The FAIR Principles were first developed in 2016 by the FORCE11 community (The Future of Research Communication and e-Scholarship). FORCE11 is a community of researchers, librarians, archivists, publishers, and research fundersFunding institutions are organizations that provide financial support for scientific research, such as foundations, associations, or other entities. Internationally, most of these institutions have established guidelines for research data management (RDM) in research projects, meaning that potential funding is tied to specific requirements and expectations for handling research data. Some of the most well-known funding institutions in German-speaking countries include the Federal Ministry of Education and Research (BMBF), the education and science ministries of the federal states, the German Research Foundation (DFG), the Volkswagen Foundation, the Austrian Science Fund (FWF), and the Swiss National Science Foundation (SNF). Read More aiming to bring about change in modern scientific communication through the effective use of information technology, thereby supporting enhanced knowledge creation and dissemination. The primary goal is the transparent and open presentation of scientific processes. Accordingly, data should be made findable, accessible, interoperable, and reusable (FAIR) online. The objective is to preserve data long-term and make it available for 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 by third parties in line with Open Science'Open Science encompasses strategies and practices aimed at making all components of the scientific process openly accessible and reusable on the internet. This approach is intended to open up new possibilities for science, society, and industry in handling scientific knowledge” (AG Open Science, 2014, translation by Saskia Köbschall). Read More and Data SharingData 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 reuse and handling of sensitive, personal data, it is crucial to carefully assess whether and in what form archiving 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 movement but should be critically considered and weighed from a social and cultural anthropological perspective. Read More principles. Precise definitions by FORCE11 can be found on their website¹ see: https://force11.org/info/the-fair-data-principles/.

The FAIR Principles do not adequately address ethical aspects of data sharing in social science contexts, which is why they have been supplemented by the CARE PrinciplesThe CARE principles were established by the Global Indigenous Data Alliance (GIDA) in 2019. They complement the FAIR principles and are used as a tool to focus more strongly on research contexts and their historical embeddedness, as well as on power asymmetries in the field. The acronym stands for Collective Benefit (common good), Authority to Control (control of research participants over their own representation), Responsibility (responsibility on the part of researchers) and Ethics (consideration of ethical aspects). The CARE principles are intended to emphasize and take into account the fair, respectful and ethical treatment of research participants and the data generated from research with regard to data sharing. The CARE principles are therefore relevant in all phases of the research data life cycle and research data management. Read More.