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FAIRness Along the Machine Learning Lifecycle Using Dataverse in Combination with MLflow Cover

FAIRness Along the Machine Learning Lifecycle Using Dataverse in Combination with MLflow

Data Science Journal
Volume 23 (2024): Issue 1
By: Lincoln Sherpa,  Valentin Khaydarov and  Ralph Müller-Pfefferkorn  
Open Access
|Dec 2024

Authors

Lincoln Sherpa

lincoln.sherpa@tu-dresden.de

Technische Universität Dresden, Center for Interdisciplinary Digital Sciences, Department Information Services and High Performance Computing, Dresden

Valentin Khaydarov

valentin.khaydarov@gmail.com

Technische Universität Dresden, P20, Dresden

Ralph Müller-Pfefferkorn

ralph.mueller-pfefferkorn@tu-dresden.de

Technische Universität Dresden, Center for Interdisciplinary Digital Sciences, Department Information Services and High Performance Computing, Dresden
DOI: https://doi.org/10.5334/dsj-2024-055 | Journal eISSN: 1683-1470
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Language: English
Submitted on: Mar 24, 2024
Accepted on: Nov 16, 2024
Published on: Dec 6, 2024
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Machine Learning (ML),
Research data management,
FAIR data principles,
FAIR Data,
Database management system,
Competing Interests

© 2024 Lincoln Sherpa, Valentin Khaydarov, Ralph Müller-Pfefferkorn, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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