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In the past years, scientific research in Data Science and Artificial Intelligence has witnessed vast progress. The number of published papers and digital objects (e. g., data, code, models) is growing exponentially. However, not all research artefacts fulfill the criteria of being findable, accessible, interoperable and reusable (FAIR), contributing to a rather low level of reproducibility of experimental findings reported in scholarly publications and to the reproducibility crisis. In this paper, we focus on Data Science and Artificial Intelligence Open Science best practices, i. e., a set of recommendations that eventually contribute to the management and development of digital artefacts that are as FAIR as possible. While several guidelines exist, we add best practices for the FAIR collection, processing, storing and sharing of scholarly findings via Research Knowledge Graphs. The final list of recommendations will be available on the NFDI4DS website as an interactive web application. [ABSTRACT FROM AUTHOR]