The American World Gazetteer

or too much text, too little time...

Tim Sherratt ยท @wragge

  • OCRd text from 83,135 digitised books (30gb)
  • Never mind the metadata โ€“ just give me everything!

The dataset

  • What's an API anyway?
  • Where's the API documentation?
  • Used the manifest to get list of files
  • Downloading was straightforward โ€“ 83,135 text files (30gb) in 5 days

Accessing the dataset

  • Encoding of text files
  • How many files are there?
  • OCR quality (of course!)
  • Not enough time!

Biggest obstacle

  • Exploring new data!
  • The challenges of scale (on a budget)
  • I learnt heaps!

What did I enjoy?

  • More time!
  • Clearer processing pipelines
  • Disambiguation and data cleaning?

What would I have done differently?

  • The world as seen from America?
  • 7,762,992 places from 34,570 books
  • Limited to 737 'countries' & linked to Wikidata
  • 1,393,125 sentences extracted from 10,155 books
  • Book metadata, countries, & sentences saved to SQLite, searchable through Datasette
  • American World Gazetteer app โ€“ random sentences from Datasette

How did you choose to represent the dataset?

  • What does 'access' and how does it change?
  • What's possible? Does large-scale analysis need large-scale resources?

Did you have a specific research question?

If you had endless amounts of time and money...

Outputs