Data management is crucial in research because it ensures the integrity, reliability, and accessibility of research findings, ultimately promoting scientific rigor and reproducibility. It also facilitates collaboration, open data sharing, and long-term preservation of research assets.
The visual below shows the different elements needed to create a comprehensive data management plan.
D2R’s Research Data Management Guidelines and Best Practices
This new guide helps D2R-funded projects uphold high standards in data stewardship, aligned with McGill University and Tri-Agency policies.
These guidelines cover research data, software and source code used to produce and process the data and communications materials.
Read the FAQ below to: 1) understand how to implement the guidelines in your project, 2) learn about best practices for data management and sharing, and 3) get answers to common questions about compliance and expectations.
As a D2R funded researcher, what am I required to do?
- Data Management Plans (DMP): Submit a DMP either with your application or within 3 months post-award.
- Data deposit: Deposit all relevant research data, metadata, and code supporting research conclusions in journal publications and preprints into a digital repository.
- Regulatory compliance:
- Follow the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans - 2nd edition (2022) and the Tri-agency Research Data Management Policy (2021).
- Follow the Tri-Agency Framework: Responsible Conduct of Research (2021) guidelines.
- Follow Quebec’s privacy legislations (for example, The Québec Loi 25 (Bill 64) "Act to modernize legislative provisions as regards the protection of personal information").
- Intellectual property: Abide with The McGill Policy on Inventions and Software and the McGill Policy on Copyright.
- Research ethics:
- Human data required ethics board approval (IRB/REB Project Approval).
- Animal research must follow the guidelines of The Animal Compliance Office.
- Data sovereignty: For research conducted by and with First Nations, Métis, and Inuit communities, collectives, and organizations, data management policies, plans and strategies must be developed in collaboration with these entities in accordance with RDM principles or DMP formats that they accept.
- Data security and privacy: Implement strong security measures to safeguard against breaches, illegal access, and other security risks.
The guidelines also provide non-mandatory best practices to support Open Science, long-term usability of data, use of metadata, and responsible data sharing.
What is the responsibility of D2R, funded projects and HeDS in terms of data management?
