The pyQuARC tool reads and evaluates metadata records with a focus on the consistency and robustness of the metadata. pyQuARC flags opportunities to improve or add to contextual metadata information in order to help the user connect to relevant data products. pyQuARC also ensures that information common to both the data product and the file-level metadata are consistent and compatible. pyQuARC frees up human evaluators to make more sophisticated assessments such as whether an abstract accurately describes the data and provides the correct contextual information. The base pyQuARC package assesses descriptive metadata used to catalog Earth observation data products and files. As open source software, pyQuARC can be adapted and customized by data providers to allow for quality checks that evolve with their needs, including checking metadata not covered in base package.
Overview:
In the pyQuarc, while running this collection (C2098742955-LARC (dif10)), it does not show the Use_Constraints errors.
Changes made:
Added if condition in _get_path_value_recursively function in custom_checker.py file.
Now, Use_Constraints errors are shown for the collection C2098742955-LARC (dif10).
This is the pull request to solve this issue.
Overview: In the pyQuarc, while running this collection (C2098742955-LARC (dif10)), it does not show the Use_Constraints errors.
Changes made: Added if condition in _get_path_value_recursively function in custom_checker.py file. Now, Use_Constraints errors are shown for the collection C2098742955-LARC (dif10).
Tested on these different dif10 collections: