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Feb. 13, 2023
The 51本色 Research Data Management Strategy is mandated by the (March 2021). The institutional strategy must be publicly available by March 1, 2023.
This Strategy is valid from March 1, 2023 outlined herein, and is valid until further notice. This Strategy should be reviewed at a minimum every three years; however, in lieu of a review during any period specified, the current Strategy will remain in effect.
Review Period: Every 36 months
Previous Review Date: N/A
Next Review Date: March 1, 2026
As part of its commitment to research excellence, 51本色 (51本色) recognizes the positive impact that research data management (RDM) brings to the research enterprise. Research data are a critical research output that enables data synthesis, data reproducibility, and the dissemination of knowledge. The management of research data is guided by RDM best practices, subject-matter knowledge, and a policy landscape that includes universities, grant agencies, publishers, Indigenous communities, researchers, and data management professionals. 51本色 is committed to promoting research methodologies and providing institutional support that include established RDM best practices. These include:
51本色’s Research Data Management Strategy identifies researchers’ RDM requirements and the institutional services and supports that underpin good data stewardship practices. 51本色 researchers can use these supports to improve their research data management practices and meet their RDM commitments to granting bodies, Indigenous partners, research participants, publishers, and other community members.
The 51本色 Research Data Management Strategy is informed by Tri-Agency’s RDM requirements and expectations, which are outlined in its 2021 and 2016 . The 51本色 RDM Strategy applies to all research activities at the University regardless of their grant status.
All grant proposals submitted to the agencies should include methodologies that reflect best practices in RDM. For certain funding opportunities, the agencies will require data management plans (DMPs) to be submitted to the appropriate agency at the time of application, as outlined in the call for proposals; in these cases, the DMPs will be considered in the adjudication process.
For research conducted by and with First Nations, Métis and Inuit communities, collectives and organizations, DMPs must be co-developed with these communities, collectives and organizations, in accordance with RDM principles or DMP formats that they accept. DMPs in the context of research by and with First Nations, Métis and Inuit communities, collectives and organizations should recognize Indigenous data sovereignty and include options for renegotiation of the DMP.
DMPs help researchers better understand the technologies, people, and resources required to manage their research inputs and outputs. DMPs also describe how research data will be organized, described, stored, shared, and archived during the life of a research project and after project completion. Special attention should be afforded to data sensitivity and Indigenous data sovereignty.
Researchers should create DMPs when designing their research program. Any research proposal submitted for Tri-Agency funding must either include a DMP or at least articulate methodologies that reflect best practices in RDM; this requirement will be disclosed in the application process. Tri-Agency funding opportunities that require a full DMP will consider the DMP as part of the adjudication process. The University encourages researchers to develop DMPs for both funded and unfunded research.
Data management plans associated with research that is conducted by or with Indigenous communities must be co-developed with these communities, be held in a format they accept, and include options for renegotiation. Indigenous research partners will guide and determine how their data is collected, stored, used, and preserved, during and after the life of the project.
The 51本色 Library provides DMP consultation services to researchers in all fields. This includes consultation and support for writing a DMP with the Tri-Agency recommended DMP Assistant. The Library also provides DMP training to research teams, graduate students and academic departments. Office of Research Services grant facilitation staff provide guidance to researchers applying to grant opportunities with DMP requirements.
Research Data should be collected and stored throughout the research project using software and formats that ensure secure storage, and enable the preservation of and access to the data well beyond the duration of the research project.
Researchers should collect, store, and back up research data on platforms that enable file security and file integrity while adhering to their and the University’s ethical and legal obligations. Researchers should consult with ICT, ideally at the time of developing a DMP, to identify ICT-approved solutions for their active-phase data storage needs. Researchers are also expected to adhere to legislation, including , , , and other provincial and federal statutes. Researchers should consult with the for questions or concerns.
ICT Active Research Data Storage Solutions
ICT offers a variety of storage solutions including on-premise centralized storage and cloud storage for active research. These storage solutions are University approved and offer high-volume storage of data, robust security functions, and data backup during the life of a research project. It is important to note that some of these options have a capital and/or an operational cost associated with them that is the responsibility of the researcher to fund. These solutions include:
Links:
In line with the concept of Indigenous self-determination, and in an effort to support Indigenous communities to conduct research and partner with the broader research community, 51本色 will work collaboratively with researchers to understand data storage needs within the Indigenous communities that they are working with. The guidance of Indigenous communities is important in this collaboration with the university.
