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UN-Water Global Analysis and Assessment of Sanitation and Drinking-water

GLAAS provides policy and decision-makers at all levels with reliable, easily accessible, comprehensive data on water, sanitation and hygiene (WASH) systems, including on governance, monitoring, human resources and finance. GLAAS monitors elements of WASH systems that are required to sustain and extend WASH services and systems to all, and especially to the most vulnerable population groups.


Installation

You can install the development version of glaas from GitHub with:

devtools::install_github("openwashdata/glaas", dependencies = TRUE)

Download as CSV Files

If you prefer to work with the data outside of R, you can download individual datasets as CSV files.

  1. Right-click on the “Download CSV” link for the dataset you want.
  2. Select “Save Link As” or “Download Linked File” .
  3. Choose where you’d like to save the file on your computer.
dataset CSV
glaas Download CSV

Data

glaas

The dataset glaas has 263033 observations and 18 variables

get(glaas) |> 
  head(3) |> 
  gt::gt() |>
  gt::as_raw_html()
GrandParentText ParentText IndText_HL LocText Time IsComparable_2013 IsComparable_2016 IsComparable_2018 IsComparable_2021 IsComparable_2024 Dim1ValText Dim2ValText Dim3ValText Dim4ValText Dim5ValText Dim6ValText ValText DataType
Finance Domestic absorption Absorption of domestic capital commitments (estimated %) Brazil 2016 TRUE TRUE TRUE TRUE TRUE Drinking-water Urban NA NA NA NA Between 50 to 75% Text
Finance Domestic absorption Absorption of domestic capital commitments (estimated %) Brazil 2013 TRUE TRUE TRUE TRUE TRUE Drinking-water Urban NA NA NA NA Less than 50% Text
Finance Domestic absorption Absorption of domestic capital commitments (estimated %) Barbados 2021 FALSE TRUE TRUE TRUE FALSE Sanitation Rural NA NA NA NA No response Text

For an overview of the variable names, see the following table.

variable_name variable_type description
GrandParentText character The high-level category or domain of the data, such as Finance, Governance, or Monitoring.
ParentText character The specific subcategory or topic within the high-level category, such as Domestic absorption or External funding absorption.
IndText_HL character The detailed description or indicator text for the high-level category, providing context or specific details about the data.
LocText character The location or country associated with the data, such as Brazil or Barbados.
Time numeric The year in which the data was recorded or the time period of the data.
IsComparable_2013 logical A boolean value indicating whether the data is comparable to the data from 2013.
IsComparable_2016 logical A boolean value indicating whether the data is comparable to the data from 2016.
IsComparable_2018 logical A boolean value indicating whether the data is comparable to the data from 2018.
IsComparable_2021 logical A boolean value indicating whether the data is comparable to the data from 2021.
IsComparable_2024 logical A boolean value indicating whether the data is comparable to the data from 2024.
Dim1ValText character The first dimension value text, representing categories such as Drinking-water or Sanitation.
Dim2ValText character The second dimension value text, representing categories such as Urban or Rural.
Dim3ValText character The third dimension value text, representing categories such as National* or Address.
Dim4ValText character The fourth dimension value text, representing categories such as Behaviour change improvement initiatives or Standards or regulations.
Dim5ValText character The fifth dimension value text, representing categories such as Themes or Quality.
Dim6ValText logical The sixth dimension value text, representing categories such as Sufficiency or Treated.
ValText character The value text, providing specific details or descriptions about the data, such as Between 50 to 75% or No response.
DataType character The data type of the column, indicating whether the data is Text or Decimal.

License

Data are available as CC-BY.

Citation

#> To cite package 'glaas' in publications use:
#> 
#>   Massari N (2025). "glaas: UN-Water Global Analysis and Assessment of
#>   Sanitation and Drinking-water." doi:10.5281/zenodo.15497462
#>   <https://doi.org/10.5281/zenodo.15497462>,
#>   <https://github.com/openwashdata/glaas>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Misc{massari:2025,
#>     title = {glaas: UN-Water Global Analysis and Assessment of Sanitation and Drinking-water},
#>     author = {Nicolo Massari},
#>     year = {2025},
#>     doi = {10.5281/zenodo.15497462},
#>     url = {https://github.com/openwashdata/glaas},
#>     abstract = {GLAAS provides policy and decision-makers at all levels with reliable, easily accessible, comprehensive data on water, sanitation and hygiene (WASH) systems, including on governance, monitoring, human resources and finance. GLAAS monitors elements of WASH systems that are required to sustain and extend WASH services and systems to all, and especially to the most vulnerable population groups.},
#>     version = {0.1.3},
#>   }