Section outline

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    • 3.1 Introduction & learning goals

      Before you start your research project, you should take a fundamental look at what kind of data your project will produce and how you want to deal with it. It is important to think beyond the completion of your research (see Chapter 8). Record the results of your considerations in a data management plan (DMP for short). A DMP helps you to get the best out of your data in the long term. Third-party funders are also aware of this and often require a DMP.

      After completing this chapter, you will be able to...

      • ...explain what a DMP is
      • ...name what information a DMP contains
      • ...recognise the benefits you get from a DMP
      • ...find tools to help you create a DMP

      A good first overview of data management plans is provided in this video from RWTH Aachen University.

    • 3.2 Benefits of a data management plan

      Overall, the DMP saves you time and prevents data loss. If you consider in advance how the data should be processed, stored, and filed, you probably won’t have to reorganise your data. If, for example, it is already clear during data collection how the data is to be archived later, it can be formatted and stored right away in such a way that the transfer to the later archive is as simple as possible (see Chapter 7 and Chapter 8).

      Searching is also easier with well-maintained and annotated (= enriched with metadata) data (see Chapter 4). This applies both to data providers and to subsequent users. Making research data available beyond a research project allows future researchers and research groups to retrieve the data when it has become relevant for research again.

      In addition, many third-party funders already require a DMP as part of the research proposal. Examples of guidelines from research funders:

    • 3.3 What is a data management plan?

      A data management plan (DMP) is a document that describes for all phases of the data life cycle which activities are to be carried out and how they are to be implemented so that the data remain available, usable, and comprehensible (understandable). Of course, this also includes basic information such as the project name, third-party funders, project partners, etc.

      The DMP thus records how the resulting research data is handled during and after the research project. To create a substantial DMP, you need to address issues of data management, metadata, data retention and data analysis in a structured way.

      It makes sense to create the DMP before starting the data collection, because it forms the basis for decisions concerning, for example, data storage, backup, and processing. Nevertheless, a DMP is not a static but a living document that can be adapted again and again during the project.

    • 3.4 What does a data management plan include?

      The DMP contains information about the data, the data format, how the data is handled and how the data is to be interpreted. To decide which aspects should be included, the following sample questions, can be helpful:

      • What data is created?
      • How and when do you collect the data?
      • How do you process the data?
      • In which format do you store the data and why did you decide on this format?
      • Do you use file naming standards?
      • How do you ensure the quality of the data? This refers to the collection as well as to the analysis and processing
      • Should you use existing data? If so, where does it come from? How will existing and newly collected data be combined and what is the relationship between them?
      • Who is responsible for data management?
      • Are there any obligations, e.g. by third-party funding bodies or other institutions, regarding the sharing of the data created? (Legal requirements also play a role here)
      • How will the research data be shared? From when on, and for how long will it be available?
      • What costs arise for the RDM (these include e.g. personnel costs, hardware and software costs, possibly costs for a repository) and how are these costs covered?
      • What ethical and data protection issues need to be taken into account?
      • Is it necessary for political, commercial, or patent reasons to make the research data accessible only after a certain blocking period (Embargo)?
      • How will the data be used in the future?
      • In what way should the data be cited? Can the data be made unambiguous and permanently traceable by means of a persistent identifier? (See Chapter 4.3)

      The following checklists, samples, templates and wizards provide further assistance in creating data management plans:

    • 3.5 DMP Tools

      There now is a whole range of tools for faster and easier creation of data management plans. For example, one can compile a DMP with text modules or one is guided through a catalogue of questions. There are usually different templates for different funders.

      You can find a detailed list of other free DMP tools at the website of our colleagues at forschungsdaten.info.

    • References,further reading and online sources Страница
    • Test - 3 Data management plan Тест

      Test your knowledge about the content of this chapter!

    • Handout - 3 Data management plan Файл

      A summary of the most important facts.