MaRDIFlow: A Workflow Framework for Documentation and Integration of FAIR Computational Experiments
DOI:
https://doi.org/10.52825/cordi.v1i.323Keywords:
FAIR, Reproducibility, MaRDIFlow, Computational WorkflowsAbstract
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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References
D. Talia, “Workflow systems for science: Concepts and tools,” International Scholarly Research Notices, vol. 2013, 2013.
C. Goble, S. Cohen-Boulakia, S. Soiland-Reyes, et al., “FAIR Computational Workflows,” Data Intelligence, vol. 2, no. 1-2, pp. 108–121, 2020.
M.Wolf, J. Logan, K. Mehta, et al., “Reusability first: Toward FAIR workflows,” in 2021 IEEE International Conference on Cluster Computing (CLUSTER), IEEE, 2021, pp. 444–455.
MaRDI. “Mathematic research data initiative.” (2021), [Online]. Available: https://www.mardi4nfdi.de.
J. W. Cahn and J. E. Hilliard, “Free energy of a nonuniform system. I: Interfacial free energy,” The Journal of chemical physics, vol. 28, no. 2, pp. 258–267, 1958.
M. D. Wilkinson, M. Dumontier, I. J. Aalbersberg, et al., “The FAIR guiding principles for scientific data management and stewardship,” Scientific Data, vol. 3, no. 1, pp. 1–9, 2016.
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Copyright (c) 2023 Pavan L. Veluvali, Jan Heiland, Peter Benner
This work is licensed under a Creative Commons Attribution 4.0 International License.
Accepted 2023-06-29
Published 2023-09-07