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    Research Data Management Strategy

Data Management Plans

  • Data Management Plans (DMPs) should include research methodologies that reflect best practices for managing research data throughout the research lifecycle. DMPs are living documents that can be modified to accommodate changes throughout the course of a research project and the content or length of the DMP is dependent on the research project.

    This is a formal document which clearly articulates the strategies and tools researchers will implement to effectively manage their data throughout the research project. DMPs support the management of data both during the active phases of the research and after the completion of the research project. The overall objective of a DMP is to address issues related to data management before starting a research project to strengthen research.

    Why are DMPs Important?

    DMPs are important to the research process as they can help researchers to:

    Set out Consistent Strategies
    Before starting your research set out strategies for how data will be managed throughout its entire lifecycle.
    Identify Strengths & Weaknesses in Current Processes
    This will help to make decisions on how to effectively integrate data management into the research process.
    Prepare Data for Future Reuse, Preservation & Sharing
    Data should be prepared in collaboration with researchers and research communities with the future in mind.
    Reduce Overall Cost
    Increase project efficiencies to lower the costs associated with research.

    Planning of the research data is an important initial step in Research Data Management and some key components that need to be considered are:

    • Institution and funding agency expectations and policies
    • Whether raw data will be collected or reused
    • Kinds of data collected and format
    • Quantity of data collected
    • Whether versions of the data need to be tracked
    • Storage of active data and backup policy and implementation
    • Storage and archiving options and requirements
    • Organizing and describing or labelling of data
    • Data access and sharing
    • Privacy, consent, intellectual property, and security issues
    • Roles and responsibilities for data management of the research team
    • Budgeting for data management

    In addition, all DMPs should describe:

    • How data will be collected, documented, formatted, protected, and preserved;
    • How existing datasets will be used and what new data will be created over the course of the research project;
    • How and whether data will be shared;
    • Where and how the data will be deposited.
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