Improving Discovery and Use of NASA’s Earth Observation Data Through Metadata Quality Assessments

Kaylin Bugbee; Jeanné le Roux; Adam Sisco; Aaron Kaulfus; Patrick Staton; Camille Woods; Valerie Dixon; Christopher Lynnes; Rahul Ramachandran

doi:10.5334/dsj-2021-017

Improving Discovery and Use of NASA’s Earth Observation Data Through Metadata Quality Assessments

Authors

Kaylin Bugbee NASA https://orcid.org/0000-0001-6733-5698
Jeanné le Roux University of Alabama in Huntsville https://orcid.org/0000-0002-8274-987X
Adam Sisco University of Alabama in Huntsville https://orcid.org/0000-0002-5974-3402
Aaron Kaulfus NASA https://orcid.org/0000-0002-8319-1126
Patrick Staton University of Alabama in Huntsville https://orcid.org/0000-0002-9415-2413
Camille Woods University of Alabama in Huntsville https://orcid.org/0000-0002-7586-9021
Valerie Dixon NASA https://orcid.org/0000-0002-5125-2270
Christopher Lynnes NASA https://orcid.org/0000-0001-6744-3349
Rahul Ramachandran NASA https://orcid.org/0000-0002-0647-1941

DOI:

https://doi.org/10.5334/dsj-2021-017

Keywords:

Metadata quality, Stewardship, Accessibility, Usability, Information Management, Assessment Framework

Abstract

High quality descriptive metadata is essential to enabling the effective discovery of Earth observation data to a growing number of diverse users. In this paper, we define a framework to assess the quality of NASA’s Earth observation metadata with the overarching goal of improving the discoverability, accessibility and usability of the data it describes. The framework, developed by the Analysis and Review of the Common Metadata Repository (ARC) team, focuses on the metadata quality dimensions of correctness, completeness, and consistency. The methodology used by the ARC team to implement the framework is described, as well as best practices, lessons learned and recommendations for implementing similar metadata quality assessment processes. Initial results from the project indicate that this methodology, in combination with community and stakeholder collaboration, is effective in improving metadata quality.

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Published

2021-04-28

Issue

Vol. 20 (2021)

Section

Research Papers

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