MaRDIFlow: A Workflow Framework for Documentation and Integration of FAIR Computational Experiments




FAIR, Reproducibility, MaRDIFlow, Computational Workflows


Numerical algorithms and computational tools are essential for managing and analyzing complex data processing tasks. With ever increasing availability of meta-data and parameter-driven simulations, the demand and the need for reliable and automated workflow frameworks to reproduce computational experiments has grown.  In this work, we aim to develop a novel computational workflow framework, namely MaRDIFlow, that describes the abstraction of multi-layered workflow components. Herein, we plan to enable and implement scientific computing data FAIRness into actionable guidelines for FAIR computational experiments.


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Received 2023-04-26
Accepted 2023-06-29
Published 2023-09-07