Introduction

Canada and many other developed countries are establishing Research Data Management requirements across a range of scholarly disciplines. Barriers to data management, data preservation, and data sharing, which you’ll learn about in future chapters, are being addressed through the recommendation and use of community standards, such as established metadata, data documentation, and disciplinary repositories.

As you’ve now learned, 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 Canada’s federal research funding agencies. In March 2021, the agencies released the Tri-Agency Research Data Management Policy to gradually begin Data Management Plan (DMP) requirements with selected grant programs. Through these programs, the agencies actively encourage research institutions to provide their researchers with an environment that enables robust research data stewardship and curation practices and to deliver support for managing and depositing research data in secure, curated, and accessible repositories. But even before this policy was released, visionary leaders and organizations, especially Canadian academic libraries, were carrying out grassroots data management awareness-raising initiatives and efforts.

Over the past decade, academic libraries in Canada have been working collaboratively to deliver RDM support to their communities (Steeleworthy, 2014; Liss, 2018). Collaborations between academic libraries and the broader research community address the central challenges of infrastructure, services, and training through initiatives such as the Portage Network (Portage) and Research Data Canada (RDC). Both these entities are now part of the Digital Research Alliance of Canada (Alliance).

In this chapter, we provide a brief history and overview of Canadian RDM, which began with grassroots initiatives before evolving into larger national efforts. The chapter updates and expands on previous work from a few years ago (Barsky et al., 2017).

A Brief History of Research Data Management in Canada

Since the end of the 20th century, academic libraries have discussed and advocated for centralized data archiving and data discovery services and improved access to research data in Canada. However, in a country with a relatively small and geographically dispersed population, centralization is challenging. In the early stages of RDM, Canadian academic librarians succeeded in strengthening the social sciences and, especially, government data collections available to researchers for secondary analysis purposes. The academic libraries also contributed to the development of a national RDM community of practice. By leveraging the close ties between researchers and data librarians and specialists, the network of data stewards was not only able to contribute collaboratively to the development of RDM tools and infrastructures, but was also able to make new resources available to local researchers through data education, consultation, and data deposit services.

Providing Access to Statistics Canada Data

The Data Liberation Initiative (DLI), a subscription-based service providing access to Statistics Canada data, is an excellent early example of how data management collaboration can help build and maintain data delivery infrastructure and train data reference experts. The DLI program began in 1996 as a result of consultations between Statistics Canada, the Canadian Association of Research Libraries (CARL), and the Humanities and Social Sciences Federation of Canada (Boyko & Watkins, 2011). The DLI was founded in response to both the high costs of Statistics Canada’s public use microdata files and the lack of data infrastructure at Canadian universities to provide access to these data (Humphrey, 2005). Due to budget cuts in the 1980s, the public use microdata files were priced on a full cost recovery basis, so only the most well-funded researchers could afford them.

The DLI collection includes thousands of data files for hundreds of survey series. Its size and the demand from researchers have directly contributed to the growth of the library data infrastructure needed to manage and preserve access to these data. When the DLI was formed, there was little expertise in many libraries to support data services. However, Statistics Canada required a point of contact within the library who would be responsible for distributing data to end-users. So libraries had to develop staff expertise through DLI training activities (Humphrey, 2005). Training programs under the DLI have led to the development of skilled library professionals and a national academic data community. The need to support the DLI program also led to the development of local initiatives to provide or improve data delivery to data specialists and users. These data delivery systems include <odesi> and Abacus in Ontario and BC, as well as systems in the Western provinces and Quebec (Gray and Hill, 2016). Sources cited for this chapter provide further in-depth reading.

National Research Data Strategy in the Early 2000s 

In the 2000s, Hackett (2001) identified a wide range of issues related to Canadian research data acquisition, preservation, and access. Difficulty locating and accessing previously collected Canadian data was a key issue. This difficulty was due to high costs, a lack of a central resource directory or depository service, and a lack of a national body to set standards and provide guidance, funding, and infrastructure (Hackett, 2001). There were some exceptions. In the disciplines of physical sciences and genetics, there was already an international culture of data sharing through disciplinary repositories. The importance of data sharing to scientific practice in these disciplines led to the establishment of some Canadian repositories that did not need a policy. Examples of domain repositories include the Polar Data Catalogue (a project of the Canadian Cryospheric Information Network), the Canadian Astronomy Data Centre (an initiative of the Canadian Advanced Network for Astronomical Research), and CBRAIN (an initiative of the McGill Centre for Integrative Neuroscience, MCIN). However, the lack of interdisciplinary coordinated data curation and metadata standards still remains a problem.

For the last twenty years, the federal government has consulted with various research communities, including the National Library of Canada and the National Archives of Canada (now Library and Archives Canada), about the benefits and challenges of RDM. In 2005, the Canadian government released the National Consultation on Access to Scientific Research Data (NCASR) report. This was the cumulative work of an expert task force of more than seventy Canadian leaders in the fields of research, administration, and libraries, among others (Strong & Leach, 2005). The report included a recommendation for the development of a national steering body to form a national data archive and coordinate data management. It also included a recommendation for project funding across sectors in Canada. However, the approach ultimately failed to gain political support (Humphrey, 2012a).

