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.
Is this a new check? Please describe the check and the field.
</DIF/Project/Long_Name>: Provide a warning if a long name is not provided
Describe the checks in steps
Check to see if the provided project short name has an associated project long name.
If it does, check to make sure the project long name field is provided with the correctly associated project long name.
If there is no project long name provided, provide a warning that states: "The project long name is missing. Please add the associated project long name: {}"
Is there a similar check already implemented? Please list the name of the check
campaign_name_presence_check
Is this a new check? Please describe the check and the field. </DIF/Project/Long_Name>: Provide a warning if a long name is not provided
Describe the checks in steps
Is there a similar check already implemented? Please list the name of the check campaign_name_presence_check