Barriers and pathways for advancing open science and open scholarship in academic institutions: a Canadian perspective

1 Barriers and pathways for advancing open science and open scholarship in academic institutions: a Canadian perspective Pedro R. Peres-Neto1, Nicolás Alessandroni2 and Krista Byers-Heinlein2 1Corresponding author, Department of Biology, Concordia University, 7141 Sherbrooke Street West, Montreal, QC H4B 1R6, Canada; 2Department of Psychology, Concordia University, 7141 Sherbrooke Street West, Montreal, QC H4B 1R6, Canada. Abstract Open science and open scholarship aim to make research more transparent, accessible, and reusable, yet adoption across Canadian universities remains uneven despite growing funder mandates and policy requirements. This paper examines the structural, organizational, and cultural barriers that impede widespread implementation of open science practices within academic institutions and proposes pathways for meaningful institutional transformation. Drawing on examples from multiple Canadian universities and using Concordia University as a detailed case study, we identify nine interconnected barriers spanning evaluation systems, researcher capacity, infrastructure, governance structures, and equity considerations. These include misaligned academic reward structures, limited researcher training, cultural resistance to data sharing, insufficient cyberinfrastructure, fragmented institutional responsibilities, inadequate frameworks for sensitive data, policy ambiguities, overreliance on libraries, sparse community engagement, and accessibility barriers. We argue that overcoming these challenges requires coordinated multilevel governance integrating top-down institutional leadership with bottom-up disciplinary engagement. The Concordia case demonstrates how combining grassroots researcher initiatives with administrative support can achieve system-wide policy change, culminating in the university’s unanimous Senate resolution on open science and open scholarship in May 2025. This framework offers a roadmap for Canadian institutions seeking to align their structures, policies, and cultures with expanding expectations for research transparency and openness. Keywords: open science, open scholarship, research data management, institutional transformation, academic governance, Indigenous data sovereignty 2 Open science and scholarship as drivers of research transformation Open science and open scholarship refer to a set of interconnected practices aimed at making research processes, outputs, and infrastructures more transparent, accessible, inclusive, and reusable across all stages of research design, execution, and dissemination (Fecher and Friesike 2014). Core elements include open access publishing, open data and code, open methodologies, as well as other practices such as open preprints, open educational resources, open lab notebooks, open hardware, and citizen science (Nosek et al. 2015; Wilkinson et al. 2016). These open science and scholarship practices aim to boost the reliability of research findings, strengthen public trust in science, and broaden participation in knowledge production (Fig. 1). Open science and open scholarship also offer concrete practical benefits by reducing duplication of effort, accelerating discovery, and enabling more efficient use of research resources. Studies have shown that research teams who share methods and data benefit from higher visibility, more citations, and greater reproducibility (McKiernan et al. 2016; Renaut et al. 2018). In this paper, we use the term “open science” while acknowledging that “open scholarship” may be more inclusive of the full range of academic disciplines and practices. We recognize that open science typically emphasizes the transparency and reproducibility of research processes, while open scholarship encompasses broader cultural, institutional, and participatory dimensions through which knowledge is produced, shared, and valued. Despite its limitations, we use “open science” here given its widespread adoption in policy documents, funding agency mandates, and international frameworks, and intend it to include both the technical and sociocultural dimensions of openness. Open science has increasingly become a mandate across multiple governance levels, from international organizations such as UNESCO (2021), to national funding agencies including Canada’s Tri-Agency and the US National Science Foundation (NSF), to universities (and other academic institutions, e.g., research institutes) adopting institutional open scholarship policies and infrastructures. These developments underscore that openness should no longer be optional but fundamental to ensuring research credibility, transparency, and societal relevance. Yet the transition toward open science remains strikingly limited (Alessandroni and Byers-Heinlein 3 2022; Tennant et al. 2016; Thibault et al. 2023; Vicente-Saez and Martínez-Fuentes 2018) despite funder mandates. For example, only 46% of Canadian researchers’ publications from 2015-2018 were available in any form of open access (Haustein, cited in University Affairs, 2023). Many Canadian universities have developed research data management strategies in response to funder mandates, but there is considerable variation in resources, capacity, and implementation approaches (Cobey et