Last year we posted about the pyQuARC tool, an open source library for Earth observation metadata quality assessment that assists data curators in assessing the correctness, completeness, and consistency of NASA’s Earth observation metadata. The functionality of the tool continues to be refined and expanded. Today we are spotlighting two members of the pyQuARC development team who are central to its success.
Sparking Collaborations with pyQuARC
Slesa Adhikari is part of IMPACT’s development group and brings her skill and talent as a coder to the pyQuARC project. She serves as the lead developer on the project and is responsible for designing and implementing the architecture of the pyQuARC application, programming automated checks based on specifications provided by the larger ARC team (Analysis and Review of the CMR), and supporting the ARC team in the maintenance of the project. Slesa sees the value of the pyQuARC tool in the way it provides easy, automated assessment of metadata, which makes data more accessible, searchable, and usable. This is a value-added which she believes can be leveraged by many applications:
"It’s been great to see pyQuARC being considered for and adapted to many other projects such as the Commercial SmallSat Data Acquisition Program, the Multi-Mission Algorithm and Analysis Platform, and NASA’s Metadata Management Tool. It’s exciting to see something you were a part of building turn into something big and useful to so many other projects."
Jenny Wood is part of the IMPACT Earth science team. She came to the pyQuARC project through her involvement in the larger ARC team’s efforts to improve the quality of NASA’s Earth observation metadata records. She brings to the pyQuARC project her knowledge of the metadata standards that need to be implemented and an understanding of the desired output from the tool. Her expertise has facilitated effective communication within the team, especially between the ARC Earth science and development teams. She has found this inter-team collaboration to be especially rewarding:
"By working closely with other team members, it’s allowed me the opportunity to learn better coding practices, gain more comfort with Python and Git, and understand the tool development process. Now that the tool is being integrated within our CMR Metadata Curation Dashboard, we get to see pyQuARC in action, assisting us in our curation efforts and increasing our efficiency. Seeing the tool gain interest in the broader community has also been inspiring, and I’m excited to see what else comes out of it!"
More details about the pyQuARC tool are available through the links below:
Description and details as well as technical user guide