Research data management is the term applied to all activities involving digital research data (apart from its actual use), in particular those relating to storage and long-term availability. The individual steps from the collection of research data to its use, analysis, processing, archiving, publication, reuse and, in some cases, planned deletion are all part of what is known as the research data life cycle. As this term implies, research data and research data management play an important role during all stages of a research project and after its completion.
Some research organisations already require research data to be stored for a particular length of time, published and made available for others to use. For this reason, it is important to create a data management plan when planning a research project. A data management plan provides clear written documentation of how data is handled to ensure that requirements are met and the quality of the research data is ensured. When creating a plan it is important to adhere to the established norms and regulations on safeguarding good scientific practice (http://www.dfg.de/download/pdf/dfg_im_profil/reden_stellungnahmen/download/empfehlung_wiss_praxis_1310.pdf).
There are several helpful tools available for drafting data management plans designed with the data life cycle in mind:
- Check list created by Georg-August Universität Göttingen and partners as part of the WissGrid project (http://www.wissgrid.de/publikationen/deliverables/wp3/WissGrid-oeffentlicher-Entwurf-Checkliste-Forschungsdaten-Management.pdf)
- DMPonline by the British Digital Curation Centre (https://dmponline.dcc.ac.uk/)
DMPonline allows you to create a step-by-step data management plan that meets your needs and the requirements of various research institutions. It is free to use. Once you have created a plan you can export it in different formats for various purposes, such as to integrate it into project applications.