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The CMR Team would like to recommend that pyQuARC use the CMR API for basic validation checks (metadata schema, controlled vocabularies) rather than have a separate validation in pyQuARC. If there are changes to CMR validation, we want to ensure that users are not using outdated validation in pyQuARC. We also want to verify consistency between what results are provided to users in pyQuARC vs CMR.
Collection metadata can be validated at ingest or without having to ingest it. The validation performed is schema validation, UMM validation, and inventory specific validations. Keyword validation can be enabled with the keyword validation header. It returns status code 200 with a list of any warnings on successful validation, status code 400 with a list of validation errors on failed validation. Warnings would be returned if the ingested record passes native XML schema validation, but not UMM-C validation.
The CMR Team would like to recommend that pyQuARC use the CMR API for basic validation checks (metadata schema, controlled vocabularies) rather than have a separate validation in pyQuARC. If there are changes to CMR validation, we want to ensure that users are not using outdated validation in pyQuARC. We also want to verify consistency between what results are provided to users in pyQuARC vs CMR.
Collection metadata can be validated at ingest or without having to ingest it. The validation performed is schema validation, UMM validation, and inventory specific validations. Keyword validation can be enabled with the keyword validation header. It returns status code 200 with a list of any warnings on successful validation, status code 400 with a list of validation errors on failed validation. Warnings would be returned if the ingested record passes native XML schema validation, but not UMM-C validation.
The validation API is documented at https://cmr.earthdata.nasa.gov/ingest/site/docs/ingest/api.html#collection.
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