Without a national steering body or resources from the federal government, academic libraries had to forge an alternative path. They built institutional and cross-institutional repositories for disseminating and archiving data, particularly long-tail research data, which is the large number of relatively small datasets produced across many disciplines (Heidorn, 2008). These long-tail datasets are diverse and are often difficult to manage (Cooper et al., 2021). Libraries had expertise in archiving and preserving research output and a history of engagement in solutions for access to and dissemination of licensed data through their work with the DLI program. They were recognized as being well positioned to take on the challenge of managing long-tail datasets.

A Grassroots Approach to Canadian RDM Infrastructure Beginning in the 2010s 

In 2008, a Research Data Strategy Working Group was formed to implement the recommendations made by the NCASR. It was a task force appointed by the National Research Council of Canada with over seventy Canadian leaders in scientific research. At the same time, CARL, a group representing Canada’s largest university libraries and two federal institutions, had started participating in various national conversations about the future of Canadian digital research infrastructure. CARL gradually made the case for RDM, high-performance computing (represented by Compute Canada), and high-speed research network (represented by Canada’s National Research and Education Network (CANARIE)) to be considered equally important pillars for such an infrastructure (Humphrey, 2012b).

In 2011, CARL and the Research Data Strategy Working Group held a Research Data Summit, which resulted in the formation of RDC in 2012. Since 2014, the project has been supported by CANARIE, a not-for-profit organization whose mission is to operate the national backbone network of Canada’s research and education network. RDC has helped form committees and launch technical projects, and it has partnered with international organizations to advance research data infrastructure and expertise. RDC coordinated the National Data Services Framework (NDSF) Summit, first held in 2017 and again in 2019–2022. The NDSF Summit brought together RDM groups and experts, such as funding agency representatives, disciplinary data repository curators, and data librarians, from around the country. They discussed and raised awareness on the importance of prioritizing a nationally coordinated RDM infrastructure and services for the future of Canadian digital research infrastructure (Attendees of the NDSF Summit, 2019).

As part of CARL’s efforts to enhance library readiness for research data support services, an RDM course was offered to libraries in early 2013. In the wake of the course, a forum called the Canadian Community of Practice for Research Data Management was created for ongoing dialogue related to RDM activities in Canada.

CARL directors created more formal relationships with the organizations providing Canadian libraries with research computing infrastructure, namely CANARIE, Compute Canada (high-performance computing), Canadian University Council of Chief Information Officers (CUCCIO), and the National Science Library. A one-year pilot project, known as project ARC, was launched in 2014 to foster a community of practice for research data in Canada. The pilot resulted in the creation of a network of experts, including academic librarians, system and code developers, and data service providers. Project ARC was a success and became the Portage Network in 2015, with the mission of providing stewardship for Canadian researchers through a network of experts across the country. As of April 1, 2021, Portage became part of the Alliance. The RDC subsequently amalgamated with the Alliance in the spring of 2022. Currently, the Alliance provides an integrated digital research infrastructure and service for all academic researchers across Canada.

National RDM Policy in the Late 2010s and Early 2020s

By 2016, following in the steps of other countries, Canada’s federal research funding agencies began developing an RDM policy by releasing a “Statement of Principles on Digital Data Management.” This statement proposed expectations for researchers, research communities, research institutions, and funders to collaborate on building a robust and open environment for Canadian research data.

In 2018, the agencies announced a draft RDM policy and started a public consultation. The agencies received over one hundred submissions of feedback from a variety of experts on Indigenous research, monitoring and compliance, and each of the three pillars of implementation detailed in the policy: RDM strategy, DMP, and data deposit. In March 2021, the agencies formally announced their Tri-Agency Research Data Management Policy: promoting excellence in RDM within the Canadian research community, while recognizing the diverse context of disciplinary scientific inquiry, legal and ethical constraints, institutional capacities, and Indigenous communities’ self-determination and engagement. As a result of this long-anticipated announcement, the policy established an RDM support mandate within research institutions.

The policy requires each Canadian institution to submit an RDM strategy so research funders can assess readiness across institutions. Developing an RDM strategy allows institutions to think through local gaps and develop solutions, and it encourages collaboration with other institutions. The release of the Tri-Agency RDM Policy coincided with the establishment of the Alliance, a national not-for-profit organization whose goal is to harmonize and improve access to digital tools and services for Canadian researchers. A key vision of the Alliance is to build a network of collaborative national RDM services in three areas: advanced research computing, research data management, and research software.

National Collaboration: From Portage Network to the Alliance

Origin and Current Organization

Portage was launched by CARL in 2015 in response to Canada’s Action Plan on Open Government and was a precursor to the Alliance. Portage began as a community-based national network of RDM services and support that leveraged the existing national and regional networks of Canadian academic libraries. It was envisioned by dedicated RDM advocates and leaders (Humphrey, 2012b). The initial concept of the network was discussed during an informal meeting at a CARL conference in 2013.

In 2014, CARL launched a one-year community of practice pilot project, called project ARC. Building on the success of the pilot, a library-based RDM network of experts (NOE) was framed, and operational models and governance were established over the following two years (September 2015–August 2017 ) (Humphrey, Shearer, and Whitehead, 2016). Since then, the NOE has developed and made available numerous RDM-related training resources, guidelines, and templates aligned with the Canadian funders’ requirements to support the research community and help data stewards. The NOE strengthened the connections among existing regional data repository infrastructures that used the Dataverse software, which ultimately led to the formal partnerships and the launch of the national service Borealis Dataverse Repository (Borealis). It also coordinated the development of a Data Management Plan Assistant (DMP Assistant) web-based application, a repository known as the Federated Research Data Repository (FRDR), and Lunaris, a data discovery platform.