All research data should be accompanied by metadata that accords with international and disciplinary best practices to enable future users to access, understand and reuse the data.
Researchers should be familiar with research data curation standards in their field and apply these practices to their work. Research data should be documented, described, and organized to enable findability and reuse. This includes developing clean, error-free datasets as well as including documentation and code that contextualizes collection, processing, and analysis methodologies to improve understanding and enable reuse.
The 51本色 Library offers data curation consultation and training opportunities, including data organization, file naming and description, version control, and documentation. Research data archived with the Library in its Borealis data repository will be curated according to best practices that improve findability, access, interoperability, and reuse.
Grant recipients are required to deposit into a digital repository all digital research data, metadata and code that directly support the research conclusions in journal publications and pre-prints that arise from agency-supported research. Determining what counts as relevant research data, and which data should be preserved, is often highly contextual and should be guided by disciplinary norms.
The deposit must be made by the time of publication. The choice of the repository may be guided by disciplinary expectations and the recipient’s own judgment, but in all cases, the repository must ensure safe storage, preservation, and curation of the data.
Grant recipients are not required to share their data. However, the agencies expect researchers to provide appropriate access to the data where ethical, cultural, legal and commercial requirements allow, and in accordance with the FAIR principles and the standards of their disciplines. Whenever possible, these data, metadata and code should be linked to the publication with a persistent digital identifier.
For research conducted by and with First Nations, Métis and Inuit communities, collectives and organizations, these communities, collectives or organizations will guide and ultimately determine how the data are collected, used and preserved, and have the right to repatriate the data. This could result in exceptions to the data deposit requirement.
Research data that supports publications must be deposited into a repository for archiving, access, and use. The repository must be able to professionally curate, store, and preserve research data; a researcher’s hard drive or OneDrive is not a repository. Researchers must ensure that data be “as open as possible and as closed as necessary.” Researchers should identify potential data repositories when writing their DMPs.
Data associated with research conducted by and with Indigenous communities and organizations will be subject to these communities’ conditions and may result in exceptions to data deposit. These exceptions can include the deposit of raw or processed data in the community’s repository or a repository of their choosing.
Researchers can archive their research data with the Library’s Borealis data repository. All data submitted to Borealis is curated according to best practices that improve its discovery, access, and re-use. Data must be open-access and non-sensitive. Researchers who require restricted data deposit services may consult with the Library to find a suitable repository.
Research data must be managed in agreement with all commercial, legal and ethical obligations.
Data management should be performed in accordance with the requirements of the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans - 2nd edition. This statement provides guidance on data management aspects of research involving humans, such as consent, privacy and confidentiality, Indigenous Peoples’ rights, secondary use of data and data linkage. Data management should also be performed in accordance with the requirements of the Tri-Agency Framework: Responsible Conduct of Research.
Sensitive data includes but is not limited to research involving human participants, research conducted by or with Indigenous communities or about Indigenous resources, proprietary data, and industry data. The management of sensitive data is dependent on disciplinary norms, university and granting body policy instruments, and legislation. Researchers whose work involves sensitive data must articulate their collection, storage, access, retention, and disposition plans in a data management plan. At the very least, researchers should store sensitive data only on authorized and approved 51本色 software, platforms and devices. Sensitive data should be encrypted, and care should be afforded to its access, sharing, linking, and publication. The Library and ICT can give guidance on sensitive data handling as capacity allows. Dedicated and funded ICT resource capacity continues to be worked towards for the future.
The 51本色 Library consults on sensitive data handling, storage, and disposition as well as the development of data management plans. Researchers can consult with the Office of Research Services and the REB regarding research involving human participants. ICT consults with researchers on finding software solutions, approving software for use, advising on licensing costs, as well as recommending secure data storage and transfer solutions (with costs associated), in alignment with 51本色’s and 9.5 External Information Technology and Cloud Services policy. The 51本色 Library, ICT and the REB are currently developing institutional guidelines for safeguarding sensitive participant data.
