Scientific institutions have increasingly embraced formalized research data management strategies, which involve complex social practices of codifying the tacit dimensions of data practices. Several guidelines to facilitate these practices have been introduced in recent years, for example, the FAIR guiding principles. The aim of these practices is to foster transparency and reproducibility through 'data sharing,' the public release of data for unbounded reuse. However, a closer look suggests that many scientists' practices of data release might be better described as what I call data handovers. These practices are not rooted in the lofty ideals of good scientific practice and global data reuse but in the more mundane necessities of research continuity, which have become more urgent in light of increasing academic mobility. The Austrian scientists interviewed for this study reinterpreted defining features of research data management - such as ensuring findability - as techniques for managing the effects of researcher mobility. This suggests that the adoption of Open Science practices might be dissociated from its stated epistemic goals, and explains why many Open Science initiatives at present are administratively strong but normatively weak.
Keywords: Open Science; data practices; data sharing; research data management.