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Under-five Mortality Dataset - v11 via Gapminder
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About this fileThis file has multiple sheets with data for one or more indicators used by Gapminder. In this sheet below you'll first find an overview of the indicators (measures) and the list of underlying sources. The actual data we use, is found in the sheet(s) labeled "data-...".
This file is also a documentation of the data process. To follow how the data was transformed from the original sources, start in the sheet to the far right, which holds the input data. You can then follow the process step by step, by looking at the formulas in the sheets from right to left, until you reach the output in the "data-..." sheets.
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Version:v11
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Updated:January 30 2020
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Download latest version:Excel file »
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Latest version online:http://gapm.io/du5mr
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Contributor(s) to this version: Diane I
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FeedbackPlease give feedback here
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#Indicator(s)DescriptionFull nameUnitIDtypeUsage
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1Child mortalityThis is the probability of dying between birth and exactly five years of age expressed per 1,000 live birthsUnder-five mortlality ratedeaths per 1000 live birthsu5mrmeasure2
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Sources
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Dataset description:This file contains data on child mortality rates compiled by Gapminder, based on multiple sources: — 1800 to 1950: Gapminder v7 ( In some cases this is also used for years after 1950, see below.) This was compiled and documented by Mattias Lindgren from many sources, but mainly based on www.mortality.org and the series of books called International Historical Statistics by Brian R Mitchell, which often have historic estimates of Infant mortality rate which were converted to Child mortality through regression. See detailed documentation of v7 below.
— 1950 to 2018: UNIGME, is a data collaboration project between UNICEF, WHO, UN Population Division and the World Bank. They released new estimates of child mortality for countries and a global estimate on September 19, 2019, which is available at www.childmortality.org. In this dataset 70% of all countries have estimates between 1970 and 2016, while roughly half the countries also reach back to 1950.
— 1950 to 2100: UN WPP, World Population Prospects 2019 provides annual data for Child mortality rate for all countries in the annually interpolated demographic indicators, called WPP2019_INT_F01_ANNUAL_DEMOGRAPHIC_INDICATORS.xlsx In In general, We connected our historic estimates from Gapminder v7 to the earliest available year with data in UNIGME or if it didn’t have data, we used UN POP from 1950 and on, until UNIGME had data. Depending on data availability, different countries are moving between sources at different points in the period 1930-1980.After 2018, we have extended the UN IGME series with the UN POP numbers. But we haven't extended it with the UN POP actual numbers but instead, we extended it with the UN POP expected change. The data is part of Gapminder effort to build a fact-based worldview by showing the big picture of global development. When we find multiple data sources that haven't been combined we combine them into one consistent timeseries. This often results in large data uncertainty, as the underlaying data-sources use different methodologies etc. But we still dare to combine data that hasn't been combined, as we find it extremely important to visualize the big picture, which people otherwise tend to get absolutely wrong. Before using our data for any other purpose though, please read the documentation to make sure you are aware of our levels of doubts in the data.
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Link to documentation:http://gapm.io/du5mr
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Short source summary:GN based on IGME & UNPOP
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#Source idNameLink
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1gm2015GM- child Mortality v7
https://www.gapminder.org/data/documentation/gd005/
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2igme2019UN IGME, Child Mortality estimates,2018https://childmortality.org
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3wpp2019UN POP, World Population Prospects 2019
https://population.un.org/wpp/Download/Standard/Interpolated/
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License
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Attribution:
We believe in free knowledge and therefor we share free data. Most sheets in this file are provided under the open license, called Creative Commmon Attribution License CC BY 4.0., except those sheets mentioned in the exceptions section below. This means you can freely use, copy, and spread the data in those sheets, as long as you mention the following: 'Free data from Gapminder.org'.
You should also mention the underlaying data sources listed above and include this link: http://gapm.io/du5mr
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License link:Creative Common License CC BY 4.0
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Exceptions:
The sheets starting with the word "data" are covered by this license. Other sheets are included for documentation purpose, and may include data that is governed by other licenses. Check the underlying sources for the specific licenses in these cases.
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VersionsLink
Changes compared to previous
DateContributors
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v1-First version--
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v2----
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v3----
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v4----
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v5----
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v6----
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v7https://www.gapminder.org/data/documentation/gd005/Mattias Lindgren2015 January 1Mattias Lindgren
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v8----
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v9----
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v10https://www.gapminder.org/data/documentation/gd005/
New data from IGME 2017 and UNPOP, WPP2017
--
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v11
https://docs.google.com/spreadsheets/d/1Av7eps_zEK73-AdbFYEmtTrwFKlfruBYXdrnXAOFVpM/edit#gid=501532268
New data from IGME 2019 and UNPOP, WPP2019
#REF!#REF!
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Technical stuff
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Dataset name:Under-five Mortality
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Dataset id:u5mr
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Doc urlhttps://docs.google.com/spreadsheets/d/1Av7eps_zEK73-AdbFYEmtTrwFKlfruBYXdrnXAOFVpM/edit#gid=501532268
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Doc id of work doc spreadsheet1Av7eps_zEK73-AdbFYEmtTrwFKlfruBYXdrnXAOFVpM
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FormulasThe formulas in this workbook may be referring to other spreadsheets online, by their named ranges, and not by sheet names. Search for "named ranges" to see how to use those instead of cell ranges.