After joining the Alliance in April 2021, the Portage NOE community became part of the Alliance RDM team. The future governance and operations of the NOE is currently under discussion. The NOE has grown to over 140 experts from 60 institutions across Canada. It collaborates with a broad range of interested parties and partners locally, nationally, and internationally to develop services and infrastructure so academic researchers can access the support they need for RDM (Humphrey, 2020). At the time of writing, the NOE includes the following nine active groups:

1. 1. 1. Curation Expert Group (CEG)
      2. Data Management Planning Expert Group (DMPEG)
      3. Data Repositories Expert Group (DREG)
      4. Dataverse North Expert Group (Dataverse North)
      5. Discovery and Metadata Expert Group (DMEG)
      6. Preservation Expert Group (PEG)
      7. Research Intelligence Expert Group (RIEG)
      8. Sensitive Data Expert Group (SDEG)
      9. National Training Expert Group (NTEG)

The efforts of the RDM community of experts have continued to advance through the efforts of the Alliance RDM team to develop shared resources, expertise, and training materials. The outputs and publications of each expert group are openly available on the Alliance website. Below are highlights of the major accomplishments of the community.

Infrastructures, Services, and Tools

Canada’s current network of local and regional collaborations makes it easier and more efficient to foster national data management infrastructure, services, and tools. Data specialists and librarians from Canadian academic institutions and staff from the Alliance RDM have contributed to the development and ongoing support of the RDM infrastructures and tools mentioned in this chapter. For example, the Dataverse North Working Group was formed to bring the Dataverse repository providers and librarians in Canada together to coordinate and discuss local and national training, support services, outreach strategies, promotions, and infrastructure development and needs.

An even bigger, multi-functional data management infrastructure, FRDR, was developed with the Alliance RDM as its service provider and Compute Canada as its hardware and infrastructure host. It also had support from several expert groups, including the DMEG, PEG, and CEG. Today, FRDR provides a wide range of RDM services to Canadian institutions, organizations, and researchers, including data discovery, storage, preservation, and curation. All Canadian researchers are eligible to deposit open data in FRDR and obtain a Digital Object Identifier (DOI) to uniquely identify their dataset and generate a permanent web address. FRDR also has a large data ingest capacity and dedicated curation support.

FRDR originally included functionality to index data from other Canadian data repositories and make their data discoverable. However, in 2022 the decision was made to develop this capability as a separate service, named Lunaris. Lunaris is a bilingual platform that provides a single place to search for data from FRDR and other sources. Lunaris does not host data, it instead provides links to external repositories where users can go to download data.

Preservation of research data is essential to ensure that it remains accessible and usable in the long term. However, Canada still lacks a robust research data preservation plan or strategy. PEG was created to improve Portage’s capability in developing infrastructure and best practices for preserving research data and metadata. This includes working with relevant parnters on software development projects that add platforms and preservation services to the RDM infrastructure in Canada. PEG has been collaborating with other expert groups to increase awareness of preservation issues, liaising with FRDR and Borealis repositories on preservation functionality in repositories, and working with FRDR, SciNet, Scholars Portal, and University of Toronto Libraries on a preservation pipeline project to facilitate researcher access to a robust long-term digital preservation environments.

Initially, the online DMP Assistant tool was hosted and overseen by the University of Alberta, but later responsibility for the tool has moved to the Alliance RDM. The Tri-Agency RDM Policy highlights the importance of Data Management Plans in the research process and defines a DMP as one of three core pillars. Canada’s three federal research funding agencies also announced that a DMP would soon become a requirement and not a recommendation for all Canadian researchers seeking public funding. Before this announcement, the use of DMPs was already a standard requirement for American and European research funding applications. Developed in partnership with the agencies, the DMP Assistant offers step-by-step advice for developing a Data Management Plan. In addition, the NOEs developed several bilingual documents, including guides describing how to:

• create an effective Data Management Plan,
• customize the DMP content and appearance.

There are also a number of discipline-specific DMP exemplars and templates highlighting best practices in DMPs for various disciplines within the training resources area of the Alliance website.

Best Practices, Standards, and Guidance

As a national collaborative network of experts, the Alliance RDM fostered a coordinated framework of existing, disperse infrastructure and online tools: DMP Assistant, Scholars Portal Dataverse (rebranded to Borealis, the Canadian Dataverse Repository in 2022), FRDR, and Lunaris. It also developed guidelines and recommendations on best RDM practices in close partnership with the three federal research funding agencies. The guidelines and documentation developed by the Alliance RDM working groups can be found on Zenodo and include:

• A Guide to Curating Dataverse Datasets, developed by the Dataverse Curation Guide Working Group. This guide outlines best practices for preparing datasets for publication in the Dataverse repository.
• A Dataverse North Metadata Best Practices Guide, developed and continuously updated by the Dataverse North Working Group. This guide provides an overview of metadata best practices and offers examples from various disciplines, including geospatial data.
• Appraisal Guidance for the Preservation of Research Data, developed by the Appraisal for Preservation Working Group. The guide addresses the needs of data creators and curators to evaluate and select research data for long term access.
• Sensitive Data Toolkit for Researchers, published in 2020 and continuously updated by the SDEG. The 3-part guide includes a glossary of terms related to sensitive data, a data risk matrix, and a sample consent language. We’ve listed and provided a link to each part of the guide in the in following textbox. The guide has been widely adopted by Canadian institutions.

