Data sharing refers to the act of sharing or distributing data. According to research requirements, data should be made as open as possible and as confidential as necessary (European Commission, 2021). Particularly with regard to the reuseData reuse, often referred to as secondary use, involves re-examining previously collected and published research datasets with the aim of gaining new insights, potentially from a different or fresh perspective. Preparing research data for reuse requires significantly more effort in terms of anonymization, preparation, and documentation than simple archiving for storage purposes. Read More and handling of sensitiveWithin the category of personal data, there is a subset known as special categories of personal data. Their definition originates from Article 9(1) of the EU GDPR (2016), which states that these include information about the data subject’s: Read More, personal dataPersonal data includes: 'any information relating to an identified or identifiable natural person (data subject); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier, or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural, or social identity of that natural person(…)” (EU GDPR Article 4 No. 1, 2016; BDSG §46 para. 1, 2018; BlnDSG §31, 2020). Read More, it is crucial to carefully assess whether and in what form archivingArchiving refers to the storage and accessibility of research data and materials. The aim of archiving is to enable long-term access to research data. On one hand, archived research data can be reused by third parties as secondary data for their own research questions. On the other hand, archiving ensures that research processes remain verifiable and transparent. There is also long-term archiving (LTA), which aims to ensure the usability of data over an indefinite period of time. LTA focuses on preserving the authenticity, integrity, accessibility, and comprehensibility of data. Read More and sharing data with other researchers and the public is possible and appropriate. The imperative of data sharing enjoys broad consensus within the Open Science movementSince the early 2000s, the Open Science movement has advocated for an open and transparent approach to science in which all stages of the scientific knowledge process are made openly accessible online. This means that not only the final results of research, such as monographs or articles, are shared publicly, but also materials that accompanied the research process, such as lab notebooks, research data, software used, and research reports. This approach aims to promote public participation in science and knowledge, engaging interested audiences. It also seeks to encourage creativity, innovation, and new collaborations, while enabling the verification of findings in terms of quality, accuracy, and authenticity – a process intended to democratize research. Components of Open Science include Open Access and Open Data, which provide the infrastructure for sharing interim research results. Read More but should be critically considered and weighed from a social and cultural anthropological perspective.