al. 2025). Moreover, qualitative research reveals that Canadian researchers, administrators, and librarians hold diverse and sometimes conflicting views about open science (Burt-D’Agnillo and Thuna 2025). These gaps between policy requirements and actual practice underscore that institutional policies, incentives, and support structures have not kept pace with expanding expectations. The goal of this paper is to shed light on the persistent structural, organizational, and cultural barriers that impede the widespread adoption of open science and scholarship within universities and to examine the institutional transformations required to enable system-wide change. We first analyze both existing approaches in Canadian institutions to open scholarship and the structural barriers that limit their impact. We then outline structural barriers and potential solutions. Finally, we use Concordia University (Montréal, Québec, Canada) as a case study for an integrated governance framework that combines bottom-up (i.e., researcherand communitydriven initiatives) and top-down (i.e., institution-led policies, mandates, and resource allocation) approaches. By focusing on the conditions under which open practices can meaningfully develop, we aim to contribute to an informed discussion on how academic institutions can align their structures, policies, and cultures with the expanding societal and scientific expectations for transparency, accessibility, and openness. Existing approaches to open scholarship in Canada Canadian universities have pursued varied paths toward open scholarship, reflecting different institutional priorities, resources, and governance structures. These existing initiatives provide important context for understanding both progress made and persistent challenges. Several Canadian universities have fostered open science through top-down initiatives. These typically involve strategic planning processes and working groups, often led by research 4 offices and libraries. The University of Ottawa formed an Open Science Working Group that delivered recommendations in 2024 (Butler et al. 2025; University of Ottawa 2024; University of Ottawa Open Science Working Group 2024). In response to new requirements from Canadian funding agencies, universities including Calgary, Toronto, and UBC have developed institutional Research Data Management strategies through collaboration among research administration, libraries, and IT services (see references - Burt-D'Agnillo and Thuna 2025 for University of Toronto; University of Calgary 2025; University of British Columbia 2023). Multiple institutions have also pursued library-led initiatives focused primarily on open access publishing (Open Scholarship Policy Observatory 2017). Philanthropy has also been an important driver of open science in Canada, particularly in neuroscience. Following a $20-million donation in 2016, the Montreal Neurological InstituteHospital (The Neuro) established the Tanenbaum Open Science Institute (TOSI) and adopted comprehensive open science principles (Poupon et al. 2017, 2020). The Neuro's transition involved extensive consultation processes including surveys, presentations, and retreats to address researcher concerns about workload, intellectual property, and data sharing requirements (Poupon et al. 2020). TOSI has since formed partnerships with other Canadian neuroscience institutes, creating an alliance that now includes completed partnerships with the University of Calgary's Hotchkiss Brain Institute, the Douglas Research Centre, the University of British Columbia's Djavad Mowafaghian Centre for Brain Health, and the Centre for Addiction and Mental Health, with Western University's Institute for Neuroscience and the Centre de recherche de l'Institut universitaire de gériatrie de Montréal in the buy-in phase. Simon Fraser University (SFU) represents an adaptation of this model to university-wide scale. Through its partnership with TOSI, SFU developed institution-wide open science and open scholarship guidelines (Simon Fraser University 2025). Bottom-up work on open science also exists alongside these formal strategies. Libraries across Canadian universities provide crucial support through open access guidance, repository services, and research data management training. Many institutions also have committees, journal clubs, and individual labs and research groups that practice and support open science. 5 These varied approaches - top-down institutional strategies, philanthropically driven initiatives, and bottom-up grassroots activities - demonstrate Canadian universities’ recognition of open scholarship’s importance. Yet despite these efforts, adoption remains uneven (Ripp et al. 2025). The following analysis identifies nine structural barriers that explain why even wellintentioned initiatives struggle to achieve deep, sustainable transformation. Nine structural barriers hindering open science implementation Drawing on our experience working across multiple academic units and disciplines at Concordia University, as well as conversations with scholars across Canada, we have observed that the transition toward open scholarship is shaped by a complex set of organizational, cultural, and infrastructural factors. While enthusiasm for openness is widespread among university communities - among faculty, librarians, students, and