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Research Data Management Guide: Data Management Plan

What is a data management plan?

Data management plans help researchers choose the best methods for managing their research data. These plans describe how data will be collected, formatted, stored, and shared. They facilitate the work of other researchers wishing to use the research data by specifying the nature and mode of use of the data.

Using these plans also helps researchers identify the costs, benefits, and challenges of managing research data.

Use the DMP Assistant (below) for a step-by-step guide to developing your DMP.

What should be included in a data management plan?

Many tools are available on the internet to help you build your data management plan: DMP writing tools, examples of annotated DMPs, templates, etc. We recommend using a tool that incorporates the requirements of the major Canadian funding agencies. Usually, the DMP includes the following sections. Explanations are taken from the DMP Assistant.

Data collection

This section covers data collection issues such as data types, file formats, naming conventions, and data organization—factors that will improve the usability of your data and contribute to the success of your project.

Documentation and metadata

Because data are rarely self-explanatory, all research data should be accompanied by metadata (information that describes the data according to community best practices). Standards for metadata vary from one discipline to another, but they usually indicate who created the data, when and how they were created, their quality, accuracy, and precision, as well as other characteristics necessary to the discovery, understanding, and reuse of the data. Any restrictions on the use of data must be explained in the metadata and, whenever possible, information must be provided on how to obtain authorization to access the data. 

Storage and backup

It is imperative to plan how research data will be stored and backed up throughout and beyond the research project to ensure the safety and integrity of the data. Appropriate storage and backup not only help protect research data from catastrophic losses (due to hardware and software failures, viruses, hackers, natural disasters, human error, etc.), but also facilitate appropriate access by current and future researchers.

Preservation

Data preservation will depend on potential reuse value, whether there are obligations to either retain or destroy data, and the resources required to properly curate the data and ensure that they remain usable in the future. In some circumstances, it may be desirable to preserve all versions of the data (e.g., raw, processed, analyzed, final), but in others, it may be preferable to keep only selected or final data (e.g., transcripts instead of audio interviews).

Sharing and reuse

Many Canadian funding agencies now have policies requiring that research data be made accessible immediately upon publication of results or within a reasonable period. While data sharing contributes to the visibility and impact of research, the desire of researchers to publish as many publications as possible before releasing data must also be taken into account. Equally important is the need to protect the privacy of respondents and to handle sensitive data appropriately.

Responsibilities and resources

Data management refers to the “what” and the “how” of data-related management operations throughout the project lifecycle. Data stewardship, on the other hand, focuses on “who” is responsible for ensuring that this data management is carried out. A large research project, for example, will have several people in charge. The principal researcher must determine at the start of the project which members of the team will have data management responsibilities during and after the project.

Ethical and legal compliance

Researchers and their teams need to be aware of the ethical and legal policies and processes with which their research data management must comply. Protecting the privacy of the respondent is of paramount importance, and shapes many data management practices. In their data management plan, researchers must indicate how they will prepare, store, share, and archive data to ensure that participant information is protected throughout the research lifecycle from disclosure, harmful use, or inappropriate linkage with other personal data. We acknowledge that there may be cases where certain data and metadata cannot be made public due to policy or legal considerations. However, the default position must be that all research data and metadata is public.

Examples of data management plans