As with other aspects of research data management, there is a discrepancy between general science policy requirements and the actual implementation of data management plans (DMPs) within ethnographic disciplines. In these fields, DMPs have not yet become a routine part of research practice. In a survey conducted by the Specialized Information Service for Social and Cultural Anthropology (FID SKA)The Specialized Information Service for Social and Cultural Anthropology (FID SKA) provides members of the German Society for Empirical Cultural Studies and the German Society for Social and Cultural Anthropology, as well as other interested researchers to a limited extent, with selected online resources for research. Read More on the handling of research data in social and cultural anthropology, only 10 percent of respondents indicated that they were using a data management plan in their current project. Around 30 percent did not know whether such a plan existed within their research project or what a data management plan even was (Imeri, 2017).

Nevertheless, a DMP can support research project work. It provides researchers with clarity and an opportunity for reflection during the generation of research data.

Benefits of Data Management Plans: A DMP…

• ensures adherence to good scientific practiceGood scientific practice (GSP) represents a standardized code of conduct established in the guidelines of the German Research Foundation (DFG). These guidelines emphasize the ethical obligation of every researcher to act responsibly, honestly, and respectfully, also in order to strengthen public trust in research and science. They serve as a framework for guiding scientific work processes. Read More (e.g., transparency and traceability).
• facilitates project planning, particularly in budgeting for research data management.
• helps make data and materials interpretable and reusable at a later stage, potentially for other researchers as well.
• ensures project continuity, even in cases of personnel changes.
• requires detailed reflection on one’s own handling of data and materials.
• serves to meet the expectations and requirements of funding institutionsFunding 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.

Even at the level of a bachelor’s or master’s thesis, it is useful to go through the key questions of a DMP, reflect on one’s handling of data, and document where and how data is stored, among other things. This ensures that, at a later stage – such as when writing a dissertation on a similar topic – one can refer back to material from the master’s thesis. In this sense, a DMP serves the internal usability of research data within the project in which they were created. The primary goal is to ensure that research data remain accessible during and after the project’s completion, do not get lost, and are not damaged.

Many funding agencies (DFG, FWF, SNF, Horizon Europe, Volkswagen Foundation) now require applicants to include details about research data management in funding proposals. In this context, the development and implementation of data management plans are increasingly being mandated.

A few examples are listed below, with further information available under the guidelines of funding institutions regarding research data management (Forschungsdaten.info, 2023i).