Grand Cape Mount

Data Dictionary: https://github.com/wri/Aqueduct40/blob/master/data_dictionary_country-rankings.md#country-future  

Data sited at: The Humanitarian Data Exchange  https://data.humdata.org/ Publication URL: https://data.hdx.rwlabs.org/dataset/sub-national-data-of-confirmed-cumulative-ebola-by-gender License: https://creativecommons.org/licenses/by/4.0/   The dataset only contains data on the confirmed Ebola cases. This dataset is updated occasionally.

Ebola : Sub-national time series data on Ebola cases and deaths, 2015

Data citation: Data retrieved from the Area Database of the Global Data Lab, https://globaldatalab.org/areadata/, Version 4.4.1Smits, J. GDL Area Database. Sub-national development indicators for research and policy making.Smits GDL Working Paper 16-101 v44.pdf Smits GDL Working Paper 16-101 v44.docx

This Dataset shows the modelled parasite rate for Plasmodium falciparum for the years 2000-2015 for all African countries where it is endemic. The Dataset shows the percentage of 2-10 year olds infected by the parasite for each year.

Postharvest loss profiles (PHL profiles) quantify the expected loss – as a percentage – at each point along the postharvest chain. This loss data is collected by reviewing scientific literature and is broken down by crop, type of farm and climate type (based on the Köppen-Geiger climate classification). These profiles provide percentage loss figures for the various crops throughout the value chain under varying conditions and are updated as new research becomes available."   For complete reference information and definitions, Please visit: https://www.aphlis.net/en/page/20/data-tables#/datatables?year=20&tab=references&metric=prc

This dataset provides data on literacy rates, primary and secondary school attendance rates access to improved water and sanitation, household access to electricity, and household ownership of radio and television. Unlike other datasets, notably the World Bank’s World Development Indicators (WDI), this dataset provides data at the subnational level, specifically the first administrative district level. Furthermore, the data is comparable both within and across countries. This subnational level of data allows for assessment of education and household characteristics at a more relevant level for allocation of resources and targeting development interventions.

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/    

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/  

Travel & Tourism is a truly global economic activity – one which takes place in destinations across the world, from leading capital cities and smaller towns and villages in rural and coastal areas, to some of the remotest points on the planet. It is one of the world’s largest industries, or economic sectors, contributing trillions of dollars annually to the global economy, creating jobs and wealth, generating exports, boosting taxes and stimulating capital investment