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

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

doi:10.5334/dsj-2021-017

Kaylin Bugbee, Valerie Dixon + Show 7 more

Open Access

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

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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.

Highlights

Since the launch of the TIROS-1 weather satellite in 1960, the availability of Earth observation data has expanded significantly
We present a quality framework for assessing NASA’s Earth observation metadata, a methodology for implementing the framework in an actionable manner, and a process for collaborating with metadata authors to improve quality
Updated records must be pushed to the aggregated catalog; otherwise no modifications are made to the metadata records within the aggregated catalog, and global metadata quality is not improved. While this operational philosophy is a good best practice for maintaining metadata quality across multiple databases, we suggest that the aggregator role should be expanded to enable metadata quality in collaboration with the discipline-specific data centers

Summary

Introduction

Since the launch of the TIROS-1 weather satellite in 1960, the availability of Earth observation data has expanded significantly. Earth observation data are often ‘found to be useful for additional purposes not foreseen during the development of the observation system’ (OSTP 2016). Discipline-specific data centers typically serve a specific scientific community and provide pertinent information and services needed by the community. Discipline-specific data center users are knowledgeable about the scientific context within which the data were collected and are generally familiar with the information and services provided by the data center. A prototypical example of a discipline-specific data center is the Alaska Satellite Facility Distributed Active Archive Center (ASF DAAC). The ASF DAAC’s search and discovery tools assume some knowledge of SAR and SAR observing platforms While these tools may work well for SAR subject matter experts, the ease of use may not translate to users outside of the community. Examples of other discipline-specific archives include the World Data Center for Climate/CERA at DKRZ (WDCC), the Crustal Dynamics Data Information System (CDDIS) and the Cambridge Crystallographic Data Centre

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