Effective research data management? – DMP to the rescue!

Data management planning (DMP) is too often considered a burden and a bureaucratic procedure. However, a data management plan is a useful tool that helps researchers prepare more effectively for the research process and identify the potential risks. DMP also has significant pedagogical potential and, in collaboration with DMP organisations, can develop the infrastructure and services needed to conduct research.

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Text: Mikko Ojanen

Increasingly, it has been acknowledged that research data management (RDM) is an integral part of the research project. However, effective RDM does require systematic planning. The importance of planning in advance – in other words, writing a data management plan (DMP) in good time – cannot be emphasised enough.

The hiccups in the research process – described in the previous sections of this article series – are only the tip of the iceberg when it comes to the problems of RDM. Typically, and all too often, the challenges faced in the processes can be traced back to poor planning. It is the rule rather than the exception that RDM related tasks remain hidden, and researchers must cover the costs from their project’s resources –often with their own time and money. DMP is central to overcoming these problems.

It is the rule rather than the exception that RDM related tasks remain hidden, and researchers must cover the costs from their project’s resources.

DMP as a versatile tool for the researcher

Unfortunately, too often DMP is considered a burden and a bureaucratic procedure. However, a data management plan is a tool that can provide many benefits and DMP is a central skill of a modern researcher. With its significant pedagogical potential, DMP can even serve as a method for teaching general research skills at various levels of study.

Planning your RDM also serves as a handy checklist. For example, it will help ensure that you know:

  • How and when to make agreements;
  • How to meet the legal aspects of GDPR (General Data Protection Regulation) and assess the sensitivity of your data;
  • How to use systematic documentation to keep your data in order and ensure that the same documentation practices are followed by everyone in your project;
  • How to keep your data secure and how to share it safely with your colleagues;
    How to decide what data can be destroyed and what is valuable and should be preserved;
  • How to prepare your data for archiving, opening, and publishing, and where to do this; and finally,
  • How to show your funder’s reviewers that you can manage these issues.

DMP for better risk management and support services

Outlining a data management plan also covers the important details that are needed to address the risk management of a research project. A data management plan will help you recognise, anticipate, and handle the risks related to your data management workflow. DMP can also assist with clearly identifying the ethical and legal aspects of a project that are sometimes difficult to understand. It is also the first step that directs a researcher towards the Data Protection Impact Assessment (DPIA) and, if necessary, the Ethical review.

DMP can also assist with clearly identifying the ethical and legal aspects of a project that are sometimes difficult to understand.

By creating a data management plan, researchers are better prepared to avoid the loopholes in their data management processes. They can also present the documents to help the organisation arrange the support required to conduct the project. Research organisations generally require more information about the projects that are starting under their wings. In these cases, the researcher’s data management plan is an invaluable resource.

DMP requires resources and this is one aspect that can prevent DMP from being used as a risk management tool or for organisational and pedagogical purposes. However, the investment will pay off. RDM and its planning require skills that can be learnt and practised. Therefore, over time, DMP becomes easier and more efficient.

Planning in practice – DMP guidelines supporting researchers

The annually updated national DMP guidelines, which are based on the template produced by Science Europe, will help you create a data management plan for your project, step by step. The researcher and the data support services of their home organisation can follow the guide to check that all the necessary components have been included when starting a new project.

By outlining a data management plan in good time, you will get to know your data before it is too late. It is worth emphasising that the data management plan should be based on your own research project. In other words, it should reflect your own work: do not copy and paste sentences from somebody else’s document, as this will not advance your own project management.

Timely planning is the first step towards conducting ethically sound research and effective research data management!

   Research Data Management – know your data!

Research data management (RDM) is a crucial part of any research. First and foremost, the aim of RDM is to make the research process as efficient as possible. Second, RDM will help you meet the expectations and requirements of your organisation and research funders. RDM skills are fundamental skills for researchers and they apply to everyone who handles data for research projects. By learning RDM, you get to KNOW YOUR DATA!

In this series, the University of Helsinki Data Support team introduces the key components of RDM and data management planning (DMP): what they are, why they are important, and where to look for more help with RDMP (research data management planning) issues. The series comprises six parts:

1) What is research data management (RDM)? (3.9.2020)
2) The components of research data management (17.9.2020)
3) Why research data management? (30.9.2020)
4) Why plan research data management in advance? (22.10.2020)
5) Effective research data management? – DMP to the rescue! (19.11.2020)
6) Where is the help and support for research data management? (8.12.2020)