staff alike - the practical implementation of open practices often encounters systemic obstacles embedded in institutional routines and governance structures. In the following section, we outline nine structural barriers that collectively slow the adoption of open scholarship and highlight areas where targeted institutional action is needed (see Table 1 for a summary). Evaluation and Incentive Barriers [1] Misaligned Incentives and Academic Reward Structures. Universities evaluate researchers primarily on outputs such as high-impact publications, citations, and grants, while undervaluing datasets, open-source software, transparent analytical workflows, communityengaged research, and reproducibility-enhancing practices (Aubert Bonn and Pinxten, 2021; Hicks et al. 2015). This disconnect makes open practices appear professionally risky, particularly for early-career researchers facing tenure decisions. [2] Cultural resistance and data hoarding. Fear of being “scooped,” losing competitive advantage, or having data misinterpreted creates hesitations around sharing. Intellectual property questions, ambiguous authorship expectations, and deep-seated cultural norms (e.g., protecting data until publication) further contribute to hesitation (Vicente-Saez and Martínez-Fuentes 2018). These cultural barriers are amplified by a documented pattern of data loss: research data availability decreases by 17% per year after publication (Vines et al. 2014), with an estimated 6 80% of all scientific data are never used, published, or shared, remaining as “dark data” in notebooks and hard drives (Heidorn 2008). Without institutional support, researchers are not effective long-term data stewards (Gonzalez and Peres-Neto 2015). Capacity and Skills Barriers [3] Limited researcher training. Researchers have limited knowledge and access to training in areas such as research data management, metadata standards, version control, reproducible computational workflows, and ethical data sharing. Many researchers rely on ad hoc, peer-to-peer learning or self-teaching, resulting in variable uptake and quality of open outputs (Tenopir et al. 2018). Compounding this, many instructors and researchers who themselves lack knowledge or confidence in open science practices may be reluctant to teach or promote these skills to their trainees, inadvertently perpetuating gaps in literacy and capacity across generations of scholars. [4] Insufficient cyberinfrastructure and technical support. Open scholarship relies on secure repositories, persistent identifiers, interoperable metadata, long-term storage solutions, and computational environments for reproducibility. While there are discipline-specific infrastructures (e.g., data repositories such as Dryad for biological and medical data, GenBank for sequence data, PANGAEA for earth and environmental sciences, ICPSR for social sciences) as well as Canadian infrastructure (e.g., Calcul Québec, Digital Research Alliance of Canada, WestGrid), they are not designed for implementing all stages of the open-science workflow (Fig. 1). Moreover, without sufficient support, even well-established repositories remain underused, and researchers struggle to deposit, document, and curate data in ways that meet disciplinary and FAIR (Findable, Accessible, Interoperable, Reusable) standards. Governance and Coordination Barriers [5] Fragmented responsibilities and overreliance on libraries. Open science and scholarship are multifaceted, touching nearly every aspect of university research operations. As a result, many units (e.g., libraries, research offices, IT services, ethics boards, teaching centres, and academic departments) naturally interface with open scholarship in their regular work, providing training, infrastructure, policy guidance, and research support. However, this work 7 typically proceeds without coordination, creating inconsistent messaging, duplicated efforts, and confusion for researchers navigating open scholarship requirements (Renaut et al. 2018). Perhaps because libraries were early and visible leaders in institutional efforts around open access publishing, there can be an expectation now that they should similarly coordinate all other dimensions of open scholarship. However, while libraries provide essential services in research data management and scholarly communication, they lack both the capacity and comprehensive expertise required for institution-wide coordination. Open scholarship encompasses domain-specific data standards, computational workflows, research ethics protocols, incentive structures, cyberinfrastructure, and disciplinary norms that extend far beyond any single unit’s purview (Zimmerman 2008). Effective adoption requires both distributed ownership and formal coordination mechanisms that enable all relevant units to align their efforts. [6] Policy ambiguity and gaps in governance alignment. Although external bodies such as UNESCO, the OECD, national funders, and peer review journals (Jenkins et al. 2023) increasingly mandate open scholarship, universities frequently struggle to translate these expectations into actionable policies, standardized procedures, and clear accountability mechanisms. Ambiguity around compliance requirements, resource allocation, and long-term stewardship responsibilities often leads to inconsistent implementation by researchers. Without