Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets

Q2 Computer Science Data Science Journal Pub Date : 2020-12-15 DOI:10.31219/osf.io/nwe5p
G. Peng, R. Downs, C. Lacagnina, H. Ramapriyan, I. Ivánová, D. Moroni, Yaxing Wei, Larnicol Gilles, L. Wyborn, Mitchell Goldberg, J. Schulz, I. Bastrakova, A. Ganske, L. Bastin, S. Khalsa, Mingfang Wu, C. Shie, N. Ritchey, Dave Jones, T. Habermann, C. Lief, Iolanda Maggio, M. Albani, S. Stall, Lihang Zhou, M. Drévillon, Sarah M. Champion, C. Hou, F. Doblas-Reyes, K. Lehnert, E. Robinson, K. Bugbee
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引用次数: 6

Abstract

Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data and need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision- and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Community practical guidelines will allow for global access and harmonization of quality information at the level of individual Earth science datasets and support open science.
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全球获取和协调单个地球科学数据集的质量信息的行动呼吁
关于数据和元数据质量的知识对于支持关于(重新)使用单个数据集的知情决策很重要,也是支持开放科学的生态系统的重要组成部分。质量评估反映了数据的可靠性和可用性,需要持续策划、完全可追溯和充分记录,因为这些对于依赖数据的健全决策和决策工作至关重要。质量评估还需要在系统和工具之间得到一致的表示和容易的集成,以允许在数据集级别更好地共享单个质量属性或维度的质量信息。尽管评估数据和相关信息质量的必要性已得到充分认识,但评估框架的方法以及向最终用户介绍由此产生的质量信息的方法可能尚未在学科内部和学科之间得到全面解决。全球跨学科领域专家聚集在一起,系统地探索在数据集的整个生命周期中持续管理和表示高质量信息的需求、挑战和影响。本文介绍了调查结果,呼吁社区采取行动制定切实可行的指导方针,并概述了制定此类指导方针的社区建议。社区实用指南将允许全球获取和协调单个地球科学数据集层面的高质量信息,并支持开放科学。
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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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