Inconsistency of metadata validation in API's
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- Dominant language
- Java
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Description
There is inconsistency in metadata validation in Dataverse APIs.
For example, one can create a dataset without a required metadata field such as "Subject". Using API one can also add files for that dataset and update metadata of a dataset without a problem. But updating file metadata of that dataset will fail on schema validation. Also delete file SWORD api will fail on validation.
It seems more logical either to require to have required fields in dataset creation api and update dataset metadata API or remove validation from update file metadata and delete file SWORD api.
Contributor 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.
Research direction
Start by locating the dataset creation, dataset metadata update, file metadata update, and file-delete SWORD API entry points, then compare where schema validation is applied. Determine the intended consistent validation policy with maintainers and add coverage for the affected API operations; done means all relevant endpoints handle required metadata consistently.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- java
- Domain
- api, backend
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100