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For developersIf you like the data we use into your own products, it's better if you fetch data from our standardized gitHub repo on https://open-numbers.github.io
These spreadsheets are part of Gapminder's data compilation process and allow end users to track how we combine data.
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Read more:gapm.io/dataworks
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CHART PREVIEWS
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[c]
data-for-countries-etc-by-year
https://www.gapminder.org/tools/#$state$time$dim=time;&entities$dim=geo;&entities_colorlegend$dim=geo;&marker$axis_x$which=income_per_person_gdppercapita_ppp_inflation_adjusted&scaleType=log&spaceRef:null;&axis_y$data=data_&which=Child%20mortality&spaceRef:null;&label$which=name&scaleType=ordinal;&size$which=population_total&use=indicator&scaleType=linear;&color$which=_default&use=constant&scaleType=ordinal;;;&data$reader=ddfbw&service=https:////big-waffle.gapminder.org&dataset=sg-master&translateContributionLink:///crowdin.com//project//systema-globalis;&data_$reader=google_csv&path=https:////docs.google.com//spreadsheets//d//1Av7eps_zEK73-AdbFYEmtTrwFKlfruBYXdrnXAOFVpM//gviz//tq?tqx=out:csv/&sheet=data-for-countries-etc-by-year&hasNameColumn:true&nameColumnIndex:1;&chart-type=bubbles
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Child%20mortality
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DDF mapping:schema for indicator table
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concept_id6
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name_short2
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name4
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description3
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unit5
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type7
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usage8
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Catalog statusIndicator IDTime unit
Countries etc
RegionsIn. LevelsWorld
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Child mortalityu5mryearGOODGOOD-GOOD
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#Validation
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1output-sheetsGOOD: There is at least one output sheet present (sheets starting with 'data-for-' and not ending with '-in-columns')
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output-sheet:data-for-world-by-year
GOOD: The 'data-for-world-by-year' output sheet has at least 4 header columns
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output-sheet:data-for-world-by-year
GOOD: The 'data-for-world-by-year' output sheet does not have filter mode turned on (since it breaks the CSV endpoint)
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output-sheet:data-for-regions-by-year
GOOD: The 'data-for-regions-by-year' output sheet has at least 4 header columns
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output-sheet:data-for-regions-by-year
GOOD: The 'data-for-regions-by-year' output sheet does not have filter mode turned on (since it breaks the CSV endpoint)
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output-sheet:data-for-countries-etc-by-year
GOOD: The 'data-for-countries-etc-by-year' output sheet has at least 4 header columns
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output-sheet:data-for-countries-etc-by-year
GOOD: The 'data-for-countries-etc-by-year' output sheet does not have filter mode turned on (since it breaks the CSV endpoint)
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8versionGOOD: Named range 'version' exists
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9versionGOOD: 'Version:' is filled in
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10versionGOOD: The version at 'Version:' starts with a v, followed by an integer
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11dateGOOD: Named range 'date' exists
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12dateGOOD: 'Updated:' is filled in
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13gapmioGOOD: Named range 'gapmio' exists
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14gapmioGOOD: 'Latest version online:' is filled in
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15contributorsGOOD: Named range 'contributors' exists
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16contributorsGOOD: 'Contributor(s) to this version:' is filled in
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17indicator_tableGOOD: Named range 'indicator_table' exists
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18indicator_tableGOOD: The named range 'indicator_table' covers the whole Indicator(s) table (the rows immediately above and below the table are empty)
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19indicator_table:row_1GOOD: This first column of row '1' in the indicator(s) table is incremental (from 1 and up)
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20indicator_table:row_1GOOD: Indicator 1 has a short indicator name (Column 2)
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indicator_table:row_1:data-for-world-by-year
GOOD: The indicator name cell of indicator 1 is referenced in the 'data-for-world-by-year' output sheet in column 4 as "=ABOUT!B11"
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indicator_table:row_1:data-for-regions-by-year
GOOD: The indicator name cell of indicator 1 is referenced in the 'data-for-regions-by-year' output sheet in column 4 as "=ABOUT!B11"
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indicator_table:row_1:data-for-countries-etc-by-year
GOOD: The indicator name cell of indicator 1 is referenced in the 'data-for-countries-etc-by-year' output sheet in column 4 as "=ABOUT!B11"
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24indicator_table:row_1GOOD: Indicator 1 has a description (Column 3)
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25indicator_table:row_1GOOD: Indicator 1 has a full name (Column 4)
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26indicator_table:row_1GOOD: Indicator 1 has a unit (Column 5)
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27indicator_table:row_1GOOD: Indicator 1's unit does not start or end with a space
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28indicator_table:row_1GOOD: Indicator 1 has an ID (Column 6)
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29indicator_table:row_1GOOD: Indicator 1's ID contains only lowercase latin characters (a-z) or numbers, and no space, dashes or underscores. (Column 6)
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30indicator_table:row_1GOOD: Indicator 1's ID has less than or equal to 20 characters
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31indicator_table:row_1GOOD: Indicator 1 has a type set (Column 7)
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32indicator_table:row_1GOOD: Indicator 1 has a usage level set (Column 8)
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33dataset_descriptionGOOD: Named range 'dataset_description' exists
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34dataset_descriptionGOOD: 'Dataset description:' is filled in
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35source_urlGOOD: Named range 'source_url' exists
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36source_urlGOOD: 'Link to documentation:' is filled in