Strategy scope
The strategy applies to research and scholarly activities undertaken by faculty, students, and staff throughout SAIT, including those in the department of Applied Research and Innovation Services.
It is reviewed and updated annually by the Vice President Academic. Impact measures for each priority will be developed and reported upon as part of the review process. For further information please contact Vice President Academic Janet Welch.
Tri-Agency background
In 2021, the Tri-Agency (made up of the Canadian Institutes of Health Research, the Natural Sciences and Engineering Research Council of Canada, and the Social Sciences and Humanities Research Council of Canada) released a Research Data Management (RDM) Policy to “support Canadian research excellence by promoting sound RDM and data stewardship practices.”
This policy has three main components:
- Institutional RDM strategy (for institutions): A requirement that each post-secondary institution eligible to administer Tri-Agency funds create an institutional RDM strategy, make that strategy publicly available on the institution’s website, and notify the agencies when the strategy is complete.
- Data management plans (for individual researchers): A requirement that all grant proposals submitted to the agencies include best practices in RDM as part of their methodologies. Some funding opportunities require the submission of a research data management plan with the grant proposal.
- Data deposit (for individual researchers): A requirement that grant recipients 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."
RDM working group
At SAIT, a small working group made up of representatives from faculty, the Vice President Academic’s office, the Reg Erhardt Library, and Applied Research and Innovation Services came together to begin work on strategies to meet the first requirement of the Tri-Agency RDM Policy.
The group used the Digital Research Alliance of Canada’s Institutional Research Data Management Strategy Development Template v. 3.0 as the basis for their process. They gathered data on the current state of RDM practice at SAIT, as well as the desired future state, in a number of ways:
- A series of meetings was held with a larger advisory group to work through the RISE Framework, with supplemental questions from the MAMIC inventory. This advisory group had representatives from Information Technology Services, the Data Governance Office, the Vice President Academic’s office, Business Intelligence and Analytics, the Reg Erhardt Library, faculty, the Office of General Counsel, Applied Research and Innovation Services, and Academic Systems.
- A survey regarding current RDM practices was distributed to academic staff and faculty who had previously identified that they engaged in scholarly activity, as well as to staff in Applied Research and Innovation Services.
- Informational interviews were held with a sample of researchers on campus who had been involved in projects in partnership with different Indigenous communities, as well as with the Director of Indigenous Engagement.
- An informational interview was held with the co-chair of the Research Ethics Board.
A draft version of the strategy was sent to the members of the larger advisory group and to the people with whom informational interviews were held for feedback. The final draft of the strategy was approved by SAIT's Executive Management Council on April 7, 2025.
SAIT’s commitment to research excellence
We recognize research data as a vital output of the research process, and commit to supporting our researchers in adopting best practices in research data management, including those outlined in the FAIR Principles, the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans – TCPS 2 (2022), the Tri-Agency Framework: Responsible Conduct of Research, the Tri-Agency Statement of Principles on Digital Data Management, and any other relevant ethical, legal, and commercial guidelines.
Indigenous data sovereignty
SAIT recognizes the importance of Indigenous data sovereignty and commits to managing “data created in the context of research by and with First Nations, Metis, and Inuit communities, collectives and organizations...according to principles developed and approved by those communities, collectives and organizations, and in partnership with them.” (Tri-Agency RDM Policy).
We recognize “that a distinctions-based approach is needed to ensure that the unique rights, interests and circumstances of the First Nations, Metis, and Inuit are acknowledged, affirmed, and implemented.” (Tri-Agency RDM Policy).
Our goal is to build capacity internally to support our researchers in learning about Indigenous research generally and Indigenous research data management more specifically. The Office of Indigenous Engagement is working to partner with other institutions to bring in education opportunities for SAIT faculty and staff.
Institutional support
Knowledge about best practices in research data management and the capacity to meet them are currently inconsistent across SAIT. Some researchers and departments have been working with RDM practices for a while, and some are encountering them for the first time. Knowledge, use, and availability of the information technology infrastructure needed to manage data both during and after the active research stage is also inconsistent across the institution.
Over the next three years, SAIT will support all of those engaged in research to learn best practices in RDM, while recognizing engagement levels and capacity-building needs will differ for different departments. We will create a baseline of consistency, although some researchers and departments may need to be supported at a higher level.
SAIT will need to make investments in infrastructure and human resources to create an environment that can support its researchers in meeting best practices in RDM. Staff roles will need to be redesigned to include these new responsibilities.
Due to the infrastructure, ongoing maintenance, and personnel costs involved, SAIT will not look to build its own data repository but will instead look to appropriate hosted third-party solutions aligned with Tri-Agency requirements, including that they are on Canadian soil, secure, curated, and publicly accessible.
