Land acknowledgement
Royal Roads University acknowledges that the campus is located on the traditional lands of the Xwsepsum (Esquimalt) and Lkwungen (Songhees) ancestors and families who have lived here for thousands of years.
This land has been part of the fabric of the life of Indigenous communities long before Hatley Castle was built, and it will be long into the future. It is with gratitude that we now learn and work here, where the past, present and future of Indigenous and non-Indigenous students, faculty and staff come together.
Hay’sxw’qa si’em!
Royal Roads University Research Data Management Strategy
Researchers at Royal Roads University endeavor to inspire action to address real-world challenges and contribute to positive change in individual lives, communities, and societies be they local, national, or international. Research at Royal Roads University is conducted in various fields of inquiry – social sciences and humanities, health, and physical and environmental science – however, research by faculty, librarians, staff, and students is largely in the social sciences. Our research is primarily inter- and trans-disciplinary, and partnerships with those that may be impacted by or use the research are critical. We are committed to the inclusion of equity-seeking groups in the conduct and leadership of research and to their access to the products of the research. Appropriate, accurate, and, secure collection, preservation, and sharing of research data is key to the integrity of our research collaborations with our partners.
Our research is designed to be shared and developed with practitioners who may benefit from the findings, data, and results. In addition, research and research data inform our university operations, our teaching and learning practices, and how we work at the university. In the spirit of inquiry, we move forward in the quest for knowledge and insight with a commitment to action.
Introduction and background
Over the last several years, there has been a shift toward publishing not only the results of academic research projects, but also the data from which the results were derived to enhance research rigor. This movement has been worldwide and approached similarly by different nations. Canada’s major federal research funding organizations – the Tri-Agencies, which include SSHRC, NSERC, and CIHR – developed a policy in consultation with post-secondary institutions across Canada to affect this transition (see: https://science.gc.ca/site/science/en/interagency-research-funding/policies-and-guidelines/research-data-management/tri-agency-research-data-management-policy). As noted on the Tri-Agency website, “RDM is a key element of research excellence. The agencies have a responsibility to ensure the research they fund is conducted according to the highest standards.”
The Tri-Agency Research Data Management policy has three components: 1) requirements for researchers to submit Data Management Plans (DMPs) as part of funding applications; 2) requirements for researchers to deposit their research data for safe storage, preservation, and curation; and 3) a requirement for institutions to develop an Institutional Research Data Management Strategy. The Tri-Agency also continues to help co-ordinate interdisciplinary teams to develop tools, strategies, and governance models that support data development, sharing, and storage.
The Director of Research and Innovation, the University Librarian, the Chair of the RRU Ethics Board, and the CIO have been following the development of the Tri-Agency policy since the early stages of consultation. Efforts toward capacity building in RDM support have been cooperative and incremental since that time:
- In 2016, the Library added Research Data Management support as a core Librarian role. In 2018, that Librarian customized the DMP Assistant to RRU.
- In 2019/20, a small team from the Library and the Research Office conducted a preliminary research data needs assessment by interviewing a selection of RRU researchers for their current data production and support needs.
- In April 2020, the Library formally joined a national license for Dataverse - now called Borealis - to support the data deposit needs of RRU researchers.
- In early 2021, RRU expanded licensing of the data analysis software NVivo to increase researcher access to data collection tools.
These activities were based on research, benchmarks, feedback, and consultation and have helped to build initial capacity in this RDM support. The intention of RRU’s Research Data Management Strategy is to formalize and broaden RRU’s next steps for a planned and resourced approach to developing a foundation of Research Data Management that is modelled on best practices (e.g. OCAP, CARE, FAIR, etc).
Definitions
Research Data: 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, Government of Canada 2022).
Research Data Management (RDM): 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. RDM is essential throughout the data lifecycle—from data creation, processing, analysis, preservation, storage and access, to sharing and reuse (where appropriate), at which point the cycle begins again. Data management should be practiced over the entire lifecycle of the data, including planning the investigation, conducting the research, backing up data as it is created and used, disseminating data, and preserving data for the long term after the research investigation has concluded. (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2022).
Data Deposit: Data deposit refers to “when the research data collected as part of a research project are transferred to a research data repository. The repository should have easily accessible policies describing deposit and user licenses, access control, preservation procedures, storage and backup practices, and sustainability and succession plans. The deposit of research data into appropriate repositories supports ongoing data-retention and, where appropriate, access to the data. Ideally, data deposits will include accompanying documentation, source code, software, metadata, and any supplementary materials that provide additional information about the data, including the context in which it was collected and used to inform the research project. This additional information facilitates curation, discoverability, accessibility, and reuse of the data” (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2022).
Data Management Plan (DMP): A data management plan 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. DMPs should be modified throughout the course of a research project to reflect changes in project design, methods, or other considerations. DMPs guide researchers in articulating their plans for managing data; they do not necessarily compel researchers to manage data differently” (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2022).
FAIR Principles: FAIR principles for scientific data management and stewardship are an international best practice for improving the findability, accessibility, interoperability and reuse of digital assets.
- Findable: The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of data sets and services.
