SwissEnvEO: A FAIR National Environmental Data Repository for Earth Observation Open Science

Q2 Computer Science

Data Science Journal Pub Date : 2021-05-31 DOI:10.5334/DSJ-2021-022

G. Giuliani, Hugues Cazeaux, Pierre-Yves Burgi, Charlotte Poussin, Jean-Philippe Richard, B. Chatenoux

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引用次数: 9

Abstract

Environmental scientific research is highly becoming data-driven and dependent on high performance computing infrastructures to process ever increasing large volume and diverse data sets. Consequently, there is a growing recognition of the need to share data, methods, algorithms, and infrastructure to make scientific research more effective, efficient, open, transparent, reproducible, accessible, and usable by different users. However, Earth Observations (EO) Open Science is still undervalued, and different challenges remains to achieve the vision of transforming EO data into actionable knowledge by lowering the entry barrier to massive-use Big Earth Data analysis and derived information products. Currently, FAIR-compliant digital repositories cannot fully satisfy the needs of EO users, while Spatial Data Infrastructures (SDI) are not fully FAIR-compliant and have difficulties in handling Big Earth Data. In response to these issues and the need to strengthen Open and Reproducible EO science, this paper presents SwissEnvEO, a Spatial Data Infrastructure complemented with digital repository capabilities to facilitate the publication of Ready to Use information products, at national scale, derived from satellite EO data available in an EO Data Cube in full compliance with FAIR principles.

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SwissEnvEO:一个公平的对地观测开放科学国家环境数据库

环境科学研究高度依赖于数据驱动和高性能计算基础设施来处理不断增加的大容量和多样化的数据集。因此，人们越来越认识到需要共享数据、方法、算法和基础设施，以使科学研究更加有效、高效、开放、透明、可复制、可访问和可供不同用户使用。然而，地球观测(EO)开放科学仍然被低估，通过降低大规模使用大地球数据分析和衍生信息产品的进入门槛，实现将EO数据转化为可操作知识的愿景仍然存在不同的挑战。目前，符合fair标准的数字存储库不能完全满足EO用户的需求，而空间数据基础设施(SDI)也不完全符合fair标准，在处理大地球数据方面存在困难。为了应对这些问题以及加强开放和可复制的EO科学的需要，本文提出了SwissEnvEO，这是一个空间数据基础设施，与数字存储库功能相补充，以促进在国家范围内发布随时可用的信息产品，这些信息产品来源于EO数据立方体中可获得的卫星EO数据，完全符合FAIR原则。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data Science Journal Computer Science-Computer Science (miscellaneous)

CiteScore

5.40

自引率

0.00%

发文量

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.