Research data management

Introduction

The purpose of this Research Data Management Strategy is to make explicit the commitments Simon Fraser University (SFU) will provide to support its researchers in complying with the Tri-Agency Research Data Management Policy. Secondly, it articulates SFU’s goals and objectives for improving ongoing support for Research Data Management as part of SFU’s 2023-2028 Strategic Research Plan. A corollary of these two objectives is that the strategy will form the basis for researcher-facing and researcher-focused documentation describing where researchers can get support for managing data generated as part of their research, regardless of where the funding for that research comes from. 

This strategy is intended to evolve so that it remains relevant to SFU researchers. While it will be reviewed annually, the SFU Research Data Management Strategy Working Group welcomes feedback at any time.

 

Definitions

• Research Data Management (RDM) encompasses the processes applied throughout the lifecycle of a research project to guide the collection, documentation, storage, sharing and preservation of data created during the project.
• Tri-Agencies: The Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Social Sciences and Humanities Research Council of Canada (SSHRC) are federal granting agencies that promote and support research, research training, knowledge transfer and innovation within Canada. Also known as the Tri-Council.
• PI: The principal investigator in a research project.
• Data Management Plan (DMP): A written document outlining how data for a research project will be collected, documented, formatted, protected and preserved. DMPs may also describe whether data will be shared, where it will be deposited for access by others, and whether and when it will be destroyed.
• FAIR: A set of principles to improve the findability, accessibility, interoperability and re-use of research data.
• CARE: A set of principles for advancing Indigenous innovation and self-determination through collective benefit, authority to control, responsibility and ethics.
• OCAP®: A set of principles specific to First Nations data sovereignty defining ownership, control, access and possession.
• TCPS2: The Tri-Agencies policy statement on Ethical Conduct for Research Involving Humans.
• STEM: Science, Technology, Engineering and Math.

 

Responsible authority

SFU’s Office of the Vice President Research and Innovation is responsible for the creation and review of this strategy. 

 

Background

In response to the Tri-Agency directive, SFU’s Vice President Research and Innovation (VPRI) established a Research Data Management Strategy Working Group comprised of representatives from across the university, including: the Associate Vice-President Research (AVPR); Chief Information Officer; Executive Director, Research Operations; Director, Research Intelligence; Associate Director, Research Computing, IT Services: Director, Strategic Services, IT Services; Research Data Services Librarian; and (Chair) Associate Dean of Libraries, Digital Strategy. 

During the development of this strategy, the working group conducted four focus groups with SFU researchers (one each for researchers who recently received funding from one of the Tri-Agencies, and a separate focus group for Indigenous researchers). It also hosted two town halls open to all researchers. Additionally, the working group leveraged expertise from the Research Data Alliance Canada (formerly Portage) and its network of research data management specialists.

 

Scope 

As described above, the scope of this strategy encompasses the types of support SFU will provide recipients of funding from Canada’s Tri-Agencies, with an emphasis on compliance with the funder’s specific RDM requirements. However, this support is not limited to recipients of Tri-Agencies' funding, but will be available to all researchers at SFU.

 

Principles

This strategy is predicated on the following principles:

1. The university will advise researchers on mechanisms for RDM activities throughout the research lifecycle, including storage, backup, registration, data security, data deposit, data sharing, and long-term preservation of research data for current and future access during and after completion of research projects. It will also provide, where possible, infrastructure and platforms to support these activities.
2. The university will provide training, support, advice and, where appropriate, guidelines and templates for data management plans. 
3. Research data associated with human participants must comply with TCPS2 and SFU’s policy on human participants research. 
4. Support for research involving First Nations, Metis and Inuit Peoples must include recognition that they have control over how research data is collected with regards to themselves and their communities, and that they own and control how the data will be used, stored, accessed and preserved. The university will support mechanisms and processes to ensure community control over collection, storage, access, and preservation of their research data, data management plans and other aspects of RDM should reflect this data ownership.
5. PIs and other researchers are required to make their research data openly available where ethical, legal, and commercial requirements allow, and in accordance with the standards of their disciplines. Data generated by or about Indigenous communities will only be shared according to the wishes of those communities.
6. The PI, or their designate, is responsible for ensuring access to their research data complies with federal and provincial privacy legislation, and that all data users with access to research data are made aware of these requirements
7. PIs and other researchers must comply with SFU’s policy on the Responsible Conduct of Research, whose principles include complete and accurate record keeping.

 

Existing support for RDM at SFU

SFU currently supports RDM via the following campus units:

 

Strategy and roadmap

Based on consultation with SFU researchers and support units, the university has developed the following RDM strategy defining six high-level goals that will improve the ability of SFU researchers to meet the expectations of the Tri-Agencies, and that will strengthen support for RDM at SFU in general.