coherent governance frameworks that align institutional policies with researcher incentives and support systems, open scholarship risks becoming a formal obligation rather than a fully integrated and supported academic practice. Equity and Access Barriers [7] Inadequate sensitive data frameworks. Research involving human participants, endangered species, Indigenous knowledge, or proprietary information requires secure enclaves, tiered-access models, and ethical protocols that many institutions lack. Without these frameworks, researchers must choose between openness and responsible data governance. [8] Limited community engagement. Canadian universities have been slow to develop frameworks respecting Indigenous Data Sovereignty principles (First Nations Information 8 Governance Centre - FNIGC 2014). Open scholarship practices developed without community leadership risk reproducing extractive relationships, and conflicting with rights to selfdetermination (Carroll et al. 2020; Raine et al. 2019). [9] Accessibility and linguistic barriers. Many open science resources and platforms fail to adhere to accessibility standards (e.g., compliance with Web Content Accessibility Guidelines/WCAG), missing Alt-Text for figures, non-machine-readable documents such as some PDFs, and poorly structured datasets can make ostensibly “open” resources functionally closed to many users, including those with disabilities and language barriers (Borgman 2010; Brown and Holloway 2008). In the Canadian context, accessibility is also inseparable from linguistic inclusivity. As an officially bilingual and multicultural country, Canada requires open scholarship systems that support both official languages (English and French) while also respecting and enabling the use of additional languages spoken in immigrant and Indigenous communities (Haque and Cray 2011). Without inclusive design, openness risks becoming an ideal in principle but exclusionary in practice. These barriers are interconnected and mutually reinforcing. Cultural norms, incentive structures, training gaps, and fragmented governance combine to make open science and scholarship difficult to enact through isolated efforts. In the next section, we outline pathways for creating the supportive ecosystem needed for open scholarship to become standard practice in academic institutions. Institutional pathways for overcoming barriers to open science and scholarship The transition to open science and scholarship cannot be achieved through individual goodwill alone. Structural barriers, embedded in evaluation systems, training pathways, infrastructure, and governance, continue to constrain adoption even where normative support is strong. Addressing these barriers requires deliberate institutional pathways that align incentives, build capacity, clarify responsibilities, and embed openness across the research lifecycle. Below, we outline several interdependent pathways through which universities can enable this transformation. 9 Reforming Evaluation and Incentives Institutions must fundamentally revise hiring, tenure, and promotion criteria to recognize a broader range of scholarly contributions. International frameworks such as Declaration on Research Assessment (DORA 2012), the Leiden Manifesto, and the Hong Kong Principles for assessing researchers provide robust frameworks for shifting evaluation away from journal-based metrics and toward responsible assessment (DORA 2012; Hicks et al. 2015; Moher et al. 2020). Adoption of these principles can help institutions legitimize open practices and reduce the perceived career risks associated with transparency and data sharing. Evidence demonstrates that integrating open scholarship into formal evaluation systems leads to increased research visibility and improved reproducibility across disciplines (Aubert Bonn and Pinxten 2021; Larivière et al. 2016), suggesting that incentive reform is both feasible and beneficial. Building Capacity and Infrastructure Sustainable adoption of open scholarship also requires comprehensive training across the academic lifecycle, including undergraduate curricula, graduate professional development, postdoctoral training, and faculty advancement. Models such as The Carpentries, the Center for Open Science training modules, and UNESCO’s Open Science Capacity Building Framework provide approaches and frameworks for developing technical and conceptual fluency (Wilson 2014; Nosek et al. 2015; UNESCO 2021). Research has shown that structured institutional training significantly increases adherence to FAIR (Findable, Accessible, Interoperable, Reusable) and Indigenous data sovereignty principles, promotes responsible data reuse, and narrows literacy gaps across disciplines (European Commission 2018; Stall et al. 2019). Importantly, training must include instructors themselves; without faculty preparedness, open scholarship cannot diffuse effectively through research supervision or laboratory culture. Infrastructure investment must parallel skills development. Universities must invest in persistent identifiers (PIDs), well-supported repositories, secure environments for sensitive data, and computational workflows that ensure reproducibility across platforms and time. Canada could benefit from institutional cyberinfrastructure hubs that interface with national systems like the Digital