Articles | Volume 10, issue 9
https://doi.org/10.5194/gmd-10-3189-2017
https://doi.org/10.5194/gmd-10-3189-2017
Model description paper
 | 
31 Aug 2017
Model description paper |  | 31 Aug 2017

eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5

Stefan Metzger, David Durden, Cove Sturtevant, Hongyan Luo, Natchaya Pingintha-Durden, Torsten Sachs, Andrei Serafimovich, Jörg Hartmann, Jiahong Li, Ke Xu, and Ankur R. Desai

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Stefan Metzger on behalf of the Authors (03 Jul 2017)  Author's response   Manuscript 
ED: Publish as is (06 Jul 2017) by Chiel van Heerwaarden
AR by Stefan Metzger on behalf of the Authors (16 Jul 2017)
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Short summary
We apply the development and systems operations software development model to create the eddy4R–Docker open-source, flexible, and modular eddy-covariance data processing environment. Test applications to aircraft and tower data, as well as a software cross validation demonstrate its efficiency and consistency. Key improvements in accessibility, extensibility, and reproducibility build the foundation for deploying complex scientific algorithms in an effective and scalable manner.