Open Science Best Practices in Data Science and Artificial Intelligence

• DOI: 10.52825/cordi.v1i.299
• Publication Date: 2023-09-08T08:39:58Z
• Authors: Ekaterina Borisova; Raia Abu Ahmad; Georg Rehm
• Keywords: Best practice; Open Science; Scientific Workflows; Data Sharing; Data Reuse; Research Data; Open research

In the past years, scientific research in Data Science and Artificial Intelligence has witnessed vast progress. The number of published papers and digital objects (data, code, models) is growing exponentially. However, not all of these research artifacts are findable, accessible, interoperable and reusable (FAIR), contributing to a rather low level of reproducibility of the experimental findings reported in scholarly publications (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 openly available on the NFDI4DS webpage as an interactive web application.