Research Alliance as well as discipline-specific resources, to support seamless integration between local workflows and larger infrastructure. International examples such as the 16 employs a graduated approach that fosters capacity-building and disciplinary adaptation while still signalling strong institutional commitment. The extensive community consultations by grassroots Working Group members, together with the active support of administration led to a major milestone: on May 16, 2025, Concordia’s Senate unanimously passed the new Resolution on Open Science and Open Scholarship, establishing the university’s first comprehensive institutional mandate in this area (Alessandroni et al. 2025). Importantly, the resolution integrates open science and open scholarship into hiring, reappointment, and tenure discussions, and embeds obligations for training, infrastructure support, cross-unit collaboration, and equitable governance structures. In doing so, it transforms open scholarship from a voluntary practice to a formally recognized institutional priority. The Concordia case illustrates how bottom-up and top-down models can be mutually reinforcing: community initiatives create the intellectual groundwork and legitimacy needed for institutional policy, while top-down support supplies the authority, resources, and accountability structures required for system-wide adoption. Such a multi-level approach can achieve outcomes that neither could deliver on its own. The success of a multilevel approach was further evidenced by the 1st Canadian Conference on Open Science and Open Scholarship, hosted at Concordia in October 2025, which showcased the institution’s leadership and helped accelerate coordinated efforts across the Canadian research landscape. Conclusions: aligning institutional change with the promise of open scholarship Advancing open science and scholarship within academic institutions necessitates a fundamentally structural challenge. The nine barriers identified in this paper highlight that open scholarship cannot become a default academic practice through individual initiative alone. Rather, it requires coordinated reforms that embed openness into hiring and promotion criteria, research training, cyberinfrastructure, and institutional governance. These barriers also reveal opportunities: by treating open scholarship as core to research quality and integrity, universities can improve the robustness, visibility, and societal relevance of the knowledge they produce. The Canadian experience, and the Concordia case in particular, demonstrates that meaningful progress emerges when bottom-up and top-down efforts are intentionally aligned. 17 While each institution requires its own pathway, the principles outlined here by recognizing diverse scholarly contributions, investing in training and infrastructure, building inclusive and community-engaged governance, and integrating openness into multilevel institutional frameworks, offer a roadmap for universities seeking to move from aspiration to sustained practice. This is not only a Canadian concern but a globally relevant project shaping how future generations of scholars are trained, how knowledge circulates, and how universities fulfill their societal responsibilities. Sustaining progress toward open science and open scholarship requires recognizing that institutional transformation is ongoing, not a one-time achievement. Universities must routinely evaluate whether training reaches intended audiences, incentives recognize diverse contributions, infrastructures remain reliable, and governance reflect disciplinary, and community needs. Through an iterative refinement, openness becomes not only a policy commitment but a living practice evolving alongside the research landscape it seeks to transform. Acknowledgements Concordia University is situated on the unceded traditional territory of the Kanien’kehá:ka Nation, the custodians of the lands and waters on which the university stands. This work was supported by a grant from the Social Sciences and Humanities Research Council of Canada to KBH (895-2025-1008). KBH holds the Concordia University Research Chair in Bilingualism and Open Science. Additional support was provided by the Fonds de recherche du Québec through a Postdoctoral Fellowship to NA (B3Z, #333109, https://doi.org/10.69777/333109). This work was supported by grants from the Canadian Natural Science and Engineering Research Council (NSERC) to PRPN (Discover Grant program, RGPIN-2020-07188, Ecology in Spatially Structured Environments); PRPN is also supported by the Canada Research Chairs program (CRC-2023-00139, Spatial Ecology and Biodiversity). References Alessandroni N., Byers-Heinlein K. 2022. Ten strategies to foster open science in psychology and beyond. Collabra: Psychology, 8(1): 57545. 18 Alessandroni N., Byers-Heinlein K., Buckland A., Chalifour J., Dugré M., Glowacki T., et al. 2023 Recommendations for Fostering Open Science at Concordia University. Concordia University. 10 p. Available from https://doi.org/10.11573/spectrum.library.concordia.ca.00992647 [last accessed 21 December 2025]. Alessandroni N., Byers-Heinlein K., Buckland A., Chalifour J., Dugré M., Glowacki T., et al. 2025. Senate Resolution on Open Science and Open Scholarship at Concordia University, Concordia University. 