In order to comply with the principles of good scientific practice, numerous aspects of research data management should be sufficiently considered and addressed at the very beginning of research work. These aspects include, among others, the documentation of the data, their archiving, the long-term availability after the completed research work as well as the clarification of the responsibilities and duties of the participating scientists.
The following points present the essence of a data management plan:
General information on the planned project such as goals, funding, and duration
Description of existing data that can be reused for the project and how their integration could look
Details on the types of data and formats and the estimated amount of data that will be used and created, along with further information on the process of creating the data and quality assurance (such as documentation and validation measures)
Details on consistent data organization within the project (e.g. for data storage, data names, synchronization, versioning, and other collaboration workflows)
Which data will be shared? How will data be shared? Information on the planned interoperability with external discipline-specific data services
How are the responsibilities for data management defined and distributed within the project?
Reports on the costs and the personnel expenditure for maintaining the data management plan and running costs for data curation, production of metadata, archiving, etc.