- Accessible: Once the user finds the required data, the user needs to know how they can be accessed, possibly including authentication and authorization.
- Interoperable: The data usually need to be integrated with other data. In addition, the data need to be interoperable and able to function with applications (including computer software and hardware) or workflows for analysis, storage and processing.
- Reusable: The ultimate goal of FAIR is to optimize the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings (Go Fair n.d. https://www.go-fair.org/fair-principles/).
Indigenous Research: Research in any field or discipline that is conducted by, grounded in or engaged with First Nations, Inuit, Métis or other Indigenous nations, communities, societies or individuals, and their wisdom, cultures, experiences or knowledge systems, as expressed in their dynamic forms, past and present. Indigenous research can embrace the intellectual, physical, emotional and/or spiritual dimensions of knowledge in creative and interconnected relationships with people, places and the natural environment. (Social Sciences and Humanities Research Council, Definition of Terms, Government of Canada 2021).
Institutional Research Data Management Strategy: An institutional RDM strategy describes how the institution will provide its researchers with an environment that enables and supports RDM practices. Developing these strategies will help research institutions identify and address gaps and challenges in infrastructure, resources and practices related to RDM. (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2022).
Metadata: Metadata are data about data—data that define and describe the characteristics of other data. Accurate and relevant metadata are essential for making research data findable. A principle to help determine what information should be included in metadata is the open archival information system model criterion that the information be “independently understandable.” “Independently understandable” means enough information has been provided in the metadata for someone else to be able to understand the data set without needing its creator explain it. (Tri-Agency Research Data Management Policy, Frequently Asked Questions, Government of Canada 2022).
Sensitive data: information that must be safeguarded against unwarranted access or disclosure. Sensitive data may include: personal information; personal health information; educational records; customer records; financial information; criminal information; geographic information (e.g., detailed locations of endangered species); confidential personnel information; information that is deemed to be confidential; information entrusted to a person, organization or entity with the intent that it be kept private and access be controlled or restricted; or information that is protected by institutional policy from unauthorized access. Sensitive data includes any information relating to an identified or identifiable natural person, organization or entity. (Sensitive Data Toolkit for Researchers Part 1: Glossary of Terms for Sensitive Data used for Research Purposes, Portage/CARL 2020)
The Tri-Council Policy and its implementation
In March 2021, the Tri-Agencies released their Research Data Management Policy (https://science.gc.ca/site/science/en/interagency-research-funding/policies-and-guidelines/research-data-management/tri-agency-research-data-management-policy), which applies to all post-secondary institutions and research hospitals which are eligible to administer SSHRC, NSERC, or CIHR funds, and to all researchers holding grants from those agencies. In brief, the Tri-Agency Research Data Management Policy rests on three pillars with the following implementation schedules:
- Institutional Research Data Management (RDM) Strategies: “Each postsecondary institution and research hospital eligible to administer CIHR, NSERC or SSHRC funds is required to create an institutional RDM strategy and notify the agencies when it has been completed. The strategy must be made publicly available on the institution’s website, with contact information to which inquiries about the strategy can be directed” (section 3.1 of the Policy). These strategies must be completed by March 1, 2023.
- Data Management Plans: “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” (section 3.2 of the Policy). The initial funding opportunities requiring DMPs will be launched in the fall of 2022, and additional programs with this requirement will roll out over the following weeks and months.
- Data Deposit: “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.... The deposit must be made by time of publication” (section 3.3 of the Policy). This requirement will be implemented after the Tri-Agencies have reviewed the published institutional strategies and “in line with the readiness of the Canadian research community” (section 4 of the Policy).
Importance of research data and research data management at RRU
Royal Roads University recognizes data as an important research output and the importance of sound management practices for research data. The university also recognizes that best practices for data management are those that are consistent with legal and ethical obligations, as well as tri-agency requirements, including the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans – 2nd edition, the Tri-Agency Framework: Responsible Conduct of Research. The university commits to ensuring its research data management strategy supports and adopts those best practices.
In addition, Royal Roads University commits to ensuring that research embeds equitable, diverse, and inclusive practice into its design, data collection, analysis, and dissemination processes so that our research reflects a diverse population and intersectional needs. Our research serves a global community by seeking to uncover and addressing systemic issues related to equity, diversity, and inclusion that create barriers for members of equity-entitled groups. Our dissemination processes aim to make research data openly available where possible to promote equity in access to research for all. RRU’s commitments to uphold social justice extend to all aspects of the research endeavor, including research data management.
Royal Roads University’s research is characterized by practitioner orientation, a desire to develop solutions to current problems, and a commitment to sustainability, social innovation, social responsibility, and change. The university’s Strategic Research Plan 2020-2025 includes the following four goals: 1) advance, enable and support quality research; 2) expand the visibility, reach, and impact of RRU research; 3) identify and focus on priority challenges for research at Royal Roads; and 4) expand opportunities to conduct research into learning and teaching as it pertains to the Royal Roads Learning and Teaching Model (LTRM). In order to achieve these goals, the university notes the importance of, and connection to, sound data management practices as part of our research activities.