Network and Community Building

Besides offering RDM infrastructure and best practices, the Alliance RDM aimed to break down social, cultural, and technological barriers associated with an RDM ecosystem (Humphrey 2012b). The Alliance RDM has, in fact, cultivated a variety of networks and communities in recent years.

Members of the Alliance RDM DREG were involved in the development of the DataCite Canada Consortium, which was launched in January 2020 with Alliance RDM as the operating lead, Canadian Research Knowledge Network as the administrative lead, and funding from the Alliance. More than fifty consortium institutions worked together to develop a governance and funding structure and to offer DOI minting services and metadata registration through DataCite to all of their members. The DataCite Canada consortium is a significant achievement for Canadian institutions. It allows us to collaboratively manage the national pool of DOIs for a variety of research repositories and other digital assets while having a stable, shared, and collaborative pricing scenario for various tiers of research institutions in Canada. Also, it allows a community of practice to resolve technical issues and initiate innovative DOI projects within Canada.

To help Canadian research data repositories align their practices with global standards, the DREG adjudicated Alliance RDM funding for a cohort of CoreTrustSeal (CTS) certification applicants. A total of 12 repositories made up the first cohort of applicants, including several Borealis institutional repositories seeking improvement of current practices. CTS certification has a lengthy process before it is successful. For the benefit of applicants, DREG organizes and oversees the writing and reading groups and assists applicants with the peer-review process.

CEG is dedicated to identifying, evaluating, and promoting best practices in curating data. This includes techniques, methods, and tools that can better prepare data and metadata, improve data quality, and ultimately facilitate data dissemination and reuse. It also fills in the need for training and supporting a new generation of data curators. Community building and networking are key aspects of the expert group’s approaches. In 2019, CEG hosted the first Canadian Data Curation Forum, in partnership with McMaster University and with funding from SSHRC. A key goal of this forum was to establish a national community of practice among data stewards, librarians, data service providers, and system developers. The Forum’s program included a variety of keynote talks, discussions, and workshops with the objectives of facilitating communication and collaboration around data curation practices and standards and developing skill and training resources. The Forum was a huge success and achieved its goal of establishing a network of data curators who have met regularly with the CEG since then to discuss and update each other on data curation, current issues, and development.

Research and Training

To keep up with a constantly changing environment, the Alliance RDM built a research intelligence group and a training team to monitor gaps in RDM areas and to provide timely training to the community and its broader groups.

RIEG prioritizes ongoing surveillance of RDM-related topics and mandates. RIEG guides the development of best RDM practices in Canada and informs relevant communities about existing and arising issues in related policies and practices. It maintains an RDM Roadmap of Research Priorities to identify gaps in RDM knowledge, skills, services, and policies. RIEG also conducts independent studies and surveys and analyzes the results to provide evidence-based recommendations to Alliance RDM. In 2016, it established the Canadian RDM Survey Consortium and developed a common survey instrument. Fifteen universities have since used the instrument to survey researchers in their institutions to understand their RDM practices and attitudes. In 2019, RIEG conducted two surveys on Canadian institutions, measuring their RDM capacity and strategy development status, before the Tri-Agency RDM Policy was announced. The survey results provided evidence of existing RDM initiatives and services and voiced the institutions’ priorities and needs for further RDM support areas.

As RDM continues to evolve, it is crucial that researchers, data professionals, and others involved with RDM have the information and training they need to stay up to date with the latest developments and best practices. The development of RDM training resources has been one of the core activities of the Alliance RDM. Since 2017, the Alliance RDM NTEG has developed RDM training material. The NTEG oversees a range of specific projects that collaboratively develop and deliver training and resources to support RDM skill development across Canada. Immediately following the announcement of the Tri-Agency RDM Policy, NTEG coordinated a series of well-attended workshops on the most important aspects of the policy. The workshops helped researchers and others understand the policy requirements and raise awareness of existing tools and resources that could support them in developing DMP and institutional RDM strategies.

Data Repository Services in Canadian Libraries

Just as a network of experts, training, and support has been established nationally, various university libraries have also developed a Canadian data repository service. Most notably, the Dataverse repository has been a key resource. The Dataverse repository is an open source software, developed by Harvard’s Institute for Quantitative Social Science, to store, share, cite, preserve, discover, and analyze research data. Its open source nature enables institutions to host their own installations of the Dataverse software and offer a customized solution tailored to their own community needs.

There has been an evolution from local and regional installations of Dataverse software in Canada, including Scholars Portal Dataverse and other institutions and regions, to a national service called Borealis: Scholars Portal Dataverse first began offering the service outside of the Ontario Council of University Libraries in 2019, an official national service was offered in 2020 with agreements with the four regional academic library consortia, and the new brand Borealis was launched in 2022. The shared national installation also provides the opportunity for local branding and for providing shared training resources to users. During this transition, a Dataverse North expert group developed training resources, provided support and outreach, and developed promotion strategies. This is an important factor, as Canadian universities often prefer to store data on locally hosted servers.

In the Dataverse platform, data can be deposited into Dataverse collections that are part of a larger network. A Dataverse collection is a container for datasets (research data, code, documentation, and metadata) and can be set up for an individual researcher, department, journal, or organization. As an example, a researcher can deposit data into their institutional Dataverse collection, which is a part of the larger Borealis repository. Researchers and their collaborators can create their own accounts and deposit their data into an institutional collection (defined by their affiliation) or into research project collections, if available. Librarians and data stewards can also curate data contributions and handle data submissions on behalf of researchers. The Dataverse software is quite flexible in this regard. It is possible to apply institutional or project branding to Dataverse collections and sub-collections.

