Kailyn MacKinnon

Background: Biomedical funders are increasingly introducing requirements for research data management (RDM) and data sharing to promote transparency and reproducibility. However, expectations for Data Management and Sharing Plans (DMSPs) and data sharing are heterogeneous and may create uncertainty and an administrative burden for researchers. Objective: In this study, we aimed to: (1) identify DMSP and data sharing requirements from biomedical funders; (2) identify how these requirements are evaluated, monitored, and supported; (3) identify existing DMSP templates used by funders; and (4) compare and assess the existing required elements for the DMSPs and how they were developed. Design: We conducted a scoping review using the Joanna Briggs Institute approach. We searched websites of 287 biomedical funders (private, philanthropic, and hybrid funders) listed on www.healthresearchfunders.org (March-August 2024) for policies, guidelines, templates, or general guidance related to RDM and data sharing. Screening and data extraction were conducted in duplicate, and data were analyzed descriptively and thematically. Results: Of 287 funders screened, 264 were eligible, and 196 documents from 84 funders were included. Sixty-five funders (25%) have explicit DMSP expectations, 76 (29%) expect data sharing, and 31 (12%) cover RDM costs. Expectations were more common among public funders (63% DMSP; 66% data sharing) than philanthropic funders (10% and 15% respectively). Regionally, requirements were most frequent in Asia (40%) and North America (32%). Nearly half of funders with DMSP policies described evaluation (49%) or monitoring (43%) processes, but approaches varied. Where expected, templates or guidance were common (86%), but the level of detail and the number of required elements differed widely. Conclusions: Our results show that biomedical funders’ expectations for DMSPs and data sharing by researchers are expanding but remain inconsistent, with considerable variation in evaluation, monitoring, and guidance. While our analysis relied on publicly available documents and did not include commercial funders, the findings highlight the need for greater harmonization, participatory template development, and clearer monitoring processes to reduce the burden on researchers and improve the impact of the policies on open and reproducible science.

In March 2021, Canada’s three federal research funding agencies introduced the Tri-Agency Research Data Management (RDM) Policy, with the objective of promoting sound RDM and data stewardship practices at research institutions. Among the requirements of the Policy, each post-secondary institution and research hospital eligible to administer agency funds was required to publish an institutional RDM strategy. This study presents a cross-sectional mapping of published institutional strategies ( n = 211) in response to the Tri-Agency RDM Policy requirement. We extracted information pertaining to institutional characteristics, institutional needs, and support models for data management planning and data deposit. Our analysis of institutional strategies indicates that developing RDM expertise among researchers (84%, n = 177) and research support staff (61%, n = 129) is of high priority. We also found that most institutions did not describe activities to promote behavioural changes and foster a broader culture of RDM among researchers; only 6% of institutional strategies ( n = 12) explored shifting incentives and rewards. A mapping of institutional RDM strategies is an important step to identify potential gaps in responding to the Policy. We find that further efforts are needed to address consultation gaps, resource constraints, and support for data management plans and data deposit to foster a robust and effective RDM culture at Canadian research institutions.

In March 2021 Canada’s three federal research funding agencies introduced the Tri-Agency Research Data Management (RDM) Policy, with the objective of promoting sound RDM and data stewardship practices at research institutions. Among the requirements of the Policy, each post-secondary institution and research hospital eligible to administer agency funds was required to publish an institutional RDM strategy. This study presents a cross-sectional mapping of published institutional strategies (n=211) in response to the Tri-Agency RDM Policy requirement. We extracted information pertaining to institutional characteristics, institutional needs, and support models for data management planning and data deposit. Our analysis of institutional strategies indicates that developing RDM expertise among researchers (84%, n=177) and research support staff (61%, n=129) is of high priority. We also found that institutions did not describe activities, such as shifting incentives and rewards (6%, n=12), to incite behavioural changes and foster a broader culture of RDM among researchers. A mapping of institutional RDM strategies is an important step to identify potential gaps in responding to the Policy. We find that further efforts are needed to address consultation gaps, resource constraints, and support for data management plans and data deposit to foster a robust and effective RDM culture at Canadian research institutions.***En mars 2021, les trois organismes fédéraux de financement de la recherche du Canada ont mis en place la Politique des trois organismes sur la gestion des données de recherche (GDR), en vue de promouvoir de bonnes pratiques de GDR et d’intendance des données dans les établissements de recherche. Entre autres exigences de cette politique, chaque établissement postsecondaire et hôpital de recherche admissible à administrer des fonds attribués par les organismes était tenu de publier une stratégie institutionnelle de GDR. Cette étude présente une schématisation transversale des stratégies institutionnelles publiées (n = 211) en réponse à l’exigence de la Politique des trois organismes sur la GDR. Nous avons extrait des renseignements sur les caractéristiques institutionnelles, les besoins institutionnels et les modèles de soutien pour la planification de la gestion des données et le dépôt des données. Notre analyse des stratégies institutionnelles indique que le développement de l’expertise en GDR chez les chercheurs (84 %, n = 177) et le personnel de soutien à la recherche (61 %, n = 129) est une priorité élevée. Nous avons également constaté que les établissements ne décrivaient pas d’activités, comme la réorientation des mesures incitatives et des récompenses (6 %, n = 12), pour susciter des changements de comportement et favoriser l’élargissement de la culture de la GDR chez les chercheurs. La schématisation des stratégies institutionnelles de GDR est une étape importante pour cerner les lacunes potentielles dans la réponse à la politique. Nous estimons que des efforts supplémentaires sont de mise pour combler les lacunes en matière de consultation, remédier aux contraintes budgétaires et soutenir les plans de gestion des données et le dépôt de données afin de favoriser une culture de GDR solide et efficace dans les établissements de recherche canadiens.