Data Management Plan Guidance

Introduction

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., data collection; documentation and metadata; storage, deposit and preservation; sharing and reuse; responsibilities and resources; and ethics and legal compliance. See page two for guidance on completing each of these sections.  

Typically, an ideal DMP will be complete, precise, and in line with disciplinary best practices. Shortcomings in a DMP will normally stem from lacking one 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). CIHR recognizes that for many research fields, data management practices are in development and disciplinary best practices have not yet been established (e.g., preferred repositories, metadata standards, etc.).

DMPs should describe how data will be FAIR – findable, accessible, interoperable, and reusable. This does not mean that the DMP needs to include a section specifically devoted to making data FAIR. Rather, by completing each section completely, precisely, and in line with disciplinary best practices (where they exist), the DMP will describe how the data will be FAIR. CIHR recognizes that the extent to which data can be FAIR could be constrained by infrastructure limitations (e.g., lack of suitable repositories) and disciplinary practices (e.g., metadata standards have not been established). CIHR also recognizes that 'accessible' data is not synonymous with 'open' data. In many instances, due to ethical, commercial or legal obligations, access to data will need to be controlled; and in some instances, access to data cannot be provided at all. See  CIHR's guidance on how to make data FAIR.

For research conducted by and with First Nations, Inuit and Métis communities, DMPs should be co-developed with these communities, in accordance with research data management principles that they accept, such as the CARE (collective benefit, authority to control, responsibility, and ethics) or OCAP© (ownership, control, access and possession) principles. Where co-development is not possible, the DMP should respect Indigenous data sovereignty, include considerations related to Indigenous research data management, and acknowledge the possibility that the DMP will be revised in line with the community's values and principles.

Data Management Plans – Guidance on Specific Sections

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 (e.g., REDCap).

Documentation and Metadata

• 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.

Storage, Deposit and Preservation

• Explain where and how data will be stored and backed-up during the research project. Oftentimes this will be at your institution; but sometimes storage during the research project will be supplied by external providers, particularly if you plan to collaborate with industry or other non-academic partners.
• Explain where data will be retained and deposited following completion of the research project, and for how long. Sometimes researchers will decide to keep the data in their institution's repository; sometimes they will deposit the data in an external repository; and sometimes they will choose to keep some data at their institution, and deposit other data in an external repository. This is important to plan from the outset of the project so that there is a clear plan in place in case the NPI retires or moves to another institution.

Sharing and Reuse

• Explain which data will be shared, and in what form (e.g., raw, processed). If applicable, explain whether data are subject to access controls or limitations due to confidentiality, privacy, and/or intellectual property considerations.
• If applicable, describe the data access procedures.

Responsibilities and Resources

• 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.
• Provide an estimate of costs related to data management – e.g., data curation, file storage and backup, archiving.

Ethics and Legal Compliance

• Describe any ethical or legal obligations the data are subject to. If the project includes sensitive data, describe how these data will be securely managed.
• The DMP should explain, if applicable, potential risks of managing and sharing sensitive data – e.g., privacy, consent, etc. – and describe how these risks will be mitigated.

How to Make Your Data FAIR – 5 Essential Steps

Researchers should follow  international best practices for ensuring that research data are shared in a manner such that they are Findable, Accessible, Interoperable and Reusable, referred to as the FAIR principles. This document provides guidance on how to make research data FAIR.

The FAIR principles do not concern, and this document does not provide guidance on, ethical issues and approaches that must be considered to determine whether and how access should be provided to research data. For information and guidance on ethical issues related to data sharing, please reach out to data librarians and/or research ethics officers at your institution.

For research conducted by and with First Nations, Métis and Inuit communities, any data that are made FAIR should be done so only with the knowledge and consent by the Indigenous community and in accordance with research data management principles the community accepts, such as the CARE (collective benefit, authority to control, responsibility, and ethics) and OCAP© (ownership, control, access and possession) principles.

The box below includes a quick summary on how to make data FAIR in five  steps. For more detailed and technical guidance, consult the FAIR Principles webpage at GOFAIR.

Date modified:

2024-12-13