Support a standard vocabulary for dataset classification in the open-data-provider contract
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 50/100
Research direction
Start by reading docs/fds-alignment.md and locating the open-data-provider contract and its tests; the issue does not name their file paths. Compare the current free-text classification behavior with candidate vocabularies such as DCAT-AP-NL, then document a recommendation and assess whether optional validation or warnings can preserve existing profiles. Done means the recommendation is documented, tests cover the chosen behavior, and a CHANGELOG entry is added.
Written by the indexing model from the issue text.
Description
Problem statement
open-data-provider's classification field accepts any free-text string; docs/fds-alignment.md leaves adoption of a standard vocabulary (e.g. DCAT-AP-NL themes) to the operator. Free text makes metadata hard to check or compare across domains.
Acceptance criteria
- Decide on and document a recommended standard vocabulary.
- Optionally validate or warn on values outside it, without breaking existing profiles.
- Tests and CHANGELOG entry.
Estimated effort: 2-3 hours
- Dominant language
- Python
- Stars
- 8
- Forks
- 12
- Avg merge
- 1d 2h
- Merged PRs (30d)
- 93
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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