The Dataverse repository software also provides data analysis functionality in the browser; users do not need to download the data files in order to interact with them. The tabular data files that are uploaded to the system can be analyzed using the integrated web-based data analysis and visualization tool. Dataverse software can also be integrated with other library resources for improved discovery. For instance, since all partners of UBC Abacus Dataverse (libraries at the University of Victoria, University of Northern British Columbia, and Simon Fraser University) use ProQuest Summon as a discovery search engine, the Dataverse collections corresponding to their libraries are accessible through the specific Open Archives Initiative (OAI) protocol feeds. Each OAI feed includes all data from partner institutions and appropriate licensed data for that school. Through improved discovery (especially the assignment of DOIs for research datasets), curated data could be easily accessed and reused by researchers (e.g., in ORCID, Google, DataCite, Google Data Search, Crossref, and other services), thereby enhancing citations and improving research metrics for individuals and institutions.

Dataverse repository software has proven to be a flexible platform that can support many models for library RDM services in Canada. It offers a range of features that may improve data discoverability and access. It also provides excellent data management for preservation. However, Dataverse software is not a fully featured digital preservation system (although the national Borealis repository does support bit-level digital preservation, which is explained in the chapter, “Digital Preservation of Research Data,” and in the Borealis Preservation Plan. The repository is format-agnostic and accepts all types of files, not just tabular data.

The Ontario Council of University Libraries sponsored work by Artefactual to develop a technical integration between the Dataverse software and Archivematica, a robust, open source tool for processing digital objects for preservation and access. This preservation processing tool could be used in conjunction with the established Borealis service or any Dataverse installation (with Archivematica version 1.8+ and Dataverse software version 4.8.6+).  

Support for RDM in Canada has been a national focus. Historically and currently, regions and communities have faced issues related to support and infrastructure based on their own networks, regional or provincial funding and participation in consortium decisions by region.

Indigenous Data Sovereignty

Many of the initiatives and developments that we have mentioned in this chapter, and others that will be referenced throughout this textbook, have occurred without considering Indigenous Peoples and their data or redressing historical injustices. In fact, there has been a long history of mistreatment and neglect of Indigenous communities in Canadian research. While the Tri-Agency RDM Policy now explicitly addresses Indigenous data considerations, and Indigenous data experts are also included in the Sensitive Data Expert Group, we encourage the Alliance RDM team to address these issues more comprehensively in the near future.

First ‘Nations advocates and academics have responded to these gaps. For example, the First Nations Information Governance Centre (FNIGC) was incorporated as a nonprofit in 2010 to serve First Nations in data sovereignty, with work encompassing research, training, capacity building, and data collection. Their work dates back to 1996, when the Assembly of First Nations formed a National Steering Committee with the mandate of creating a national First Nations Health Survey (the First Nations Regional Longitudinal Health Survey), following Canada’s decision to exclude the on-reserve population from major longitudinal data collection projects. In 1998, the committee established the principles of OCAP® (standing for ownership, control, access and possession) as a tool and standard for collecting and managing First Nations data. For more on OCAP® see the chapter, “Indigenous Data Sovereignty.”

Regional Efforts

Across Canada, institutions have taken individual approaches on developing and expanding RDM services depending on their size, available resources (human resources and infrastructure), and research focus. College and university librarians and specialists are key members of the institutional RDM working groups and committees. They are involved in developing institutional RDM policies and strategies.

Many institutions across Canada have participated in surveys of RDM practices and needs that were based on a common survey instrument developed by librarians at the University of Toronto in 2015. The survey instrument was subsequently adapted with some modifications by many institutions across the country. This survey led to a richer understanding of disciplinary RDM practices and of local and national RDM needs, and it helped researchers become aware of RDM best practices (Cheung, et al., 2022) .

Courses on RDM have been taught at library schools across Canada. As described earlier, regions have adapted Dataverse repository software locally and, in many cases, nationally. All regions had representation on the Alliance RDM committees. Some schools responded to the need to provide RDM support with the development of RDM librarian positions or library roles. Below we describe regional initiatives highlighting unique services and areas of focus.

RDM in the Atlantic region

CAAL/CBPA (the Council of Atlantic Academic Libraries/Conseil des bibliothèques postsecondaires de l’Atlantique, formerly CAUL-CBUA) is the network of public university and college libraries in the Atlantic region. CAAL/CBPA has focused on building and coordinating digital preservation activities in the region. The Digital Preservation and Stewardship Committee (DPSC) was formed in 2013. It later expanded its work on building and developing RDM services on a broad scale to align its work with the national vision. The most recent initiative involves the 2020 CAAL/CBPA Innovation Grant that enables a series of RDM workshops to be delivered and streamed across Atlantic institutions, with DPSC members taking the lead in organizing and conducting the workshops. The events are called Atlantic RDM days, and they are conducted in English and French. These workshops are important to colleges and universities that do not have the resources to support RDM at the institutional level but must still comply with the Tri-Agency RDM Policy and promote RDM best practices within their research community.

In 2015, Dalhousie University was one of the first Atlantic research institutions to start building an RDM team, which included many partners across the institution (Office of Research Services, Academic Technology Services, and Dalhousie University Libraries). Dalhousie University was one of the first Canadian institutions to develop and publish an RDM strategy, as required by the Tri-Agency RDM Policy. Dalhousie University now offers an RDM course entitled “Managing Research Data.”

