Planning

Data management planning consists of defining the strategy that you plan to use for managing data and documentation generated within the project. It is about thinking upfront what’s the best way to avoid problems or unexpected costs related to data management, and set the conditions for your research data to achieve the highest possible impact in science, even after the end of the project.

Solutions regarding the handling of the data generated within a project is usually formalised in a Data Management Plan (DMP). A DMP is a document describing several aspects of the data management process which occur before, during and after the end of a project. 

Why is data management planning important?

It is good research practice to take care of your research data and have a DMP. It will make your work more efficient, facilitate team work and use of services and tools. Moreover, a detailed DMP would help in making your research data more FAIR. Advantages of making a DMP:

• it is often a requirement of research organisations and funders;
• it helps to plan and budget necessary resources and equipment;
• it defines roles and responsibilities in data management among the project team;
• it helps to identify risks in data handling and apply solutions at early stage;
• it facilitates data sharing, reuse and preservation.

Before your project

You should address the issue of data already before your project begins. While planning your research project, you should consider what kind of data you will need, how you plan to acquire the data (will you create your own, or can you use existing data?), where you will store them, who will be responsible for them and so on.

Several aspects should be taken into account when making a data management plan.

• Research organisation and funders often require a DMP as part of the application for grants or later when the project is funded. Therefore, consider guidelines, policies and tools for data management planning required by your funder.
• Data management should be planned in the early stages of a research project. Preferably, the DMP should be filled in before starting data collection. However, the DMP is a living document and should be updated as the research project progresses to match e.g. an update of the infrastructures, research softwares or a novel collaboration.
• Consider standards or best practices required by facilities and infrastructures that you plan to use.
• Due to the variety of aspects that need to be addressed in a DMP, it is better to find recommendations and obtain help from your institution support services, such as IT department, library, data managers or data stewards, legal or tech transfer team and data protection officer.
• Explore best practices, guidelines, tools and resources for research data management described in next chapters.   We anticipate that in the 9. chapter dedicated to detailing the creation of a DMP, you will have a clearer idea of the answers to each of the specific questions and sections in the DMP. 

Personnel support

If you're going to deal with managing your own data, it's clear who is responsible for it. In the case of data management within a research team or project, you need to set up staff responsibilities.

All members of the project team work with scientific data, but someone on the team needs to be at the centre of these activities and responsible for selecting and applying the correct methodology. It seems optimal to find a person in each project team (or scientific group) who will partly handle these tasks (Data Steward position). A coordinator can then be appointed within the umbrella organisation of several projects to coordinate technical support and joint communication with external services.

Data Steward is responsible for

• setting rules for working with research data within the research team
• creating and updating the DMP

Data Steward is not responsible for

• data analysis (It is his responsibility only to ensure that the data is reproducible, findable and  accessible.)

Data stawards need to be provided with sources of information, training and examples of good practice.