Indigenous data sovereignty
Royal Roads University’s Ethics Policy state that “In collaboration with Indigenous peoples, RRU seeks to be involved in research activity co-created for the benefit of Indigenous peoples. The relationships RRU maintains with Indigenous peoples and communities locally, nationally, and internationally are vitally important to the university. RRU therefore seeks to be proactive in meeting the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans, Chapter 9: Research Involving the First Nations, Inuit, and Métis Peoples of Canada and has established guidelines for the conduct of research, scholarship, evaluation, and creative endeavours that extend the commitment found in the Tri-Council Policy” (Royal Roads University, 2020). Any projects involving Indigenous peoples are reviewed through this lens by the RRU Research Ethics Board.
Royal Roads University recognizes that “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, where these practices exist, 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” (Tri-Agencies, n.d.).
Scope
This strategy applies to all RRU researchers, including faculty, librarians, students, and staff at RRU and covers the time period of March 1, 2023 through February 28, 2025. The approach is necessarily phased in development. The initial focus will be to ensure that Tri-Council-funded researchers have the tools, technologies, and service supports in place to facilitate and demonstrate appropriate data management practices. The services and supports optimized during the initial phase will be then be expanded to other researchers. Formal data management requirements will be developed and become part of the ethics review application process.
Oversight and review
This strategy comes under the purview of the Vice President Research and International and the Vice President Academic and Provost. Key stakeholder bodies for implementation of the strategy include the Research Office, Library, IT, Ethics Review, and the Research Advisory Committee. The Research Advisory Committee will monitor progress toward the goals biannually with formal summary report to the VPRI and VPA annually.
Goals and recommendations for RRU’s Data Management Strategy
1. Increase awareness
The Tri-Council policy pre-supposes that strategic institutional support for RDM involves effecting a significant cultural shift in research processes for institutions and researchers alike. To enable a successful cultural shift of this magnitude, communication and educational efforts via a multiplicity of formats and venues will be required over a generous time horizon. Moreover, the landscape of requirements, procedures, and tools continues to evolve as institutions engage with the Tri-Council policy, so the communication around these developments will be ongoing.
From the outset of the policy’s development, Tri-Council has explicitly advocated for inter-institutional cooperation between Research Offices, Libraries, and IT departments, acknowledging the disparate and shared expertise, positionality, and constituencies of these groups to support institutional capacity building in RDM. An important aspect of awareness raising will be to minimize the duplication and contradictions of efforts from these three areas by ensuring consistency and centralization of communication efforts where appropriate and achievable.
Recommended Actions:
- Develop a communication program with channels identified and prioritized by RRU researcher needs and funding profiles.
- Develop collaborative procedures and processes between the RRU Research Office, Library, IT Department, Ethics Office, and other university stakeholders that streamline researcher RDM support.
- Develop a data management plan section in the RRU Ethics review application process and form
- Stage the requirement for data management components to be part of the application process for Internal SSHRC grants, then Internal Research Grants, then all grant applications over 3 years
2. Enable data collection, researcher collaboration, data curation, and data preservation.
Alongside the development of the Tri-Council policy, the Tri-Council and various agencies have begun development, adoption, and assessment of technological tools and frameworks that are essential to enable the data lifecycle in the research process.
Research was formally incorporated into RRU’s Learning and Teaching Model as part of its 2018 revision. As research and pedagogy are, therefore, intrinsically linked in the matrix of RRU’s educational model, access to technological tools that are foundational to good data practice should be equitably available to support the spectrum of research and researchers within the RRU community.
Recommended Actions:
- Establish needs and priorities to budget for software/technological tools that help enable good RDM learning and practice
- Develop streamlined procedures and processes for software/technological tool access and support that promote the adoption of secure, appropriate, and sustainable RDM technologies.
- Develop an education and training program for RRU researchers for effective use of adopted data collection, storage, and repository technologies
- Establish a feedback mechanism to track user satisfaction with existing technological tools and access to them, as well as suggestion for new and replacement technological tools in keeping with the fluidity of the technological marketplace.
3. Build expertise and support for data stewardship and research data management.
In response to the development of the Tri-Council policy and in coordination with and by the Tri-Council, Research, Library, and IT groups within the Canadian post-secondary sector have been taking a networked approach to making broadly available a collaborative regime of information, experience, and expertise sharing over the past few years.
Members of the Research Office, Library, and IT have been attending various of these sessions to develop a foundational understanding of the requirements and impact for the RRU community. As mentioned in the introduction, some first steps regarding RDM support have resulted from these opportunities. Faculty have accessed support where RDM has come up for them on an ad hoc basis. The progressive development of a comprehensive program of education and support for RDM that is similarly thoughtfully anticipatory rather than reactive is also necessitated to underpin the RDM cultural shift.
Recommended Actions:
- Encourage researchers already familiar with RDM practices to act as resources and champions of RDM
- Create a plan of coordinated support delivery by Library, Research Office, and IT that also identifies and prioritizes staffing needs.
- Create a collection of RRU Research RDM documents, such as DMPs, that can act as a bank of local exemplar material.