Several Atlantic research institutions have joined the national Borealis repository to provide data archiving services to their local research community. Others have agreed to maintain their own instances of the Dataverse repository installed on local institutional servers. This is due to the availability of local institutional resources to maintain and keep the repository up to date. For instance, since 2018, UNB Libraries at the University of New Brunswick have hosted a local Dataverse repository. This institutional data repository is hosted and maintained independently by the UNB Libraries through the collaborative work of the Library Systems team and the Libraries’ RDM Services Committee. Like other Canadian institutions, all research universities in the Atlantic region have access to the national data archiving infrastructure, FRDR, available through the Alliance’s website.

RDM in Quebec

Since the 1960s, academic libraries in Quebec have collaborated under le Bureau de la Coopération Interuniversitaire (BCI), formerly known as la Conférence des Recteurs et des Principaux des Universités du Québec (CREPUQ). In 1967, le Comité de coordination des bibliothèques was created. A few years later, it became le Sous-comité des bibliothèques (Roy et Bégin, 1969).

Dataverse internationalization took place in two phases: the first phase began in 2015, and the second phase began a few years later (Bilodeau, 2018). Marie-Hélène Vézina, a senior librarian from l’Université de Montréal with experience in digital project development, teamed with Scholars Portal staff, with support from the broader Dataverse community, including Harvard’s Institute for Quantitative Social Science, to internationalize Dataverse software. Although some translation work had been done in the past, nothing had been done to support multilingualism. The developed code became part of the central Dataverse software codebase, which allowed a bilingual (French and English) installation to be deployed by Scholars Portal. L’Université de Montréal contributed the French translation. The Scholars Portal and BCI institutions finalized and signed a formal agreement in spring 2019, and the first institutional Dataverse collections from BCI institutions were made available to researchers in summer 2022 (Vézina, 2022).

At l’Université de Montréal, the first dedicated RDM librarian position was established. Soon after, a second RDM librarian position was opened at l’Université Laval. McGill University set up an RDM research support position, and three smaller institutions shared an RDM research support position, namely l’Institut national de la recherche scientifique (INRS), l’École nationale d’administration publique (ENAP), and la Telé-université, Université du Québec (TÉLUQ).

Other institutions have allocated part-time resources to RDM. Institutional Dataverse collections are being launched in Borealis. The focus will likely be on keeping pace with growing needs in the years to come.

RDM in Ontario

In Ontario, there are 23 public universities and 24 colleges. Since the 1960s, the libraries at these universities have been successfully collaborating through the Ontario Council of University Libraries (OCUL). In its early years, OCUL was involved in traditional library services, such as consortial licensing of journals and facilitating effective resource sharing. In those early years, several institutions developed their own data repository systems, including Carleton University’s Social Science Data Archive, founded in 1965 in the Sociology and Anthropology Department; Western University’s Data Resources Library, launched in the late 1970s, which worked with the Social Science Computing Laboratory to disseminate and archive several faculty research projects; and the University of Toronto’s Map and Data Library, established in 1988, with services that included the acquisition and preservation of datasets produced by the University of Toronto researchers.

In 2002, OCUL formed Scholars Portal, a shared technology infrastructure that hosts and provides access to OCUL’s growing digital collections. As data services came to greater prominence, Ontario libraries saw an opportunity to collaborate under the OCUL umbrella in order to improve services, reduce duplication of effort, and better manage limited resources. Over the last decade, OCUL has undertaken several successful data infrastructure projects, including the development of the collaborative <odesi>, a social science data portal, and Scholars GeoPortal, a geospatial data portal. While both of these data portals do contain some research data, they are intended as curated collections of published datasets from authoritative sources, such as government statistical agencies. As such, they are not conducive to the widespread inclusion of member libraries’ institutional research data outputs. These systems are primarily focused on discovery and access rather than long-term data preservation (Moon, 2014).

For this reason, other solutions were needed in Ontario as well as in Canada to address the growing demand for library research data repositories. In 2011, Scholars Portal joined the UBC Library pilot and installed a Dataverse repository, an open source software and offered it to the OCUL community as a pilot program. The pilot was intended to address a community-identified need for an Ontario-based repository service that would allow for easy-to-use, web-based self-deposit by researchers. Dataverse software was chosen for the pilot due to its support for research data, including the Data Documentation Initiative (DDI) built-in metadata. Scholars Portal staff developed documentation and training materials to inform and train staff at OCUL libraries about the benefits of incorporating Dataverse software into the suite of services offered for data management and deposit of research data. As a result, the Scholars Portal Dataverse repository, now branded Borealis, has allowed some OCUL libraries to launch RDM services without needing to have the technical infrastructure and staffing to support repositories of their own. Models for the service vary from library to library, ranging from self-serve deposit to library-mediated curation. Today, the service has grown dramatically. Many more institutions across Canada have joined or migrated their research data content to Borealis, making it a national hub for research data archiving. The support for the use of Borealis is largely provided by local library staff and is independent of the infrastructure hosted and supported by Scholars Portal.

The OCUL data community, which was initially formed to address data access for Statistics Canada DLI data, has evolved into a forum for support of RDM. Experts from Ontario academic institutions have been key members of the Alliance RDM community and working groups.

