Creating Data Management Plans in Data Science Projects for Fake News Detection Supported by FAIR principles

• Jorge Zavaleta Federal University of Rio de Janeiro http://orcid.org/0000-0002-4747-8613
• Annatércia Pinheiro Federal University of Rio de Janeiro
• Renato Cerceau National Institute of Cardiology / State University of Rio de Janeiro https://orcid.org/0000-0003-3953-4715
• Cabral Lima Federal University of Rio de Janeiro
• Maria Luiza Machado Campos Federal University of Rio de Janeiro
• Sérgio Manuel Serra da Cruz Federal University of Rio de Janeiro / Federal Rural University of Rio de Janeiro

DOI: https://doi.org/10.5753/ersirj.2021.16981

Abstract

Data Science researchers are experiencing an increasingly multifaceted reality concerning data governance. The paradigm shifts from disconnected data silos to data management plans (DMP) and standardized online repositories are adhering to the FAIR principles. This manuscript discusses, compares current DMP platforms, and describes the creation of a DMP in a Machine Learning project focused on Fake News detection. As a result, we describe a use case with the construction of the PGD on the DSWizard platform and offer an executable article that may be executed by the readers.

Keywords: Data Management, Plansfake newsfair principles, machine learning methods

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