Singapore - Humanitarian Data Exchange

Singapore - Aid Effectiveness

60+ Downloads

Updated January 4, 2021 | Dataset date: January 01, 1960-December 31, 2020

This dataset updates: Every month

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. Aid effectiveness is the impact that aid has in reducing poverty and inequality, increasing growth, building capacity, and accelerating achievement of the Millennium Development Goals set by the international community. Indicators here cover aid received as well as progress in reducing poverty and improving education, health, and other measures of human welfare.

CSV

Singapore - Agriculture and Rural Development

World Bank Group

80+ Downloads

Updated January 4, 2021 | Dataset date: January 01, 1960-December 31, 2020

This dataset updates: Every month

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX. For the 70 percent of the world's poor who live in rural areas, agriculture is the main source of income and employment. But depletion and degradation of land and water pose serious challenges to producing enough food and other agricultural products to sustain livelihoods here and meet the needs of urban populations. Data presented here include measures of agricultural inputs, outputs, and productivity compiled by the UN's Food and Agriculture Organization.

CSV

Singapore - Requirements and Funding Data

OCHA FTS

1800+ Downloads

Updated December 31, 2020 | Dataset date: December 31, 2020-December 31, 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.

CSV

Topline Indicators

World Bank Group

4000+ Downloads

Updated December 27, 2020 | Dataset date: January 01, 2011-December 31, 2019

This dataset updates: Every month

Data used to update country toplines in HDX. Contains data from World Bank's data portal.

CSV

Current IATI aid activities in Singapore

International Aid Transparency Initiative

Updated Live | Dataset date: January 01, 2019-January 01, 2020

This dataset updates: Live

Live list of active aid activities for Singapore 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

CSV

Preventive Health Survey

Facebook

100+ Downloads

Updated December 26, 2020 | Dataset date: August 01, 2020-August 01, 2020

This dataset updates: As needed

The COVID-19 preventative health survey is designed to help policymakers and health researchers better monitor and understand people’s knowledge, attitudes and practices about COVID-19 to improve communications and their response to the pandemic.

API

Singapore - Education Indicators

UNESCO

1100+ Downloads

Updated December 16, 2020 | Dataset date: January 01, 1970-December 31, 2019

This dataset updates: Every three months

Education indicators for Singapore. Contains data from the UNESCO Institute for Statistics bulk data service covering the following categories: National Monitoring (made 2020 September), SDG 4 Global and Thematic (made 2020 September), Demographic and Socio-economic (made 2020 September)

CSV

Future Of Business Survey - Aggregated Data

Facebook

4700+ Downloads

Updated December 10, 2020 | Dataset date: September 01, 2016-April 01, 2018

This dataset updates: As needed

The Future of Business survey is a collaboration between Facebook, the OECD and the World Bank to provide timely insights on the perceptions, challenges, and outlook of online Small and Medium Enterprises (SMEs). The Future of Business survey was first launched as a monthly survey in 17 countries in February 2016 and expanded to 42 countries in 2018. In 2019, the Future of Business survey increased coverage to 97 countries and moved to a bi-annual cadence. 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. To date, more than 90 million SMEs have created a Facebook Page, and more than 700,000 of these Facebook Page owners have taken the survey. With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest. The survey includes questions about perceptions of current and future economic activity, challenges, business characteristics and strategy. Custom modules include questions related to regulation, access to finance, digital payments, and digital skills. The full questionnaire is available for download. This dataset contains survey response data aggregated by country and wave. Future of Business Survey website: futureofbusinesssurvey.org

Singapore - Population Density

WorldPop

Updated November 24, 2020 | Dataset date: January 01, 2000-December 31, 2020

This dataset updates: Every year

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. 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/WP00674

GeoTIFF

Singapore - Population Counts

WorldPop

20+ Downloads

Updated November 24, 2020 | Dataset date: January 01, 2000-December 31, 2020

This dataset updates: Every year

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. 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): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). 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

GeoTIFF

Government Actions on COVID-19 in Developing Countries

Dalberg

1500+ Downloads

Updated October 21, 2020 | Dataset date: December 31, 2019-September 23, 2020

This dataset updates: Every two weeks

The Database of Government Actions on COVID-19 in Developing Countries collates and tracks national policies and actions in response to the pandemic, with a focus on developing countries. The database provides information for 20 Global South countries – plus 6 Global North countries for reference – that Dalberg staff are either based in or know well. The database content is drawn from publicly available information combined, crucially, with on-the-ground knowledge of Dalberg staff. The database contains a comprehensive set of 100 non-pharmaceutical interventions – organized in a framework intended to make it easy to observe common variations between countries in the scope and extent of major interventions. Interventions we are tracking include: • Health-related: strengthening of healthcare systems, detection and isolation of actual / possible cases, quarantines • Policy-related: government coordination and legal authorization, public communications and education, movement restrictions • Distancing and hygiene: social distancing measures, movement restrictions, decontamination of physical spaces • Economic measures: economic and social measures, logistics / supply chains and security. We hope the database will be a useful resource for several groups of users: (i) governments and policymakers looking for a quick guide to actions taken by different countries—including a range of low- and middle-income countries, (ii) policy analysts and researchers studying the data to identify patterns of actions taken and compare the effectiveness of different interventions in curbing the pandemic, and (iii) media and others seeking to quickly access facts about the actions taken by governments in the countries covered in the database. Comments on the data can be submitted to covid.database.comments@dalberg.com Questions can be submitted to covid.database.questions@dalberg.com www.dalberg.com

XLSX
PDF

Novel Coronavirus (COVID-19) Cases Data

Johns Hopkins University Center for Systems Science and Engineering

327000+ Downloads

Updated Live | Dataset date: January 22, 2020-January 14, 2021

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 People’s 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

CSV

HOTOSM Singaore Sea Ports (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: amenity building name port operator:type source addr:full addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Populated Places (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: population name source is_in place This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Waterways (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: water name waterway covered source blockage depth layer tunnel natural width This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Airports (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: emergency:helipad building name capacity:persons operator:type source addr:full emergency aeroway addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Points of Interest (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: shop amenity rooms name addr:housenumber source addr:full man_made beds addr:street addr:city opening_hours tourism This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Railways (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: railway IN ('rail','station') Features may have these attributes: name ele operator:type source addr:full layer railway addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Roads (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: lanes name bridge source oneway surface smoothness layer highway width This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Education Facilities (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: amenity capacity:persons building name operator:type source addr:full addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Buildings (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: building:materials building name addr:housenumber office source addr:full building:levels addr:street addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Financial Services (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: amenity name source addr:full network operator addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

HOTOSM Singaore Health Facilities (OpenStreetMap Export)

Humanitarian OpenStreetMap Team (HOT)

Updated July 3, 2020 | Dataset date: January 07, 2021-January 07, 2021

This dataset updates: Every month

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: amenity building healthcare:speciality name operator:type capacity:persons source addr:full healthcare addr:city This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Singapore - Age and sex structures

WorldPop

Updated June 29, 2020 | Dataset date: January 01, 2000-December 31, 2020

This dataset updates: Every year

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. The 'Unconstrained 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. These are produced using the unconstrained top-down modelling method. 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

GeoTIFF

Singapore - Pregnancies

WorldPop

Updated June 29, 2020 | Dataset date: January 01, 2018-December 31, 2018

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). 2018. Singapore 1km Pregnancies. Version 1.0 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/WP00628

GeoTIFF