Unfortunately not able to do all the steps for a pull request (sorry!), but here is a suggested dataset including relevant links to sources and information and a cleaning script.

The original data is released as CC-BY 4.0 and should be cited as:

Hammarström, Harald & Forkel, Robert & Haspelmath, Martin & Bank, Sebastian. 2025. Glottolog 5.2.1. Leipzig: Max Planck Institute for Evolutionary Anthropology. (Available online at https://glottolog.org/)

Glottolog is the most comprehensive language database in linguistics, and contains information (names, genealogy, geographical information, endangerment status, etc.) of over 8,000 languages of the world.

• This dataset has not already been used in TidyTuesday.

• The dataset will (probably) be less than 20MB when saved as a tidy CSV.

• I can imagine a data visualization related to this dataset.

• title: The Languages of the World

• article: An example of the dataset being used, such as a blog post or a README about the dataset.

  • title: "Glottolog: A Free, Online, Comprehensive Bibliography of the World’s Languages", but more relevant information at https://glottolog.org and https://glottolog.org/langdoc/status
  • url: The link to the article. https://pure.mpg.de/rest/items/item_2354764/component/file_2354763/content

• data_source:

  • title: Glottolog 5.2
  • url: https://github.com/glottolog/glottolog-cldf/tree/master/cldf, also https://zenodo.org/records/15525265

• images: One or more images related to the dataset. For each image, provide:

  • file: A url to download the image, or an attached file.
  • alt: Text that can serve as a replacement for the image for those who cannot see the image (whether through visual impairment or because the image does not load).

• cleaning_script: A script to fetch and clean the data, resulting in one or more data.frames (or equivalent structures) that can be saved as CSVs.

# Download raw data and filter to endangered status
endangered_status <- 
  readr::read_csv("https://raw.githubusercontent.com/glottolog/glottolog-cldf/refs/heads/master/cldf/values.csv") |> 
  dplyr::filter(Parameter_ID == "aes") |> 
  dplyr::select(Language_ID, Value, Code_ID) |> 
  dplyr::rename(id = Language_ID,
                status_code = Value,
                status_label = Code_ID) |> 
  dplyr::mutate(status_label = stringr::str_replace(stringr::str_remove(status_label, "^aes-"), "_", " "))

# Download language and family data
fam_lgs <- 
  readr::read_csv("https://raw.githubusercontent.com/glottolog/glottolog-cldf/refs/heads/master/cldf/languages.csv")

# Filter and clean language family data
families <- 
  fam_lgs |> 
  dplyr::filter(Level == "family") |> 
  dplyr::select(ID, Name) |> 
  dplyr::rename(Family = Name) |> 
  dplyr::rename_with(stringr::str_to_lower, dplyr::everything())

# Filter and clean language data
languages <- 
  fam_lgs |> 
  dplyr::filter(Level == "language") |> 
  dplyr::select(ID, Name, Macroarea, Latitude, Longitude, ISO639P3code, Countries, Is_Isolate, Family_ID) |> 
  dplyr::rename_with(stringr::str_to_lower, dplyr::everything()) 

• data_dictionary: A description of each column in the dataset, including the column name, the data type of the column, and a description of the column.

languages

families

endangered_status