In line with the concept of Indigenous self-determination and in an effort to support Indigenous communities to conduct research and partner with the broader research community, the agencies recognize that data related to research by and with the First Nations, Métis, or Inuit whose traditional and ancestral territories are in Canada must be managed in accordance with data management principles developed and approved by these communities, and on the basis of free, prior and informed consent. This includes, but is not limited to, considerations of Indigenous data sovereignty, as well as data collection, ownership, protection, use, and sharing. The principles of Ownership, Control, Access and Possession (OCAP®) are one model for First Nations data governance, but this model does not necessarily respond to the needs and values of distinct First Nations, Métis, and Inuit communities, collectives and organizations. The agencies recognize that a distinctions-based approach is needed to ensure that the unique rights, interests and circumstances of the First Nations, Métis and Inuit are acknowledged, affirmed, and implemented.
Researchers’ RDM best practices must recognize Indigenous data sovereignty and honour their Indigenous partners’ data ownership rights. Data management plans associated with research that is conducted by or with Indigenous communities must be co-developed with these communities, be held in a format they accept, and include options for renegotiation. Indigenous research partners will guide and determine how their data is collected, used, and preserved.
51本色 researchers must recognize and accommodate their Indigenous partners’ data rights of ownership, control, access, and possession, which can include location or co-location of data on community infrastructure. Indigenous research partners also have the right to repatriate research data, even after data deposit. Special attention must be made by researchers and research support staff to the vulnerabilities of their Indigenous research partners within the research process, and their actions should be guided by the ethical practices of their subject area as well as University supports such as the Research Ethics Board and Privacy and Security Impact Assessment (PSIA) process. Researchers should stay informed of and be guided by Indigenous research data stewardship instruments such as the First Nations Principles of OCAP®, the Manitoba Metis Federation’s OCAS Principles, the Inuit Tapiriit Kanatami National Inuit Strategy on Research, and the GIDA CARE Principles.
51本色 recognizes the data sovereignty rights of its Indigenous research and community partners. Its research data management strategy is informed by the concepts of Indigenous data ownership, control, access, and possession. 51本色 will provide consultation, training, and support in the development of values-based relationships with its Indigenous partners and in the stewardship of Indigenous research data.
Researcher Responsibilities
As part of their understanding of the broader policy framework guiding research, 51本色 Researchers should understand the Tri-Agency RDM Policy and Statement of Principles of Digital Data Management, and apply them to their work.
The Office of Research Services will consult with researchers to clarify policy documents and researcher obligations. The Library holds regular data management information sessions that introduce RDM, Tri-Agency policies, and institutional supports.
Definitions are adapted from the CODATA (.
Research Data:
Data that are used as primary sources to support technical or scientific inquiry, research, scholarship, or artistic activity, and that are used as evidence in the research process and/or are commonly accepted in the research community as necessary to validate research findings and results. All other digital and non-digital content have the potential of becoming research data. Research data may be experimental data, observational data, operational data, third-party data, public sector data, monitoring data, processed data, or repurposed data.
Data Management Plan:
A formal statement describing how research data will be managed and documented throughout a research project and the terms regarding the subsequent deposit of the data with a data repository for long-term management and preservation.
Metadata:
Literally, “data about data”; data that defines and describes the characteristics of other data, used to improve both business and technical understanding of data and data-related processes. Business metadata includes the names and business definitions of subject areas, entities and attributes, attribute data types and other attribute properties, range descriptions, valid domain values and their definitions. Technical metadata includes physical database table and column names, column properties, and the properties of other database objects, including how data is stored. Process metadata is data that defines and describes the characteristics of other system elements (processes, business rules, programs, jobs, tools, etc.). Data stewardship metadata is data about data stewards, stewardship processes and responsibility assignments. Data Repository:
Repositories preserve, manage, and provide access to many types of digital materials in a variety of formats. Materials in online repositories are curated to enable search, discovery, and reuse. There must be sufficient control for the digital material to be authentic, reliable, accessible, and usable on a continuing basis.