RDM in the Prairie Provinces

Institutions in the Prairie provinces have been very influential in the national RDM collaborations over the last decade. In early 2015, the University of Alberta Libraries implemented the first Canadian instance of an open source online tool to help researchers write DMPs. A UK-based DMPOnline code was used at that time, and UBC and the University of Alberta were the first Canadian institutions to adapt the Canadian version.

Almost immediately, the project was adapted by other Canadian institutions within the CARL Portage framework and was branded as DMP Builder. Later in the tool’s lifecycle, it was rebranded again and became DMP Assistant, which included English and French options to better serve the francophone academic community. Over 50 Canadian institutions now use DMP Assistant with custom institutionally specific guidelines developed by the Alliance RDM NOE. It has been almost a decade since the University of Alberta Libraries sponsored DMP Assistant for the Canadian RDM community, who greatly appreciate their work.

Since late 2015, the University of Saskatchewan (USask) Research Computing has been implementing a similar initiative in partnership with the Office of the Vice-President Research. As a result of Compute Canada’s seed funding, the USask team was chosen to create a national data discovery interface for research data in Canada. The USask-based team is still chiefly responsible for the software development and operation of the Lunaris platform, now under the Alliance umbrella. They adapted the open source code base from the UBC Library Open Collections as their main discovery interface back in 2016 and the Geodisy open source code base, also developed by the UBC Library, as their map-based data discovery interface. Using the open source Archivematica software, the USask-based team has also developed an excellent collaboration with the Globus Connect platform to work with big data and preserve research data digitally at scale.

RDM in British Columbia

British Columbia institutions have long been engaged with RDM, with the University of British Columbia (UBC), Simon Fraser University (SFU), and the University of Victoria (UVic) taking the lead in this work. The UBC Library is one of the largest university libraries in Canada and has been conducting ad hoc RDM activities since the early 1970s. In 2008, to help smaller regional schools, UBC entered into an arrangement to make the Abacus data repository available to other universities in the province. At the time of writing, four major university research libraries in British Columbia (Simon Fraser University, University of Victoria, University of Northern British Columbia, and the University of British Columbia) are using the UBC instance of the Dataverse repository as a licensed data repository.

Data is provided to users from each institution according to their data licenses using the Canadian Access Federation, an organization that manages digital identities in higher education and research through a trust framework for access control. The UBC Library data team provides basic and advanced training on the Dataverse repository to groups, departments, and labs on the UBC campus and to its partners in other university libraries and research institutions. After the training, these groups should be managing their own data within the appropriate Dataverse assigned to them. UBC Library School (now known as iSchool) was also one of the earliest Canadian institutions to offer a Research Data Management graduate course.

The SFU and UVic Libraries have also contributed greatly to the RDM landscape in Canada. Early in the 2010s, the SFU Library developed Radar, its own Islandora-based research data repository (now depreciated and replaced by FRDR), and it became the Canadian leader on zero-knowledge encryption of sensitive data. The UVic Libraries have also successfully experimented with RDM services and have accommodated unique license needs for research teams, such as, for example, the well-used Canada Health Infoway datasets.

RDM in Northern Canada

Northern Canada consists of three territories: the Northwest Territories, Nunavut, and Yukon. The two research institutions located in Northern Canada are Yukon University and Aurora College. As part of the institutional RDM strategy (mandated by the Tri-Agency RDM Policy), Yukon University librarians and the Research Services Office work together to build an institutional repository hosted by BC ELN Arca – a collaborative initiative for digital repositories in BC based on Islandora software, primarily aimed at smaller institutions and colleges. Research outputs deposited by Yukon University researchers into BC ELN Arca will be harvested by Lunaris.

In October 2022, librarians from Aurora College in Inuvik participated in an institutional strategy panel organized by the Alliance. They shared their unique experience addressing RDM issues at the small-size Northern institution. Some institutions from Northern Canada, including Yukon University, work together with universities and colleges from British Columbia to develop their institutional RDM strategies in line with the Tri-Agency RDM Policy. They collaborate as an ad hoc group to create action plans and share visions for RDM services in small institutions.

Conclusion

It is an exciting time for RDM in Canada, and it took years of dedicated work and sophisticated, multi-provincial collaboration to get to this point. Libraries are seeing new opportunities to engage with their communities and with one another. With these new opportunities inevitably come challenges, such as costly digital infrastructure that must be managed on an ongoing basis. We believe that Portage and the formation of the Alliance have the greatest potential to meet some significant unmet needs, but they will need sustainable funding in order to be successful.

The development of open source tools, infrastructure, and support services for RDM is crucial if Canadian scholars are to successfully integrate these new activities into their workflows. Academic libraries have a history of supporting data access, dissemination, and preservation, and they have an established mandate to participate in the preservation of the research outputs of their community (e.g., in institutional repositories). Libraries can provide leadership in the adoption of best practices and open standards. They can also partner with other groups in the development of infrastructure and tools. The Canadian library community has been actively encouraging research data sharing since the 1960s and is well-positioned to play a leadership role going forward.

Acknowledgement

The initial draft of the RDM in Quebec section was contributed by Ève Paquette-Bigras, academic librarian at the Université de Montréal. The authors are grateful to Ève for providing the background and context for the RDM achievements in that province.

