
[19]
Uganda
[20]
Ukraine
[19]
United Arab Emirates
[9]
United Kingdom
[9]
United Republic of Tanzania
[18]
United States
[12]
United States Minor Outlying Islands
[1]
United States Virgin Islands
[5]
Uruguay
[13]
Uzbekistan
[12]
Vanuatu
[7]
Venezuela (Bolivarian Republic of)
[14]
Viet Nam
[19]
Wallis and Futuna Islands
[2]
World
[4]
Yemen
[18]
Zambia
[20]
Zimbabwe
[18]
LessMore
Formats:
API
[1]
ARC/INFO Grid
[1]
CSV
[66]
EMF
[1]
Garmin IMG
[22]
GeoJSON
[14]
GeoTIFF
[8]
Geodatabase
[1]
Geopackage
[24]
Geoservice
[1]
Google Sheet
[1]
KML
[33]
KMZ
[2]
PDF
[9]
SHP
[46]
TSV
[2]
TXT
[1]
Web App
[4]
XLS
[1]
XLSX
[77]
zip
[2]
LessMore
Organisations:
Armed Conflict Location & Event Data Project (ACLED)
[1]
British Red Cross Maps Team
[2]
CLEAR Global (previously Translators without Borders)
[1]
Cirrolytix
[1]
Data for Good at Meta
[8]
Fields Data
[27]
Food and Agriculture Organization (FAO)
[2]
Global Healthsites Mapping Project
[1]
Global Shelter Cluster
[2]
Globhe Drones
[1]
HDX
[4]
Health Cluster
[1]
Humanitarian OpenStreetMap Team (HOT)
[33]
Insecurity Insight
[4]
InterAction
[1]
Internal Displacement Monitoring Centre (IDMC)
[2]
International Aid Transparency Initiative
[1]
International Federation of Red Cross and Red Crescent Societies (IFRC)
[2]
International Organization for Migration (IOM)
[1]
Johns Hopkins University Center for Systems Science and Engineering
[1]
Kontur
[2]
Netherlands Red Cross - 510
[6]
OCHA Field Information Services Section (FISS)
[1]
OCHA Financial Tracking System (FTS)
[1]
OCHA HQ
[3]
OCHA Philippines
[25]
OCHA Regional Office for Asia and the Pacific (ROAP)
[1]
OurAirports
[1]
Oxford Poverty & Human Development Initiative
[1]
Qatar Computing Research Institute
[1]
ReliefWeb
[1]
The DHS Program
[2]
Thinking Machines Data Science
[1]
UNDP Human Development Reports Office (HDRO)
[1]
UNESCO
[1]
UNFPA
[1]
UNFPA Philippines
[1]
UNHCR - The UN Refugee Agency
[5]
UNICEF Data and Analytics (HQ)
[1]
United Nations Development Coordination Office
[1]
United Nations Human Settlement Programmes, Data and Analytics Section
[1]
WFP - World Food Programme
[14]
WFP Advanced Disaster Analysis & Mapping
[4]
World Bank Group
[24]
World Health Organization
[3]
WorldPop
[5]
LessMore
Tags:
administrative boundaries-divisions
[2]
affected area
[1]
affected population
[7]
agriculture-livestock
[4]
aid effectiveness
[2]
aid worker security
[3]
aid workers
[1]
asylum seekers
[1]
aviation
[5]
baseline population
[12]
births
[1]
cash voucher assistance-cva
[2]
casualties
[2]
census
[8]
children
[3]
climate hazards
[1]
climate-weather
[5]
complex emergency-conflict-security
[1]
conflict-violence
[7]
covid-19
[16]
cyclones-hurricanes-typhoons
[17]
damage assessment
[5]
demographics
[12]
development
[9]
disability
[2]
disease
[8]
displacement
[4]
earthquake-tsunami
[7]
economics
[16]
education
[16]
education facilities-schools
[7]
elderly
[2]
employment
[3]
energy
[2]
environment
[6]
epidemics-outbreaks
[4]
facilities-infrastructure
[26]
fatalities
[3]
flooding-storm surge
[1]
food security
[5]
funding
[5]
gazetteer
[2]
gender
[5]
gender-based violence-gbv
[1]
geodata
[58]
hazards and risk
[2]
health
[27]
health facilities
[7]
humanitarian access
[3]
humanitarian needs overview-hno
[1]
humanitarian response plan-hrp
[2]
hxl
[88]
hydrology
[6]
indicators
[36]
internally displaced persons-idp
[6]
languages
[1]
literacy
[2]
livelihoods
[3]
logistics
[5]
malaria
[1]
malnutrition
[1]
markets
[2]
maternity
[2]
mental health
[2]
migration
[1]
mortality
[2]
natural disasters
[3]
needs assessment
[4]
non-food items-nfi
[1]
nutrition
[5]
openstreetmap
[1]
operational capacity
[3]
operational partners
[27]
operational presence
[31]
peacekeeping
[1]
people in need-pin
[2]
points of interest-poi
[3]
populated places-settlements
[5]
population
[5]
ports
[3]
poverty
[6]
protection
[2]
railways
[3]
refugees
[1]
rivers
[4]
roads
[3]
services
[2]
severe acute malnutrition-sam
[1]
severity
[2]
sex and age disaggregated data-sadd
[1]
shelter
[4]
social media data
[2]
socioeconomics
[7]
stateless persons
[1]
survey
[3]
sustainable development
[1]
sustainable development goals-sdg
[2]
topography
[1]
trade
[3]
transportation
[13]
vaccination-immunization
[3]
water sanitation and hygiene-wash
[6]
who is doing what and where-3w-4w-5w
[32]
women
[2]
youth
[1]
LessMore
Licenses:
Creative Commons Attribution International
[103]
Creative Commons Attribution Share-Alike
[10]
Creative Commons Attribution for Intergovernmental Organisations
[24]
ODbL
[1]
Open Data Commons Attribution License (ODC-BY)
[1]
Open Database License (ODC-ODbL)
[36]
Other
[22]
Public Domain / No Restrictions
[6]