4 p. Available from https://doi.org/10.11573/spectrum.library.concordia.ca.00995690 [last accessed 21 December 2025]. Aubert Bonn N., Pinxten W. 2021. Advancing science or advancing careers? Researchers' opinions on success indicator', PLOS ONE, 16(2): e0243664 Barker M., Wilkinson R., Treloar A. 2019. The Australian Research Data Commons. Data Science Journal, 18(44): 1-7. Available from https://datascience.codata.org/articles/dsj-2019-044 [last accessed 21 December 2025]. Beasley G. 2011. The Senate Resolution on Open Access at Concordia University. Feliciter, 57(3): 101-102, 113. Available from https://spectrum.library.concordia.ca/id/eprint/7777/ [last accessed 21 December 2025]. Berridge V. 2013. Demons: Our changing attitudes to alcohol, tobacco, and drugs. Oxford University Press. 304 p. Bezuidenhout L.M., Leonelli S., Kelly A.H., Rappert B. 2017. Beyond the digital divide: Towards a situated approach to open data. Science and Public Policy, 44(4): 464-475. Borgman C.L. (2010). Scholarship in the Digital Age: Information, Infrastructure, and the Internet. MIT Press. 360 p. Brown L., Holloway I. 2008. The adjustment journey of international postgraduate students at an English university: An ethnographic study. Journal of Research in International Education, 7(2): 232-249. Burt-D'Agnillo M., Thuna M. 2025. Open science at the University of Toronto: An exploration of researcher, administrator, and librarian perspectives. Partnership: The Canadian Journal of Library and Information Practice and Research, 19(2): 1-38. Available from https://doi.org/10.21083/partnership.v19i2.7847 [last accessed 21 December 2025]. Butler L.A., Hare M., Van Walsum S., Chantal R., Haustein S. 2025. An evidence-based approach to advancing open science at the University of Ottawa: Experiences from the Open Science Working Group. In Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l’ACSI. Available from https://doi.org/10.29173/cais1953 [last accessed 21 December 2025]. Carroll S.R., Garba I., Figueroa-Rodríguez O.L., Holbrook J., Lovett R., Materechera S., et al. 2020. The CARE Principles for Indigenous Data Governance. Data Science Journal, 19(1): 43. 19 Cobey K.D., Armond A.C.V., Ramos J., Ripp C., Moher D. 2025. Is Canada poised to implement a data deposit requirement? FACETS, 10: 1-3. David-Chavez D.M., Gavin M.C. 2018. A global assessment of Indigenous community engagement in climate research. Environmental Research Letters, 13(12): 123005. Deem R. 2004. The knowledge worker, the manager-academic and the contemporary UK university: New and old forms of public management? Financial Accountability & Management, 20(2): 107-128. DORA - San Francisco Declaration on Research Assessment. 2012. San Francisco Declaration on Research Assessment. Available from https://sfdora.org [last accessed 21 December 2025]. European Commission. 2018. Turning FAIR into Reality: Final Report and Action Plan. Directorate-General for Research and Innovation. Available from https://bpos.bg/assets/documents/Превръщане%20на%20FAIR%20в%20реалност.pdf [last accessed 21 December 2025]. Fecher B., Friesike, S. 2014. Open Science: One term, five schools of thought. In Opening Science. Edited by S. Bartling, S. Friesike. Springer, Cham. pp. 17-47. Available from https://doi.org/10.1007/978-3-319-00026-8_2 [last accessed 21 December 2025]. Fecher B., Kahn R., Sokolovska N., Völker T., Nebe P. 2021. Making a research infrastructure: conditions and strategies to transform a service into an infrastructure. Science and Public Policy, 48(4): 499-507. FNIGC - First Nations Information Governance Centre. 2014. Ownership, Control, Access and Possession (OCAP™): The Path to First Nations Information Governance. The First Nations Information Governance Centre. Available from https://achh.ca/wpcontent/uploads/2018/07/OCAP_FNIGC.pdf [last accessed 21 December 2025]. Frith U. 2020. Fast lane to slow science. Trends in Cognitive Sciences, 24(1): 1-2. Gonzalez A., Peres-Neto, P.R. 2015. Act to staunch loss of research data. Nature, 520(7548): 436. Haque E., Cray E. 2011. Constraining teachers: Adult ESL settlement language training policy and implementation. TESOL Quarterly, 41(3): 513-535. Haustein S. (cited in University Affairs). 2023. Catching up on open access. University Affairs, 19 April. Available from https://universityaffairs.ca/features/catching-up-on-open-access/ [last accessed 21 December 2025]. Heidorn P.B. 2008. Shedding light on the dark data in the long tail of science. Library Trends, 57(2): 280-299. Hicks D., Wouters P., Waltman L., de Rijcke S., Rafols I. 2015. The Leiden Manifesto for research metrics. Nature, 520(7548): 429-431. 20 Jenkins G.B., Beckerman A.P., Bellard C., Benítez-López A., Ellison A.M., Foote C.G., et al. 2023. Reproducibility in ecology and evolution: Minimum standards for data and code. Ecology and Evolution, 13(5): e9961. Kezar A., Eckel P.D. 2002. The effect of institutional culture on change strategies in higher education. The Journal of Higher Education, 73(4): 435-460. Larivière V., Kiermer V., MacCallum C.J., McNutt M., Patterson M., Pulverer B., et al. 2016. A simple proposal for the publication of journal citation distributions. BioRxiv. Available from https://doi.org/10.1101/062109 [last accessed 21 December 2025]. Leonelli S. 2016. Data-centric biology: A philosophical study. University of Chicago Press, Chicago, IL. 288 p. Marginson S., Rhoades, G. 2002. Beyond national states, markets, and systems of higher education: A glonacal agency heuristic. Higher Education, 43(3): 281-309. McKiernan E.C., Bourne P.E., Brown C.T., Buck S., Kenall A., Lin J., et al. 2016. How open science helps researchers succeed. eLife, 5: e16800. Moher D., Bouter L., Kleinert S., Glasziou P., Sham M.H., Barbour V., et al. 2020. The Hong Kong Principles for assessing researchers. PLOS Biology, 18(7): e3000737. Montgomery L., Hartley J., Neylon C., Gillies M., Gray E. 2021. Open knowledge institutions: Reinventing universities. MIT Press. 