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.
<Collection/CitationforExternalPublication>: check whether the dataset citation is provided in the metadata.
Describe the checks in steps
Check whether the "Collection/CitationforExternalPublication" field is populated with a dataset citation.
If not, provide a warning message stating, "No CitationforExternalPublication" is provided. Recommend providing a citation for the dataset in the "CitationforExternalPublication" field."
Is there a similar check already implemented? Please list the name of the check
Additional context
Refer to the "Collection Citation Presence Check" in the QA Rules spreadsheet for more information.
slesaad
commented
3 years ago 
Addressed by: bcfe991
Is this a new check? Please describe the check and the field. <Collection/CitationforExternalPublication>: check whether the dataset citation is provided in the metadata.
Describe the checks in steps
Is there a similar check already implemented? Please list the name of the check
Additional context Refer to the "Collection Citation Presence Check" in the QA Rules spreadsheet for more information.