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Research Data Management

From data collection to data sharing and archiving, Research Data Management is an essential component of modern research and scholarship. The DRS team supports McGill researchers in preparing Data Management Plans for their grant or REB applications, identifying the best storage solution for their data, as well as suggesting means for sharing their research data for further discovery. 

 

Available services and support

         Sharing Research Data

 


Data Management Planning

A data management plan (DMP) is a formal document created at the onset of a research project to describe how data will be collected, documented, stored, and shared. A DMP is a living document that requires regular review, and therefore should be updated throughout the lifecycle of a research project. Creating a DMP is also considered a best practice in contemporary research and can help researchers organize their research process, determine resource requirements, implement appropriate documentation and file formats for data storage and accessibility, while mitigating potential security and privacy concerns.

The DRS team can help McGill researchers to prepare their DMPs and identify the best solutions in terms of storage, security, or data standards. 

Many research grant applications already require a DMP and we anticipate a DMP becoming a standard component of most grant applications in the future. To assist you in developing a DMP for a grant application, we suggest starting with the Portage DMP Assistant, a bilingual tool for preparing data management plans. You may create an account with your McGill email.


For examples and templates of DMPs visit McGill Library
 

DMP Requirements by Funding Agency

FUNDER

POLICY DESCRIPTION EFFECTIVE DATE
SSHRC
CIHR
NSERC
Tri-Agency
Research Data Management Policy

All grant proposals submitted to the agencies should include methodologies that reflect best practices in RDM.

For certain funding opportunities, the agencies will require DMPs to be submitted to the appropriate agency at the time of application, as outlined in the call for proposals; in these cases, the DMPs will be considered in the adjudication process.

By 2022
Genome Canada Genome Canada Data Release and Sharing Policies

Must provide a Data Release and Resource Sharing Plan as part of the application.

“Funds will not flow until an acceptable plan has been approved and incorporated into the terms of award.”

Specific requirements may apply in certain programs’ applications.

2017-01-01
FRQ NA NA NA
NIH Final NIH Policy for Data Management and Sharing

A DMP (no more than 2 pages) should reflect the proposed approach to manage and share scientific data at the time it is prepared. DMP should be updated during the course of the award/support period.

Should be submitted at the time of application.

After the end of the funding period, non-compliance with the NIH ICO-approved DMP may be taken into account by NIH for future funding decisions for the recipient institution.

2023-01-25
NSF NSF Grant Proposal Guide on Contents of the DMP

The DMP (no more than 2 pages) “should describe how the proposal will conform to NSF policy on the dissemination and sharing of research results”.

DMP should be submitted as a supplementary document in the application.

2011-01-18
Horizon 2020 H2020 Online Manual

Must submit a first version of the DMP (as a deliverable) within the first 6 months of the project.

Updates to the DMP are required over the course of the project whenever significant changes arise and at the time of the project’s periodic evaluation/assessment.

DMP template and instruction can be found here.

2017
    Table last updated on: 2021-03-24  

 


Sharing your research data

Sharing the underlying data of a publication may be a requirement of a funding agency or a publisher. While not all data can be publicly shared (e.g., protected or regulated data containing personally identifiable information, for example, cannot be routinely shared), it is good practice to share research data in a reputable research data repository to maximize its discovery and reuse. 

The DRS team can help McGill researchers navigate ethical and privacy regulations when publishing their data, as well as identify the best repository for their specific data and research area.
 

McGill Dataverse

The McGill University Dataverse is a multi-disciplinary institutional repository for research data open to all McGill faculty, students, and staff. Files are held in a secure environment on Canadian servers. This repository is ideal for small to medium-size datasets (supports file sizes smaller than 3 GB).
 

Federated Research Data Repository (FRDR)

The Federated Research Data Repository is a national platform to deposit and discover Canadian research data. The McGill Dataverse is indexed in FRDR's discovery service. This repository is ideal for large-size datasets (supports file sizes larger than 3 GB).


If you are working with sensitive data we encourage you to contact us to identify the best solutions for your particular case, and ensure compliance with all applicable regulations.

 

Data Sharing Requirements by Funding Agency

Funder Policy Description Effective Date
SSHRC Research Data Policy All research data collected with he use of SSHRC funds must be preserved and made available for use by others within a reasonable period of time" (Within 2 years of the completion of the research project for which the data was collected). 2016-12-09
CIHR Tri-Agency Open Access Policy on Publication  Recipients of CIHR funding are required to "deposit bioinformatics, atomic, and molecular coordinate data into the appropriate public database (e.g., gene sequences deposited in GenBank) immediately upon publication of research results.

For further information and examples of research outputs and their corresponding repositories visit the Annex.
2018-01-01
NSERC NA NA NA
Genome Canada Genome Canada Data Release and Sharing Policies Approved Genome Canada projects must address the sharing of resources generated by the projects such as unique biological specimens and computer programs designed to analyze datasets.

Data must be made available at the time of publication of the research project.

Large datasets collected over several periods of time can be shared in phases or as data becomes available.
2017-01-01
FRQ NA NA NA
NIH Final NIH Policy for Data Management and Sharing

NIH Data Sharing Policies
Specific data sharing policies apply depending on the specific IC, division, and program levels at the NIH.

In general, research data should be publicly available when possible, while safeguarding the privacy of participants, and protecting confidential and proprietary data.

Data should be shared no later than the associated publication or at the end of the performance period, which ever comes first.
2023-01-25
NSF NSF Data Sharing Policy Researchers are expected to share their data at no more than incremental cost, and within a reasonable time. This includes primary data, samples, physical collections and other supporting materials created or gathered in the course of work under the NSF Grant. 2020-06-01
Horizon 2020 H2020 Manual The beneficiaries must deposit and take measures for third parties end-users to access, mine, exploit, reproduce and disseminate the research data free of charge.

The research data include data and metadata needed to validate the results presented in scientific publications. Other data can also be provided by the beneficiaries on a voluntary basis, as stated in their Data Management Plans.

Opting out from data sharing is possible at any stage of the project. “A proposal will not be evaluated more favourably if the consortium agrees to share its research data, nor will it be penalised if it opts-out.”
2017
    Table last updated on: 2021-03-24  

 For funders not listed above, you may find information on funders' policies and requirements on open access and data archiving in Sherpa Juliet database.

 


Consultations

The DRS team is available to guide researchers on all things related to Research Data Management. You can book a meeting with a specialist to discuss your specific needs.

drs [at] mcgill.ca (subject: RDM%20Consultation) (Book a consultation )

 


 

Training

There are many learning resources and ongoing training opportunities on topics related to Research Data Management. Please consult our DRS Training section for a complete list of partners and resources.

If you have any questions related to research data management

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