Strategic priorities
Over the next three years, SAIT will work toward the following:
| Goal | Contributing Departments |
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Using the ad-hoc advisory committee involved in the creation of the Institutional Strategy as a starting point, create a standing Research Data Management Advisory Committee. |
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Revise the previously created Research Data Management Procedure into a stand-alone Research Data Management Policy, and work to ensure that related policies and procedures are complementary. |
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Investigate current technology capabilities, use cases, and requirements of researchers at SAIT, including requirements to meet legal and ethical obligations. |
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Create and promote a process for managing the legal and ethical risks involved with data deposit. |
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Using third-party content as a base where possible, work to create an education program, an advisory service, and a community of practice to assist researchers with best practices in RDM, creating data management plans, creating data security plans, preparing their data for deposit, and publishing their data if appropriate. |
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Build or bring in educational programming related to Indigenous data sovereignty and principles of community-led governance for data, such as OCAP®. |
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| Goal | Contributing Departments |
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Create and promote guidance on how to apply the newly created policy. |
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Develop local guidance and templates for creating data management and data security plans. |
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Create an education and promotion program to let researchers know about the support and tools available for additional storage needs, security management, high performance computing, file transfer services, and purchasing processes for new software. |
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Create a standard process for collecting metadata on data and related research outputs across the institution and catalogue it according to best practice standards, in conjunction with the Research Metrics System project initiated by the Vice-President Academic and currently in-progress. |
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Create a network for researchers who are engaged in research in partnership with Indigenous communities to connect and share knowledge. |
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| Goal | Contributing Departments |
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Build up IT infrastructure to support researchers with their active data management needs, using cloud and third-party solutions where those are more appropriate and cost-effective:
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Mandate the submission of a data management plan for all internal research funding opportunities, using internally developed guidance and templates. |
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Create a process for the assessment of data and metadata that is prepared for deposit to ensure it meets compliance requirements. |
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Looking ahead, SAIT’s vision is to establish a robust and sustainable RDM framework that supports our researchers and staff in producing high-quality, reproducible, and accessible research outputs, fostering innovation and collaboration.
Data definitions
“Facts, measurements, recordings, records, or observations about the world, collected by researchers, that are yet to be processed/interpreted/analysed. Data may be in any format or medium taking the form of writings, notes, numbers, symbols, text, images, films, video, sound recordings, pictorial reproductions, drawings, designs or other graphical representations, procedural manuals, forms, diagrams, work flow charts, equipment descriptions, data files, data processing algorithms, or statistical records.” (CODATA RDM Terminology 2023 Version)
“Data about data. It is data (or information) that defines and describes the characteristics of other data. It is used to improve the understanding and use of the data.” (CODATA RDM Terminology 2023 Version)
“Research data are data that are used as primary sources to support technical or scientific enquiry, research, scholarship, or creative practice, 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. Research data may be experimental data, observational data, operational data, third party data, public sector data, monitoring data, processed data, or repurposed data. What is considered relevant research data is often highly contextual, and determining what counts as such should be guided by disciplinary norms.” (Tri-Agency Research Data Management Policy – Frequently Asked Questions)
“Research data management (RDM) refers to the processes applied through the lifecycle of a research project to guide the collection, documentation, storage, sharing and preservation of research data.” (Tri-Agency Research Data Management Policy – Frequently Asked Questions)
“A data management plan (DMP) is a living document, typically associated with an individual research project or program that consists of the practices, processes and strategies that pertain to a set of specified topics related to data management and curation.” (Tri-Agency Research Data Management Policy – Frequently Asked Questions)
“’Data deposit’ refers to when the research data collected as part of a research project are transferred to a research data repository.” (Tri-Agency Research Data Management Policy – Frequently Asked Questions)
“Data repositories are a centralized place to hold data, share data publicly, and organize data in a logical manner." (Harvard University Data Repositories)
“Techniques designed to make the risk of identifying a particular individual in a dataset negligible, whilst retaining the re-usability of the dataset. The purpose is to protect the privacy of the individual and comply with legislation, whilst enabling data sharing. Methods include removing direct and indirect identifiers such as names, addresses, social insurance numbers, or dates of birth, or using obfuscation methods such as encryption, hashing, generalisation, pseudonymisation, and perturbation.” (CODATA RDM Terminology 2023 Version)
Related policies
The following policies at SAIT are relevant to research data management:
Research Services
Oki, Âba wathtech, Danit'ada, Tawnshi, Hello.
SAIT is located on the traditional territories of the Niitsitapi (Blackfoot) and the people of Treaty 7 which includes the Siksika, the Piikani, the Kainai, the Tsuut’ina and the Îyârhe Nakoda of Bearspaw, Chiniki and Goodstoney.
We are situated in an area the Blackfoot tribes traditionally called Moh’kinsstis, where the Bow River meets the Elbow River. We now call it the city of Calgary, which is also home to the Métis Nation of Alberta.