Each goal identifies measurable objectives the university will work towards through collaboration with external funders, central support units, faculties, departments and researchers.

 

Goal 1: Raise awareness of RDM and research data stewardship

• Provide a researcher-focused “Start Here” hub to help researchers determine what they need and where they can get support. Clearly articulate roles in RDM, e.g. central units vs. faculty/department vs. research teams.
• Ensure RDM is included in new faculty and grad student orientation programs.
• Develop and promote clear policies and practices around disposition of data with explicit retention requirements (in other words, if data is supposed to be destroyed at a specific time, knowing when that is, and what constitutes “destroying”). These policies may relate to SFU’s general data classification standards.
• Streamline and consolidate ethics processes, grant requirements, creation of Data Management Plans, and related administrative research and approval processes as they pertain to funder requirements and general RDM practices.

 

Goal 2: Indigenous data sovereignty

• Recognize that there is a profound tension between western and Indigenous ways of knowing. Researchers must have undertaken Indigenous-led training (for example, OCAP® before undertaking research about or with First Nations, or more broadly, training in the CARE Principles for Indigenous Data Governance). Details around "ownership & control” should be included in agreements (e.g. contractually communities can demand deletion, and that all use of data requires permission). 
• The university needs to be receptive to data access agreements that assert community sovereignty over data.
• When asked, the university will commit to storing such data as desired by the communities that own it.
• Recognize that research involves practices, processes, and protocols that are living and continuously regenerated in relation to land and community.
• Recognize that “data” sharing, or sharing what is learned by observation and thought, happens in the context of teaching and guiding others. It is not necessarily separated or abstracted for “re-use”.
• Work with First Nations, Inuit and Métis researchers and communities to develop processes that support Indigenous data sovereignty through systems reinforcing responsibility, reciprocity and accountability.
• Sponsor access to external Indigenous data sovereignty training and resources for researchers, support staff, service providers and research partners.
• Specifically include First Nations, Inuit and Métis research in planning for funding RDM.

 

Goal 3: Expand RDM training and support

• Provide training on RDM best practices throughout the research data lifecycle, based on the FAIR principles (Findable, Accessible, Interoperable and Reproducible).
• Provide training on and support for writing effective Data Management Plans.
• Provide basic and intermediate training on commonly used RDM tools such as data-oriented scripting languages, lab notebooks and de-identification/anonymization tools.
• Provide specialized teaching and training support in specific aspects of RDM for graduate students, post-doctoral fellows and staff who work as lab or data managers.
• Provide technical support in establishing stable and robust data collection pipelines from external platforms (e.g. REDCap) into SFU storage and computing infrastructure.
• Assist researchers in connecting with resources relevant to RDM such as ethics review, grant facilitation, and funding agency guidelines and policies.
• Provide access to training on ethics and privacy issues throughout the research data lifecycle.

 

Goal 4: Facilitate access to RDM tools and platforms

• Work toward supporting data storage needs across all disciplines, from STEM to humanities, including providing dependable and transparent solutions for large data storage. Ensure this storage is accessible to compute resources required to analyze it.
• Provide clear advice on when public cloud storage and other shared tools (e.g. Sharepoint, Google Drive) can be used to store and process data.
• For software applications used by researchers in multiple faculties, develop a mechanism for funding licenses and support staff at the campus level (e.g. GIS software, electronic lab notebooks)
• Enable SFU researchers to collaborate with peers outside SFU (within British Columbia, Canada, and internationally) securely and easily.
• For projects that work with sensitive data (e.g., involving any of the categories governed by TCPS2, Indigenous data, or data with legal access or intellectual property constraints), support secure storage where controlled access can be given to external partners.This applies to small and large scale data. 
• For data created from within Indigenous communities, ensure appropriate (e.g., OCAP® or CARE-compliant) infrastructure for community stewardship of data.

 

Goal 5: Develop RDM services through collaboration across campus

• Coordinate all SFU units who support research (Research Ethics, Research Computing Group, SFU Library) to ensure research excellence.
• Adopt consistent language/terminology for RDM activities across the university.
• Allocate and develop appropriate staff resources to RDM.

 

Goal 6: Formalize RDM practices

• Recognize Indigenous data sovereignty as a fundamental principle of RDM support at SFU.
• Establish required base funding for SFU units providing RDM support.
• Develop sustainable financial support for short-term and long-term data storage needs.
• Encourage and support consistency and standardization in enforcing data access agreements.

 

Related documents

• SFU’s Walk This Path With Us
• SFU’s Strategic Research Plan
• SFU’s Intellectual Property Policy
• SFU’s Responsible Conduct of Research Policy
• OCAP® training
• SFU’s Data Governance Policy (under development)
• Tri-Agencies' TCPS2