UN-Habitat’s urban datasets are made available under the Public Domain Dedication and License v1.0 whose full text can be found at: http://www.opendatacommons.org/licenses/pddl/1.0/
[1]
Philippines administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata.
Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population
This dataset contains agency- and open source events published in the Attacks on Health Care News Brief and included in the Safeguarding Health in Conflict Coalition (SHCC) annual reporting on violence against or obstruction of health care. This page is managed by SHCC member Insecurity Insight.
Please get in touch if you are interested in curated datasets: info@insecurityinsight.org
2020 Census Total Population by Barangay (admin4) with new 10-digit pcode with Maguindanao del Sur and Norte; Missing barangays in R12 that moved to BARMM
More than 200 million businesses use Facebook globally. The goal of Meta’s quarterly Small Business Surveys is to learn about the unique perspectives, challenges and opportunities of small and medium-sized businesses (SMBs).
The Future of Business (FoB) Survey is conducted biannually in partnership with the World Bank and the Organisation for Economic Cooperation and Development (OECD) across nearly 100 countries. The target population consists of SMEs that have an active Facebook Business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. Meta also conducts the Global State of Small Business (GSoSB) Survey bi-annually in partnership with various academic partners across approximately 30 countries. Similarly to the FoB Survey, the target population is active Facebook Page Administrators, but also includes the general population of Facebook users.
Survey questions for all surveys cover a range of topics depending on the survey wave such as business characteristics, challenges, financials and strategy in addition to custom modules related to regulation, gender inequity, access to finance, digital technologies, reduction in revenues, business closures, international trade, inflation, reduction of employees and challenges/needs of the business.
Aggregated country level data for each survey wave is available to the public on HDX and controlled access microdata is available to Data for Good at Meta partners. Please visit https://dataforgood.facebook.com/dfg/tools/future-of-business-survey to apply for access to microdata or contact dataforgood@fb.com for any questions.
The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources. The data is provided for 93 low and middle-income countries at 2.4km resolution. Please cite / attribute any use of this dataset using the following:
Microestimates of wealth for all low- and middle-income countries
Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock
Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119
More details are available here: https://dataforgood.fb.com/tools/relative-wealth-index/
Research publication for the Relative Wealth Index is available here: https://www.pnas.org/content/119/3/e2113658119
Press coverage of the release of the Relative Wealth Index here: https://www.fastcompany.com/90625436/these-new-poverty-maps-could-reshape-how-we-deliver-humanitarian-aid
An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
Education indicators for Philippines.
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: SDG 4 Global and Thematic (made 2022 September), Other Policy Relevant Indicators (made 2022 September), Demographic and Socio-economic (made 2022 September)
The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in the Philippines: (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).
This dataset contains Who, What, and Where(3W) data for the Aklan Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Cavite Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Capiz Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Camarines Sur Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Biliran Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Bohol Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Antique Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Cebu Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Cotabato Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Dinagat Islands Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Eastern Samar Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Guimaras Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Iloilo Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Leyte Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.
This dataset contains Who, What, and Where(3W) data for the Maguindanao Province in the Philippines. The operational presence of the various organisations (who) by sector (what), and location (where) at the province level.