In 2015, The 17 United Nations’ Sustainable Development Goals were adopted. ‘spiR’ is a wrapper of several open datasets published by the Social Progress Imperative (https://www.socialprogress.org/), including the Social Progress Index (a synthetic measure of human development across the world). ‘spiR’‘s goal is to provide data to help policymakers and researchers prioritize actions that accelerate social progress across the world in the context of the Sustainable Development Goals. The Social Progress Index proposes a new perspective on social challenges and needed efforts to accelerate social progress in line with the Sustainable Development Goals. In this context, the goal of ’spiR’ is to allow an easy connection with R to the Social Progress Index in order to benefit from the “power of crowds.” ‘spiR’ is an R wrapper to easily access the Social Progress Index datasets.
At the Social Progress Imperative, they define “social progress as the capacity of a society to meet the basic human needs of its citizens, establish the building blocks that allow citizens and communities to enhance and sustain the quality of their lives, and create the conditions for all individuals to reach their full potential. Improving quality of life is a complex task and past efforts to measure progress simply haven’t created a sufficiently nuanced picture of what a successful society looks like. That’s why we created the Social Progress Index. Rather than emphasizing traditional measurements of success like income and investment, we measure 51 social and environmental indicators to create a clearer picture of what life is really like for everyday people. The index doesn’t measure people’s happiness or life satisfaction, focusing instead on actual life outcomes in areas from shelter and nutrition to rights and education. This exclusive focus on measurable outcomes makes the index a useful policy tool that tracks changes in society over time.”
The index measures the quality of life for 98% of the world’s population. In its current version, the R client provides access to global data. In further versions, this R client will include different geographical levels: states, regions, cities and sometimes communities.
Three overarching dimensions are (1) Basic Human Needs, (2) Foundations of Wellbeing, and (3) Opportunity. Within each dimension, there are four components that further divide the indicators into thematic categories. The index consists in 51 social and environmental variables, covering the years 2014 to 2019.
To see a definition of the indicators, please visit this page.
To read the methodology summary of the Social Progress Index [here]
See below to have access through ‘spiR’ to the whole list of indicators.
Users can recreate in R impactful dashboards and visualizations as the ones found on www.socialprogress.org: click here
The released version of spiR package is accessible through CRAN and devtools.
A user needs to enter the ISO code of a country. To have access to this code, the following function provides this information.
spir_country() # A list of all countries will be produced
spir_country(country = "Canada") # The ISO code for Canada will be produced
spir_country("Canada") # The ISO code for Canada will be producedA user needs to enter the code of the desired indicator. To do so, the following function provides access to all the indicators of interest.
spir_indicator() # A list of all indicators will be produced
spir_indicator(indicators = "mortality") # A list with all the variables including "mortlity" will be produced
spir_indicator("mortality") # A list with all the variables including "mortlity" will be producedOnce the user knows the ISO code and the indicator’s code, s.he can collect the data in a very easy way through this function:
spir_data(country = c("USA", "FRA"), year = c("2018", "2019"), indicators = "SPI") # It generates a data frame of the overall SPI indicator for the USA and France for the years 2018 and 2019
spir_data(country = c("USA", "FRA"), years = "2018", ) # It generates a data frame of all the indicators for the USA and France for the year 2018
spir_data("USA", "2019", c("SPI", "FOW")) # It generates a data frame of the SPI and FOW indicators for the USA in 2019
spir_data(, "2018", ) # It generates a data frame for all the countries and all the indicators for 2018
spir_data("USA", "2017", ) # It generates a data frame of all the indicators for the USA in 2017
spir_data("USA", , ) # It generates a data frame of all the indicators for all the years for the USA
spir_data(, , ) # It generates a data frame of the complete dataset
spir_data() # It generates a data frame of the complete datasetspir_visual fonction allows to create two types of visuals from the SPI data : barchart and linechart.
The first is a barchart of the top 9 countries for the chosen indicator and year.
The second is a linechart showing the evolution of the most represented countries over time for the chosen indicator.
If you use the spiR package for research, education, policymaking or other related purposes, please cite the package as well as the Social Progress Imperative. Consider making them a donation to help them pursue the work. Business, social enterprises and investors interested in using the Social Progress Index should contact their offices.
To cite the ‘spiR’ package in your work:
Warin, T. (2019). “spiR: Client for the Social Progress Index. v0.2.1.”
@article{Warin2019,
author = "Thierry Warin",
title = "{spiR: An R Package for the Social Progress Index}",
year = "2019",
month = "12",
url = "https://figshare.com/articles/spiR_Client_for_Social_Progress_Index_Data/11421573/",
doi = "10.6084/m9.figshare.11421573.v2"
}The author would like to thank the Center for Interuniversity Research and Analysis of Organizations (CIRANO, Montreal) for its support, as well as Thibault Senegas, Marine Leroi and Martin Paquette. The usual caveats apply.