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

Q2 Computer Science Data Science Journal Pub Date : 2021-04-28 DOI:10.5334/DSJ-2021-017
K. Bugbee, J. le Roux, Adam W. Sisco, A. Kaulfus, Patrick Staton, Camille Woods, V. Dixon, C. Lynnes, R. Ramachandran
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引用次数: 7

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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通过元数据质量评估改进NASA地球观测数据的发现和使用
高质量的描述性元数据对于向越来越多的不同用户有效发现地球观测数据至关重要。在本文中,我们定义了一个框架来评估NASA地球观测元数据的质量,其总体目标是提高其所描述数据的可发现性、可访问性和可用性。该框架由公共元数据存储库的分析和审查(ARC)团队开发,重点关注正确性、完整性和一致性等元数据质量维度。描述了ARC团队实施该框架所使用的方法,以及实施类似元数据质量评估流程的最佳实践、经验教训和建议。项目的初步结果表明,这种方法结合社区和利益相关者的协作,在提高元数据质量方面是有效的。
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来源期刊
Data Science Journal
Data Science Journal Computer Science-Computer Science (miscellaneous)
CiteScore
5.40
自引率
0.00%
发文量
17
审稿时长
10 weeks
期刊介绍: The Data Science Journal is a peer-reviewed electronic journal publishing papers on the management of data and databases in Science and Technology. Details can be found in the prospectus. The scope of the journal includes descriptions of data systems, their publication on the internet, applications and legal issues. All of the Sciences are covered, including the Physical Sciences, Engineering, the Geosciences and the Biosciences, along with Agriculture and the Medical Science. The journal publishes papers about data and data systems; it does not publish data or data compilations. However it may publish papers about methods of data compilation or analysis.
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