176 p. Nosek B.A., Alter G., Banks G.C., Borsboom D., Bowman S.D., Breckler S.J., et al. 2015. Promoting an open research culture. Science, 348(6242): 1422–1425. Open Scholarship Policy Observatory. 2017. Canadian university open access statements. Available from https://ospolicyobservatory.uvic.ca/canadian-university-open-access-statements/ [last accessed 21 December 2025]. OECD - Organisation for Economic Co-operation and Development (2015). Making Open Science a Reality. OECD Publishing. Available from https://doi.org/10.1787/5jrs2f963zs1-en [last accessed 21 December 2025]. Poupon V., Seyller A., Rouleau G.A. 2017 The Tanenbaum Open Science Institute: Leading a paradigm shift at the Montreal Neurological Institute. Neuron, 95(5): 1002-1006. Poupon V., Seyller A., Edwards A., Gold R., Rouleau G. 2020. Open science at the Montreal Neurological Institute and Hospital: The buy-in process. Gates Open Research, 4:15 (document). Available from https://doi.org/10.21955/gatesopenres.1116585.1 [last accessed 21 December 2025]. Raine S.C., Kukutai T., Walter M., Figueroa-Rodríguez O.L., Walker J., Axelsson P. 2019. Indigenous data sovereignty. In State of open data: histories and horizons. Edited by T. Davies, S. Walker, M. Rubinstein, F. Perini. African Minds, Cape Town, South Africa. pp. 300–319. Available from https://doi.org/10.5281/zenodo.2677801 [last accessed 21 December 2025]. 21 Renaut S., Budden A.E., Gravel D., Poisot T., Peres-Neto P.R. 2018. Management, archiving, and sharing for biologists and the role of research institutions in the technology-oriented age. BioScience, 68(6): 400-411. Ripp C., Hare M., Cobey K., Haustein S. 2025. An analysis of open science action plans by Canadian federal science departments and agencies. The Canadian Journal of Information and Library Science, 48(2): 60-77. Scott W.R. 2013. Institutions and organizations: Ideas, interests, and identities. Sage Publications. 360 pp. Shirk J.L., Ballard H.L., Wilderman C.C., Phillips T., Wiggins A., Jordan R., et al. 2012. Public participation in scientific research: A framework for deliberate design. Ecology and Society, 17(2): 29. Simon Fraser University (SFU). 2025. SFU first in Canada to adopt university-wide open scholarship framework., SFU News, March. Available from https://www.sfu.ca/sfunews/stories/2025/03/sfu-first-in-canada-to-adopt-university-wide-openscholarship-fr.html [last accessed 21 December 2025]. Stall S., Yarmey L., Cutcher-Gershenfeld J., Hanson B., Lehnert K., Nosek B., et al. (2019). Make scientific data FAIR. Nature, 570(7759): 27–29. Tennant J.P., Waldner F., Jacques D.C., Masuzzo P., Collister L.B., Hartgerink C.H. 2016. The academic, economic and societal impacts of Open Access: an evidence-based review. F1000Research, 5: 632. Tenopir C., Christian L., Allard S., Borycz J. 2018. Research data sharing: Practices and attitudes of geophysicists. Earth and Space Science, 5(12): 891-907. Thibault R.T., Amaral O.B., Argolo F., Bandrowski A.E., Davidson A.R., Drude N.I. 2023. Open science 2.0: Towards a truly collaborative research ecosystem. PLOS Biology, 21(10): e3002362. Tri-Agency Research Data Management Policy. 2025. Available from https://science.gc.ca/site/science/en/interagency-research-funding/policies-andguidelines/research-data-management/tri-agency-research-data-management-policy [last accessed 21 December 2025]. University of British Columbia (UBC). 2023. New strategy charts plan for research data management support and services. UBC Strategic Plan. 22 p. Available from https://rdm.ubc.ca/news/february-15-2023/new-strategy-charts-plan-research-data-managementsupport-and-services-ubc [last accessed 21 December 2025]. UNESCO. 2021. UNESCO recommendation on open science. UNESCO. Available from https://www.unesco.org/en/open-science/about [last accessed 21 December 2025]. University of Calgary. 2025. Open science. University of Calgary. Available from https://research.ucalgary.ca/engage-research/knowledge-impact/open-science [last accessed 21 December 2025]. 22 University of Ottawa. 2024. Increasing public access to research: The “open science” transformation at uOttawa. Available from https://www.uottawa.ca/en/news-all/increasingpublic-access-research-open-science-transformation-uottawa [last accessed 21 December 2025]. University of Ottawa Open Science Working Group. 2024. Open science roadmap: Report by the Open Science Working Group, University of Ottawa. University of Ottawa. 