World

The data relates to French development aid for projects carried out under sovereignty and in progress since 2015. This data may be published once the agreement of the counterparty has been obtained.The French Development Agency will aim to a quarterly update of the publication of these data, in particular to take into account the new development projects financed by the Agency. These data comply with the IATI (International Initiative for Aid Transparency) standard.

This dataset contains 29 data tables on global trends in forced displacement in 2017. The data provide trends and national and sometimes sub-national levels on refugees, asylum-seekers, internally displaced persons (IDPs), returnees (refugees and IDPs), stateless persons, and other persons of concern to UNHCR.

Topline figures from WFP's operations around the world.

Worldwide comprehensive metrics for children in the official primary school age range who are not enrolled in either primary or secondary schools.

OCHA ROMENA Topline Figures

The Office of the Geographer’s Global Large Scale International Boundary Detailed Polygons file combines two datasets, the Office of the Geographer’s Large Scale International Boundary Lines and NGA shoreline data. The LSIB is believed to be the most accurate worldwide (non- W. Europe) international boundary vector line file available. The lines reflect U.S. government (USG) policy and thus not necessarily de facto control. The 1:250,000 scale World Vector Shoreline (WVS) coastline data was used in places and is generally shifted by several hundred meters to over a km. There are no restrictions on use of this public domain data. The Tesla Government PiX team performed topology checks and other GIS processing while merging data sets, created more accurate island shoreline in numerous cases, and worked closely with the US Dept. of State Office of the Geographer on quality control checks. Methodology: Tesla Government’s Protected Internet Exchange (PiX) GIS team converted the LSIB linework and the island data provided by the State Department to polygons. The LSIB Admin 0 world polygons (Admin 0 polygons) were created by conflating the following datasets: Eurasia_Oceania_LSIB7a_gen_polygons, Africa_Americas_LSIB7a_gen_polygons, Africa_Americas_LSIB7a, Eurasia_LSIB7a, additional updates from LSIB8, WVS shoreline data, and other shoreline data from United States Government (USG) sources. The two simplified polygon shapefiles were merged, dissolved, and converted to lines to create a single global coastline dataset. The two detailed line shapefiles (Eurasia_LSIB7a and Africa_Americas_LSIB7a) were merged with each other and the coastlines to create an international boundary shapefile with coastlines. The dataset was reviewed for the following topological errors: must not self overlap, must not overlap, and must not have dangles. Once all topological errors were fixed, the lines were converted to polygons. Attribution was assigned by exploding the simplified polygons into multipart features, converting to centroids, and spatially joining with the newly created dataset. The polygons were then dissolved by country name. Another round of QC was performed on the dataset through the data reviewer tool to ensure that the conversion worked correctly. Additional errors identified during this process consisted of islands shifted from their true locations and not representing their true shape; these were adjusted using high resolution imagery whereupon a second round of QC was applied with SRTM digital elevation model data downloaded from USGS. The same procedure was performed for every individual island contained in the islands from other USG sources. After the island dataset went through another round of QC, it was then merged with the Admin 0 polygon shapefile to form a comprehensive world dataset. The entire dataset was then evaluated, including for proper attribution for all of the islands, by the Office of the Geographer.

This dataset contains 29 data tables on global trends in forced displacement in 2016. The data provide trends and national and sometimes sub-national levels on refugees, asylum-seekers, internally displaced persons (IDPs), returnees (refugees and IDPs), stateless persons, and other persons of concern to UNHCR.

WFP's Market Monitor analyzes market price data to find trends in the cost of the basic food basket. The Market Monitor is produced quarterly. More analysis and methodology information can be found at The Market Monitor.

This layer contains information about obstacles in different countries where WFP operates

This layer contains geodata about global railways

UNHAS (United Nations Humanitarian Air Service) routes for passenger and cargo air transport services used by humanitarian and development agencies and their implementing NGO partners

This layer contains information about global station of bus, train and ferry

Global supply routes for Transportation of Food and Non Food Items - Roads, Railways, Waterway, Airways. This layer is built by linking origin/destination locations using the most direct route on main roads. In reality, the supply routes can divert from the ones displayed here depending on many local factors. The routes shown in this dataset are only indicative and have to be used as such.

The City Prosperity Indices comprise six major components (Productivity, Infrastructure Development, Quality of Life, Equity and Social Inclusion, Environmental Sustainability, Urban Governance and Legislation) and each components has it own key ingredients and indicators which enable to calculate the city prosperity index of a city.

All WASH data for every country in the world. This document contains all data available on WASHwatch and is drawn from a variety of sources including WHO, UNICEF, OECD and World Bank. More information on the WASHwatch website: www.washwatch.org

Human Development Indicators by Country

Human Development Index trends

Fundamental Labour Rights

Educational Achievements

This dataset contains a list of events from 2000 to present during which someone died or went missing while trying to reach or stay in Europe. Details such as the date of the incident, the cause of death, number of dead and missing, location and coordinates of event are included.

Energy projects are being implemented in humanitarian contexts across the globe. These excel spreadsheets include all known past and present energy projects that have taken place in refugee camps, IDP communities, and other crisis-affected populations throughout the world, and were collected by the Global Alliance for Clean Cookstoves on behalf of the Safe Access to Fuel & Energy (SAFE) Humanitarian Working Group. To view full descriptions of the projects represented here, please visit www.safefuelandenergy.org/where-we-work. This project listing was created as part of an effort to enhance coordination of activities, encourage collaboration, and share knowledge between organizations working on Safe Access to Fuel and Energy (SAFE) in humanitarian settings. Projects included in this database are those that improve access to fuel or energy for cooking, lighting, heating, or powering among crisis-affected populations. By crisis-affected populations we mean refugees, internally displaced people (IDPs), or those affected by natural disaster or prolonged conflict. Examples of applicable energy interventions include providing solar lighting, manufacturing and/or distributing cookstoves and fuels, setting up mini grids for camp electrification, establishing and managing woodlots for fuel provision and environmental protection, improving protection mechanisms for women during firewood collection, and many others, provided they take place among crisis-affected populations. The SAFE Humanitarian Working Group is a consortium of partners including UNHCR, FAO, WFP, the Global Alliance for Clean Cookstoves, the Women's Refugee Commission, International Lifeline Fund, Mercy Corps, UNICEF, and other agencies. If you know of additional energy projects that are not shown here, please contact us at info@safefuelandenergy.org.

This dataset includes grants committed by foundations, public charities, and corporations for disasters and complex humanitarian emergencies from 2011 to 2015.

The dataset contains the old age dependency ratio which is computed from the people aged 65 and over and people aged 15 to 64 from data source OECD. It is given in the percentage.

The Global AgeWatch Index ranks countries by how well their older populations are faring.

The Disaster Risk and Age Index 2015 is a pilot initiative by HelpAge International which presents a unique snapshot of the disaster risk faced by older people in 190 countries across the world. It highlights which countries are doing the most to reduce the vulnerabilities and boost the capacities of their older populations in the face of disaster risk.