摘要: Data harmonization and documentation of the data processing are essential prerequisites for enabling
Canonical Analysis Workflows. The recently revised Terabyte-scale air quality database system, which the
Tropospheric Ozone Assessment Report (TOAR) created, contains one of the world’s largest collections of
near-surface air quality measurements and considers FAIR data principles as an integral part. A special
feature of our data service is the on-demand processing and product generation of several air quality metrics
directly from the underlying database. In this paper, we show that the necessary data harmonization for
establishing such online analysis services goes much deeper than the obvious issues of common data formats,
variable names, and measurement units, and we explore how the generation of FAIR Digital Objects (FDO)
in combination with automatically generated documentation may support Canonical Analysis Workflows for
air quality and related data.
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分类:
计算机科学
>>
计算机科学的集成理论
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引用:
ChinaXiv:202211.00441
(或此版本
ChinaXiv:202211.00441V1)
DOI:10.1162/dint_a_00130
CSTR:32003.36.ChinaXiv.202211.00441.V1
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科创链TXID:
a3c401c1-d7a9-4d28-8637-5f3a6fa4fc17
- 推荐引用方式:
Sabine, Schröder,Eleonora, Epp,Amirpasha, Mozaffari,Mathilde, Romberg,Niklas, Selke,Martin, G. Schultz.Enabling Canonical Analysis Workflows Documented Data Harmonization on Global Air Quality Data.中国科学院科技论文预发布平台.[DOI:10.1162/dint_a_00130]
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