47 p. Available from https://ruor.uottawa.ca/items/66db3ab8-8117-4586-9587-926433a818f3 [last accessed 21 December 2025]. Vicente-Saez R., Martinez-Fuentes C. 2018. Open Science now: A systematic literature review for an integrated definition. Journal of Business Research, 88: 428-436. Vines T.H., Albert A.Y.K., Andrew R.L., Débarre F., Bock D.G., Franklin M.T., et al. 2014. The availability of research data declines rapidly with article age. Current Biology, 24(1), 94-97. Wilkinson M.D, Dumontier M., Aalbersberg I.J.J, Appleton G., Axton M., Baak A., et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1): 160018. Wilson G. 2014. Software Carpentry: lessons learned. F1000Research, 3: 62. Available from https://f1000research.com/articles/3-62 [last accessed 21 December 2025]. Zimmerman A.S. 2008. New knowledge from old data: The role of standards in the sharing and reuse of ecological data. Science, Technology, & Human Values, 33(5), 631-652. 23 Table and figure captions Table 1. Nine structural barriers hindering the adoption of open science and open scholarship in academic institutions. Fig. 1. Core components and benefits of open science and open scholarship. Open science and open scholarship encompass a set of interconnected practices that collectively aim to make research design, execution, and dissemination more transparent, accessible, inclusive, and reusable. Community engagement can take many complementary forms, including outreach, partnerships with community organizations, participatory research, citizen science, knowledge co-creation, and public communication. Fig. 2. Multilevel governance model for enabling open scholarship. Effective institutional support for open scholarship requires the integration of both top-down and bottom-up governance mechanisms. Top-down structures, such as national funding mandates, international policy frameworks, and university-level strategies, provide direction, legitimacy, and accountability for openness. Bottom-up dynamics emerging from departments, research groups, community partnerships, centres, schools, and grassroots initiatives, ensure that open scholarship practices are meaningful, discipline-specific, and responsive to local needs. Together, these vertical governance flows reinforce one another to create coherent, institution-wide frameworks in which open scholarship becomes a normalized component of academic practice. 24 Table 1. Nine structural barriers hindering the adoption of open science and open scholarship in academic institutions. Barrier Description Potential Institutional Solutions Evaluation and Incentive Barriers: Misaligned incentives and academic reward structures Evaluation systems prioritize high-impact publications, citations, and grants while undervaluing datasets, opensource software, transparent workflows, communityengaged research, and reproducibility-enhancing practices, making openness professionally risky, especially for early-career researchers. Revise hiring, tenure, and promotion criteria to explicitly recognize and reward open science and open scholarship contributions. Cultural resistance and data hoarding Concerns about being scooped, losing competitive advantage, misinterpretation of data, and unclear authorship or IP norms discourage sharing. These norms contribute to widespread data loss and the accumulation of unpublished or inaccessible 'dark data'. Provide clear guidance on data sharing, authorship, and IP; support protected prepublication sharing; promote leadership and disciplinary norms that value openness. Capacity and Skills Barriers: Limited researcher training Researchers often lack formal training in data management, metadata standards, version control, reproducible workflows, and ethical data sharing, relying instead on ad hoc learning that leads to uneven adoption and quality. Implement structured, institution-wide training across undergraduate, graduate, and faculty development; integrate open science into curricula and professional development. 25 Insufficient cyberinfrastructure and technical support Open scholarship requires repositories, persistent identifiers, metadata standards, storage, and reproducible computing environments that are often fragmented, incomplete, or poorly supported. Invest in integrated institutional cyberinfrastructure linked to national platforms; provide sustained technical and curatorial support for researchers. Governance and Coordination Barriers: Fragmented responsibilities and overreliance on libraries Responsibilities for open scholarship are dispersed across libraries, IT, research offices, ethics boards, and departments, leading to poor coordination, duplicated efforts, and inconsistent guidance. Establish formal coordination mechanisms and shared governance structures that distribute responsibility across relevant units rather than relying primarily on libraries. Policy ambiguity and governance misalignment External mandates from funders, journals, and international bodies are often not translated into clear internal policies, procedures, or accountability mechanisms, resulting in inconsistent compliance. Align institutional policies with external requirements; clarify responsibilities, timelines, and support mechanisms across the research lifecycle. Equity and Access Barriers: Inadequate sensitive data frameworks Research involving human participants, Indigenous knowledge, endangered species, or proprietary data requires secure access models and ethical governance structures that many institutions lack. Develop secure data enclaves, tiered-access systems, and ethical governance frameworks, including Indigenous-led data governance where appropriate.