Additional Readings and Resources

Doiron, J., Neilson, M., & Nicholson, R. (2020). Data management planning in Canada. White paper for NDRIO. https://alliancecan.ca/en/document/261

Government of Canada. (2021). Tri-Agency research data management policy. https://www.science.gc.ca/eic/site/063.nsf/eng/h_97610.html

Lavoie, B., & Dempsey, L. (2004). Thirteen ways of looking at…digital preservation. D-Lib Magazine, 10(7–8). https://doi.org/10.1045/july2004-lavoie

Moon, J. (2021). Update on Portage and the Digital Research Alliance of Canada Alliance. https://alliancecan.ca/en/latest/news/update-portage-and-digital-research-alliance-canada

Read, K., McDonald, G., Mackay, B., & Barsky, E. (2014). A commitment to First Nations data governance: A primer for health librarians. Journal of the Canadian Health Libraries Association / Journal de l’Association des bibliothèques de la santé du Canada, 35(1), 11–15. https://doi.org/10.5596/c14-003

Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J-. W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B. (2016). Comment: The FAIR guiding principles for scientific data management and stewardship. Scientific Data, 3, 1–9. https://doi.org/10.1038/sdata.2016.18

Reference List

Attendees of the NDSF Summit. (2019). Kanata declaration (Version 2.0). National Data Services Framework Summit 2019 (NDSF 2019), Ottawa, Canada. Zenodo. https://doi.org/10.5281/zenodo.3234815

Barsky, E., Laliberté L., Leahey, A., and Trimble, L. (2017). Collaborative research data curation services: A view from Canada. In L.R. Johnston (Ed.), Curating research data, volume one: Practical strategies for your digital repository. Association of College and Research Libraries. https://dx.doi.org/10.14288/1.0340778

Bilodeau, G. (2018). Gestion des données de recherche (GDR): Écosystème Canadien – un bref survol. https://www.ulaval.ca/sites/default/files/recherche-creation/documents/conduite%20responsable/gestion-donnees-recherche-bilodeau.pdf

Boyko, E., & Watkins, W. (2011). The Canadian data liberation initiative: An idea worth considering. International Household Survey Network, IHSN Working Paper (006). www.ihsn.org/sites/default/files/resources/IHSN-WP006.pdf

Cheung, M., Cooper, A., Dearborn, D., Hill, E., Johnson, E., Mitchell, M., & Thompson, K. (2022). Practices before policy: Research data management behaviours in Canada. Partnership: The Canadian Journal of Library and Information Practice and Research, 17(1), 1-80. https://doi.org/10.21083/partnership.v17i1.6779

Cooper, A., Steeleworthy, M., Paquette-Bigras, È., Clary, E., MacPherson, E., Gillis, L., Wilson, L., & Brodeur, J. (2021). Dataverse curation guide. Zenodo. https://doi.org/10.5281/zenodo.5579820

Gray, S. V., & Hill, E. (2016). The academic data librarian profession in Canada: History and future directions. Western Libraries Publications. Paper 49. http://ir.lib.uwo.ca/wlpub/49

Hackett, Y. (2001). A national research data management strategy for Canada: The work of the National Data Archive Consultation Working Group. IASSIST Quarterly, ​25(3), 13-16. https://doi.org/10.29173/iq91

Heidorn, P. B. (2008). Shedding light on the dark data in the long tail of science. Library Trends, 57(2), 280–299. https://doi.org/10.1353/lib.0.0036

Humphrey, C. (2005). Collaborative training in statistical and data library services: Lessons from the Canadian data liberation initiative. Resource Sharing and Information Networks, 18(1–2), 167–181. https://doi.org/10.1300/J121v18n01_13

Humphrey, C. (2012a, December 5). Canada’s long tale of data. Preserving Research Data in Canada. http://preservingresearchdataincanada.net/2012/12/05/hello-world

Humphrey, C. (2012b, December 13). Research data management infrastructure II. Preserving research data in Canada. https://preservingresearchdataincanada.net/2012/12/13/research-data-management-infrastructure-ii/

Humphrey, C. (2020). The CARL Portage partnership story. Partnership: The Canadian Journal of Library and Information Practice and Research, 15(1), 1–7. https://doi.org/10.21083/partnership.v15i1.5825

Humphrey, C., Shearer, K., & Whitehead, M. (2016). Towards a collaborative national research data management network. International Journal of Digital Curation, 11(1), 195–207. https://doi.org/10.2218/ijdc.v11i1.411

Liss, S. N. (2018, September 5). Addressing gaps in Canadian research data management: A comprehensive guide of the Portage Network. University Affairs. https://www.universityaffairs.ca/magazine/sponsored-content/addressing-gaps-in-canadian-research-data-management/

Moon, J. (2014). Developing a research data management service – a case study. Partnership: The Canadian Journal of Library and Information Practice and Research, 9(1), 1–14. https://doi.org/10.21083/partnership.v9i1.2988

Roy, J. et Bégin, J.-O. (1969). Enquête relative à un plan de coordination. Montréal : Comité de coordination des bibliothèques de la CREPUQ.

Steeleworthy, M. (2014). Research data management and the Canadian academic library: An organizational consideration of data management and data stewardship. Partnership: The Canadian Journal of Library and Information Practice and Research, 9(1), 1–11. https://doi.org/10.21083/partnership.v9i1.2990

Strong, D. F., & Leach, P. B. (2005). National consultation on access to scientific research data. Final Report. Government of Canada. https://publications.gc.ca/site/eng/272526/publication.html

Vézina, M.-H. (2022). Métadonnées bibliographiques des thèses et mémoires du dépôt institutionnel de l’Université de Montréal [Canada] [dataset]. Borealis. https://doi.org/10.5683/SP3/SJJACL