Data management plans (DMPs) are highly contextual to research field, project, and mode of inquiry, but every DMP should include considerations of several key topics – i.e., responsibilities and resources; ethical, legal, commercial, and Indigenous data management considerations (as applicable); data collection; documentation and metadata; data storage, security, and access; and data retention, deposit and availability. DMPs can be developed to guide a single research project, span a multiproject research initiative or a longer-term program of research. As living documents, DMPs should be revised and updated as the research project progresses.
Typically, an ideal DMP will be complete, precise, and aligned with disciplinary best practices. Shortcomings in a DMP will normally stem from lacking one or more of these features – e.g., it will not discuss data deposit (incomplete), or it will not say where data will be deposited (imprecise), or the chosen repository is poorly suited for the data (not in line with disciplinary best practices).
For research conducted by and with First Nations, Inuit and Métis communities, DMPs should be co-developed with these communities, recognizing Indigenous data sovereignty and in accordance with research data management principles that they approve, such as the CARE (collective benefit, authority to control, responsibility, and ethics) principles, the First Nations principles of OCAP© (ownership, control, access and possession), the National Inuit Strategy on Research Principles of Inuit Qaujimajatuqangit, or the Manitoba Métis principles of OCAS.
For funding opportunities where both the National Security Guidelines for Research Partnerships and the RDM policy’s DMP requirement apply, researchers should identify risks in their Risk Assessment Form (RAF) that will be mitigated — in part or in whole — by a DMP. In these cases, the risk mitigation plan section of the RAF must also describe how the DMP will address those data-related risks. Corresponding instructions will be indicated in the Research Security section of the funding opportunity literature.
Guidance on Specific Sections
This DMP format closely aligns with the Digital Research Alliance of Canada’s Simplified DMP Template, developed by the DMP Expert Group (DMPEG) and which is accessible to researchers through DMP Assistant. DMP Assistant is a freely available, national, online, bilingual data management planning tool that assists researchers in preparing DMPs. The contents of the Simplified Template are available for viewing here.
Introductory Context – Responsibilities and Resources; Ethical, Legal, and Commercial Considerations
- Identify who will be responsible for managing the project's data during and after the project, and the major data management tasks for which they will be responsible.
- If applicable, describe what resources are required to meet your project’s data management needs, including if dedicated positions or outsourcing of tasks will be required.
Tip: Depending on your project’s needs, responsibilities may be assigned to specific individuals or be shared, including by the principal investigator, co-investigators, research staff and trainees.
- Describe any ethical, legal or commercial constraints the data are subject to. If the project includes sensitive data, describe how ethical obligations preliminary to the research project (e.g., participant consent to collect and use data) will be met.
Tip: Don’t just identify privacy risks; also explain how they will be mitigated, for example whether data will be de-identified or anonymized.
Indigenous Data Governance
- If the project involves research conducted by and with First Nations, Inuit or Métis communities, explain how Indigenous data sovereignty principles will be respected and followed.
- Explain how the DMP was co-developed with the Indigenous partner(s) involved in the research, including who was engaged and when, any existing formal agreements, and how the partnership informed the DMP.
Tip: Don’t just commit to following Indigenous RDM principles. Describe the approach for managing Indigenous research data throughout the course of the project and beyond – for example, explain the governance structures for ensuring Indigenous ownership and control of Indigenous data.
Data Collection
- Explain what data will be collected, created or used, and how – e.g., through observational studies, experiments, simulations, and the use of specific software or tools.
Tip: In addition to explaining what data will be collected, identify the software or platform being used to collect the data.
Documentation and Metadata
- Explain how the data will be documented and organized throughout the project lifecycle.
- Explain whether any information will be provided for others to understand and reuse the data – e.g., a "readme" text file, code books, or lab notebooks, etc. Ideally, dataset documentation should be provided in machine readable, openly accessible formats (e.g., .csv, .txt file formats).
- Where possible and applicable, state what metadata standard will be followed. The standard can be general (e.g., Dublin Core), but will ideally be domain-specific (in which case, it may be supported by the repository where you plan to deposit the data). Stating the metadata standard will be particularly pertinent to research teams planning to establish a data platform or hub.
Tip: Review the website for the repository in which you plan to deposit your data for information on any documentation or metadata standards they require or prefer.
Storage, Security and Access
- Explain where and how data will be stored and secured during the research project, and which team members will have access to the data. When the research project involves highly sensitive data and travel, explain how these data will be managed and accessed.
Tip: Access permissions can change throughout the course of a research project. Some people may require access at specific stages of the research project (e.g., the data analysis stage) but not once the project is complete. Include these details in your DMP.
Retention, Deposit and Availability
Data retention refers to the storage and management of research data after completion of the active phases of a research project and primarily focuses on safekeeping of the data. It does not necessarily involve making the data discoverable or available to others.
- Explain where data will be retained following completion of the research project, and for how long. If applicable, explain which data will not be retained and why.
Data deposit refers to the deposit of research data into a digital data repository for supporting their discovery, appropriate availability, and potential reuse. Data should ideally be deposited into a repository that assigns a persistent identifier, promotes FAIR (Finable, Accessible, Interoperable, and Reusable) data principles, and enables links to research outputs such as journal articles and other forms of scholarly communication.
- Explain which data will be deposited and where, and in what format (e.g., raw, processed, or both; tabular, text, images, other).
Tip: Say which repository you plan to deposit the data in (not just that the data will be deposited) and how long the data will be kept there.
Data availability refers to the ability of humans and machines to access research data and metadata through well-defined mechanisms, with clear information about the conditions under which access can be obtained. Data being "available" does not necessarily mean "open to everyone immediately". It means there is a clear, documented pathway to obtain the data via immediate download or a formal application process. Making data available is about removing unnecessary barriers to the data while respecting legitimate restrictions.
- Explain which data will be made available and in what form (e.g., raw, processed, both).
- If applicable, describe what data availability procedures will be implemented, including access controls, adjudication of data availability requests and limitations due to confidentiality, privacy and/or intellectual property considerations.
Tip: If the data cannot be made available for ethical or other reasons, provide a clear explanation for why this is the case; do not simply state that they will not be shared. For example, certain community partner requirements may not allow data availability under any circumstance. If such requirements apply, explain how. See How to write a data availability statement: A brief guide.
Additional Resources
Researchers are encouraged to familiarize themselves with the DMP resources available at their institution. Information about these resources may be available in their institution’s research data management strategy.
In addition to hosting DMP Assistant, the Digital Research Alliance of Canada provides various resources to help with creating DMPs, including: