CC BY 4.0Boukhers, ZeydZeydBoukhersCastro, Leyla JaelLeyla JaelCastro2024-04-222024-04-222024-04-222023-09-07https://publica.fraunhofer.de/handle/publica/466719https://doi.org/10.24406/publica-296610.52825/cordi.v1i.40610.24406/publica-2966The FAIR principles were introduced to enhance data reuse by providing guidelinesfor effective data management practices. In the broader context of research, assets encompass not only data but also other artifacts such as code, software, and publications.FAIRifying these artifacts is as essential as FAIRifying data, especially in Data Scienceand Artificial Intelligence, where the complexity of current AI approaches makes repro-ducibility extremely challenging. Therefore, facilitating the easy reuse of these artifactsrepresents a significant stride towards mitigating this problem. The concept of FAIRDigital Objects (FDOs) presents a solution to FAIRify these artifacts, treating them asFDOs. NFDI4DataScience is embracing FDOs and proposing an architecture to efficiently manage them.enReproducibilityFAIR Digital ObjectFAIR principlesconference paper