Journal Article

FZJ-2022-02296

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Enabling Canonical Analysis Workflows:Documented Data Harmonization on Global Air Quality Data

Schröder, S. (Corresponding author)FZJ* ; Epp, E.FZJ* ; Mozaffari, A.FZJ* ; Romberg, M.FZJ* ; Selke, N.FZJ* ; Schultz, M. G.FZJ*

2022
MIT Press Cambridge, MA

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Please use a persistent id in citations: http://hdl.handle.net/2128/31260  doi:10.1162/dint_a_00130

Abstract: 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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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)
2. IntelliAQ - Artificial Intelligence for Air Quality (787576) (787576)
3. Earth System Data Exploration (ESDE) (ESDE)

Appears in the scientific report 2022

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Database coverage:
; ; ; ; ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Emerging Sources Citation Index ; SCOPUS ; Web of Science Core Collection

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