A Data Management Plan (DMP) is a structured guideline that describes the comprehensive lifecycle of data, from conception to storage, analysis, and preservation. DMPs help researchers to think through all relevant questions concerning the data their research will generate, and ensure attention remains focused on the long-term accessibility and subsequent reusability of their data assets. DMPs provide a basic description of what kind of data will be produced and collected, and details about what will happen to the data both during a project and after it has been completed. This includes statements about the provenance of data, contextual information surrounding the data collection process, how data are conceptually related to data sets produced by similar studies, the infrastructures used to store and manage data, as well as information regarding the publication, citation, long-term access and, if necessary, destruction of data when the research lifecycle is complete. Humanities and social sciences data are unique in that they often consist of private information contributed by individual study participants, thus various questions regarding data protection, copyright attribution, exploitation rights, and licensing are also addressed in this template. The template is also compliant with the FAIR principles to improve the findability, accessibility, interoperability, and reuse of the data. This implies that research data and contextual tools like software should be stored and made available for use in a suitable repository or archiving system and data should be provided with persistent identifiers. Data must be identifiable, accessible, traceable, interoperable, and whenever possible, available for subsequent use. In compliance with intellectual property rights, and if no third-party rights, legal requirements or property laws prohibit it, research data should be assigned a licence for open use.

Acknowledgement: Developed in the project e-infrastructures Austria Plus, created by AUSSDA – The Austrian Social Science Data Archive and WU Vienna University of Economics and Business