Data management planning (DMP) is too often considered as a burden and bureaucratic procedure. However, the DMP is a useful tool that helps researchers to better prepare for the research process and to identify potential risks. DMP also has significant pedagogical potential, and with DMP’s organizations can develop the infrastructure and services needed to conduct research.
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Text: Mikko Ojanen
It has been increasingly acknowledged that research data management is an integral part of research project. Effective research data management (RDM), on the other hand, entails its systematic planning. The importance of planning ahead – in other words writing a DMP (data management plan) in good time – cannot be emphasized enough.
The hiccup in research process described in the previous part of the article series is only a tip of the iceberg of problems related to research data management. Typically, and all too often, problems faced in data management processes can be traced to their poor planning. It is a rule rather than an exception that RDM related tasks remain hidden and researchers must cover them from their project resources – and often on their own time and with their own money. Data management planning is absolutely central to overcoming these problems.
DMP as a versatile tool for a researcher
Unfortunately, data management planning is too often considered as a burden and bureaucratic procedure. However, a DMP is a tool a researcher can benefit from and data management planning is a central skill of a modern researcher. With its significant pedagogical potential, it could even serve as a method for teaching and training of general researcher skill on various study levels.
Planning your research data management also serves as a handy check list. It will help you to make sure that you know, for example:
- how and when to make agreements,
- how to meet the legal aspects of GDPR and assess the sensitiveness of your data,
- how to use systematic documentation to keep your data in order and how these documentation practices are commonly followed by everyone in your project,
- how to keep your data secured and how to share it safely with your colleagues,
- how to decide which part of the data can be destroyed and which part is valuable to be preserved,
- how to prepare your data for archiving, opening and publishing and where to do this,
- and finally, how to convince your funder’s reviewers that you can handle these issues.
DMP for better risk management and support services
Outlining a DMP also covers important details needed in order to handle the risk management of a research project. By outlining a DMP you can recognise, anticipate and handle the risks related to your data management workflow. DMP can be of great help in concretizing ethical and legal aspects that are sometimes difficult to understand. It is also the first step which directs the researchers towards Data Protection Impact Assessment (DPIA) and from there to the Ethical review, if necessary.
DMP can be of great help in concretizing ethical and legal aspects that are sometimes difficult to understand.
By outlining a DMP, researchers not only prepare themselves to avoid loopholes in their data management processes, they can also deploy the document to prepare their organization to help them conduct their projects. The research organizations desperately need more information about projects which are about to start under their wings. Here, researcher’s DMP is an invaluable asset.
One aspect hindering the use of DMP as a risk management tool or in organizational and pedagogical purposes is that it requires resources. However, the investment will pay off. Research data management and its planning are skills, which can be trained and taught. Therefore, in time they also get easier and smoother.
Planning in practice – DMP guidelines supporting a researcher
Annually updated national DMP guidelines which are based on the template produced by the Science Europe in 2019 will help you to outline a DMP for your project step by step. Following the guide will help both the researchers and their local data support services in their home organizations to check that all the necessary components have been considered when starting a new project.
By outlining a DMP in good time you get to know your data before it is too late. It may be good to stress that the DMP should be based on your own research project. In other words, it should reflect your own project: do not copy-paste sentences from somebody else – copy-pasting does not advance your own project management.
Timely planning is the first step towards ethically sound research conduct and effective research data management!
Research Data Management – know your data!