NASA makes nearly 19,000 Earth science data products freely and openly available to all users. NASA is committed to accelerating open science by making these products easier to discover and use. NASA achieves this goal by providing and maintaining high quality metadata through the Common Metadata Repository (CMR).

Through the Analysis and Review of the CMR (ARC) Project, NASA's Office of Data Science and Informatics (formerly the Interagency Implementation and Advanced Concepts Team, or IMPACT) developed a strategy for conducting metadata quality assessments of CMR records. ARC completed these assessments using a framework that consists of a series of automated and manual checks of metadata attributes. The assessments were shared with data providers, who worked to improve the metadata quality over time.

The ARC team developed pyQuARC, an open source, Python-based library that automates the ARC assessment framework as much as possible. The tool can read and evaluate metadata records with a focus on the consistency and robustness of the metadata. Using pyQuARC also ensures that information common to both the data product and the file-level metadata are consistent and compatible. For example, a check can be performed to ensure the spatial extent specified in the data product’s metadata encompasses the cumulative extent of the individual data files.

pyQuARC can flag opportunities to improve or add to contextual metadata information in order to help the user connect to relevant data products and frees up human evaluators to make more sophisticated assessments, such as whether an abstract accurately describes the data and provides the correct contextual information. A well-documented data product with detailed and sufficient metadata is easier to find, easier to understand, and easier to use. As open source software, pyQuARC can be adapted and customized by a data provider to allow for quality checks that evolve with their needs, including checking metadata not included in the CMR.