Updated
October 28, 2020
| Dataset date: Sep 21, 2020
This dataset updates: Every year
This data contains aggregated weighted statistics at the regional level by gender for the Survey on Gender Equality At Home fielded in July 2020. Facebookโs Survey on Gender Equality at Home generates a global snapshot of women and menโs access to resources, their time spent on unpaid care work, and their attitudes about equality. If you're interested in becoming a Survey on Gender Equality research partner, please email gendersurvey@fb.com.
Updated
October 28, 2020
| Dataset date: Mar 1, 2020-Aug 31, 2020
This dataset updates: Every day
These data sets are intended to inform researchers and public health experts about how populations are responding to physical distancing measures. In particular, there are two metrics, Change in Movement and Stay Put, that provide a slightly different perspective on movement trends. Change in Movement looks at how much people are moving around and compares it with a baseline period that predates most social distancing measures, while Stay Put looks at the fraction of the population that appear to stay within a small area during an entire day.
Full details, including the privacy protections in this data, are available here: https://research.fb.com/blog/2020/06/protecting-privacy-in-facebook-mobility-data-during-the-covid-19-response/
Updated
October 28, 2020
| Dataset date: Jan 1, 2019-Dec 31, 2020
This dataset updates: Every week
The ACLED project codes reported information on the type, agents, exact location, date, and other characteristics of political violence events, demonstrations and select politically relevant non-violent events. ACLED focuses on tracking a range of violent and non-violent actions by political agents, including governments, rebels, militias, communal groups, political parties, external actors, rioters, protesters and civilians. Data contain specific information on the date, location, group names, interaction type, event type, reported fatalities and contextual notes.
Updated
October 13, 2020
| Dataset date: Oct 13, 2020
This dataset updates: Every day
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, is encoded as utf-8 and the second row of the CSV contains HXL tags.
Updated
September 7, 2020
| Dataset date: Jan 1, 1970-Dec 31, 2019
This dataset updates: Every three months
Education indicators for Martinique.
Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: Students and Teachers (made 2020 February), SDG 4 Global and Thematic (made 2020 February), Demographic and Socio-economic (made 2020 February)
Updated
August 27, 2020
| Dataset date: Jan 1, 2018-Dec 31, 2019
This dataset updates: Every year
Data collated by UNHCR, containing information about forcibly displaced populations and stateless persons, spanning across almost 70 years of statistical activities. The data includes the countries / territories of asylum and origin. Specific resources are available for end-year population totals, demographics, asylum applications, decisions, and solutions availed by refugees and IDPs (resettlement, naturalisation or returns).
Updated
Live
| Dataset date: Jan 1, 2019-Jan 1, 2020
This dataset updates: Live
Live list of active aid activities for Martinique shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org
Updated
Live
| Dataset date: Jan 22, 2020-Oct 28, 2020
This dataset updates: Live
Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources including the World Health Organization (WHO), DXY.cn, BNO News, National Health Commission of the Peopleโs Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH), and others. JHU CCSE maintains the data on the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository on Github.
Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths.
On 23/03/2020, a new data structure was released. The current resources for the latest time series data are:
time_series_covid19_confirmed_global.csv
time_series_covid19_deaths_global.csv
time_series_covid19_recovered_global.csv
---DEPRECATION WARNING---
The resources below ceased being updated on 22/03/2020 and were removed on 26/03/2020:
time_series_19-covid-Confirmed.csv
time_series_19-covid-Deaths.csv
time_series_19-covid-Recovered.csv
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay')
Features may have these attributes:
tunnel
blockage
source
waterway
depth
name
water
natural
width
layer
covered
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL
Features may have these attributes:
beds
addr:street
source
amenity
tourism
rooms
shop
name
addr:full
addr:housenumber
addr:city
opening_hours
man_made
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
building IS NOT NULL
Features may have these attributes:
addr:street
building:levels
building:materials
source
name
addr:full
addr:housenumber
office
building
addr:city
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
highway IS NOT NULL
Features may have these attributes:
surface
oneway
bridge
source
smoothness
name
highway
lanes
width
layer
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity IN ('kindergarten','school','college','university') OR building IN ('kindergarten','school','college','university')
Features may have these attributes:
source
amenity
name
capacity:persons
addr:full
building
operator:type
addr:city
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
June 29, 2020
| Dataset date: Jan 1, 2000-Dec 31, 2020
This dataset updates: Every year
Age and sex 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 Tatem et al, and a description of the modelling methods used found in Tatem et al and Pezzulo et al. The 'Global per country 2000-2020' 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.
Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing methods and time periods are still available for download here: Individual countries and Whole continent.
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). https://dx.doi.org/10.5258/SOTON/WP00646
Updated
June 29, 2020
| Dataset date: Jan 1, 2017-Dec 31, 2017
This dataset updates: Every year
The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al..
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2017. Martinique 1km pregnancies. Version 2.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00502
Updated
June 29, 2020
| Dataset date: Jan 1, 2017-Dec 31, 2017
This dataset updates: Every year
The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al..
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2017. Martinique 1km births. Version 2.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00394
Updated
June 29, 2020
| Dataset date: Jan 1, 2000-Dec 31, 2020
This dataset updates: Every year
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data and methods can be found in Tatem et al, a description of the modelling methods used found in Stevens et al, and access to modelling code here.
Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively).
Individual countries 2000-2020: Consistent 100m resolution population count datasets created using "top-down" methods for all countries of the World for each year 2000-2020.
Individual countries 2000-2020 UN adjusted: Adjusted to match official United Nations population estimates (UN 2019).
Global mosaics 2000-2020: Mosaiced 1km resolution versions of the "Individual countries 2000-2020" datasets.
Bespoke methods for individual countries (WOPR): Bespoke 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country.
Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent
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). https://dx.doi.org/10.5258/SOTON/WP00645
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
aeroway IS NOT NULL OR building = 'aerodrome' OR emergency:helipad IS NOT NULL OR emergency = 'landing_site'
Features may have these attributes:
source
emergency
aeroway
name
capacity:persons
addr:full
building
operator:type
addr:city
emergency:helipad
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
healthcare IS NOT NULL OR amenity IN ('doctors','dentist','clinic','hospital','pharmacy')
Features may have these attributes:
operator:type
source
amenity
name
capacity:persons
addr:full
building
healthcare
addr:city
healthcare:speciality
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
railway IN ('rail','subway','station')
Features may have these attributes:
source
railway
name
addr:full
operator:type
addr:city
layer
ele
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity = 'ferry_terminal' OR building = 'ferry_terminal' OR port IS NOT NULL
Features may have these attributes:
port
source
amenity
name
addr:full
building
operator:type
addr:city
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
amenity IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office')
Features may have these attributes:
network
source
operator
amenity
name
addr:full
addr:city
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
OpenStreetMap exports for use in GIS applications.
This theme includes all OpenStreetMap features in this area matching:
place IN ('isolated_dwelling','town','village','hamlet','city')
Features may have these attributes:
source
is_in
population
place
name
This dataset is one of many OpenStreetMap exports on
HDX.
See the Humanitarian OpenStreetMap Team website for more
information.
Updated
May 30, 2020
| Dataset date: Jan 1, 2011-Dec 31, 2019
This dataset updates: Every year
Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.
"People Displaced" refers to the number of people living in displacement as of the end of each year.
"New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.
Contains data from IDMC's Global Internal Displacement Database.
