Low Resource Language Index Project
# Low Resource Language Data Readiness Index
A reproducible, automatically-updatable index measuring, for every major world language, how much non-synthetic, clearly-licensed text and audio data exists for training generative AI models — and how close each language is to the data thresholds real applications require.
Most AI language tools work well for a handful of high-resource languages and poorly, or not at all, for thousands of others — and this isn't just a function of speaker population: a language can have millions of native speakers and still be low-resource if it has limited representation online or in digital datasets. This index is designed to answer two practical questions: *how close is language X to being AI-ready?* and *where should future investment be directed* — toward collecting more data, improving data quality, or developing models? It's built as a World Bank Development Data Partnership initiative.
## New to this project? Start here.
If you're picking up this project without prior context, read the documents in **`Supplementary Information/`** before anything else:
- **`Index Overview.docx`** — a high-level overview of what the index measures and why, and how the whole project is structured.
- **`Next Steps.docx`** — outstanding work across every part of the project, with concrete next actions per section.
- **`Challenges.docx`** — major challenges already encountered, written up as problem/solution pairs, so you're not rediscovering the same issues from scratch.
- **`Contact Information.docx`** — who to reach out to for questions about different parts of the project.
- **`language-data-index-intern-workplan.docx`** — the original workplan this project was built against.
Together, these should give you the full picture of what this index is, what's been done, what's left, and who can help — before you go digging into individual tier folders.
## Project structure
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├── Supplementary Information/ project overview, next steps, challe …