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Climate Research Reproducibility With The Climate 4R R-Based Framework

Conference: 8th International Workshop on Climate Informatics
Year: 2018
Contribution type: Poster
Poster: CI2018_poster_paper21.pdf

Climate driven sectoral applications in a variety of domains (such as hydrology, agriculture, energy, or health) typically require elaborated data processing workflows involving multiple data access, collocation, harmonization and postprocessing (e.g. bias correction) steps. This is a time-consuming and error-prone task which, in many cases, is performed with different tools and lack of appropriate metadata for reproducibility. The R-based climate4R framework provides a solution to this problem, building on open source software and standards. climate4R allows accessing, postprocessing and visualizing local and remote (OPeNDAP) data sources providing full provenance information via METACLIP (semantic MEtadata for CLIimate Products). As a result, climate4R provides a unique comprehensive framework for end-to-end fully reproducible sectoral studies favoring open science.