Building better RDM guidance

The aim of the Mildred M5 group is the implementation of the data management planning tool DMPTuuli which helps you write data management plans. In data management plan you give a brief description of how you will collect, manage and store your data, and how the data can be used now and in the future. Many research funders like Academy of Finland require a data management plans in their funding applications. DMPTuuli links the funders requirements, the guidance and the support services provided by the UH to the same user interface.

In the M5 project the focus is on writing targeted research data management (RDM) guidance to researchers and students in the University of Helsinki. The current guidance in DMPTuuli is generic level instructions for all disciplines. Obviously, on size doesn’t fit for all and so we are planning to create discipline or data type specific guidance to better meet your demands.

First we are planning to make simplified guidance aimed for those who are not so familiar with the data management plans. So far we have defined the principles of the good guidance and benchmarked the available RDM guidance made by other organizations. At the moment we are writing a glossary of terms related to RDM.

In the next phase we will discover the needs for more specific guidance. For example, the sensitive data that needs to be anonymized might benefit of having RDM guidance that would go deeper than the generic level instructions.

But, we cannot write guidance without your contribution. Now that we are working on the beginner level guidance aimed for students for example, we would be happy to have volunteers to help us by giving comments and suggestions on what kind of guidance would be useful for students. And furthermore, if your research group has a need for more specific RDM instructions, please let us know! Feel free to use our feedback form or leave a reply to this post.

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