Canadian researchers are faced with an unprecedented urgency to share COVID-19 research outputs via data repositories and open access publishers. Many Canadian funding agencies, including the Tri-Agencies (SSHRC, NSERC, and CIHR), have signed the Joint statement on sharing research data and findings relevant to the novel coronavirus (nCoV) and will require funded projects to share their research data widely and rapidly. The World Health Organisation (WHO) also released a statement on “Data sharing for novel coronavirus (COVID-19)”, making it clear that timely sharing of preliminary results and research data is needed. In response, this resource was created by the Portage Network COVID-19 Working Group to enable researchers in Canada to follow international data sharing guidelines for pandemic-related research. You can also download this document as a PDF from the Portage Zenodo Community.
This guide is based on the Research Data Alliance (RDA) COVID-19 Working Group Recommendations and Guidelines for Data Sharing, which were designed to:
- help researchers follow best practices for data sharing in their discipline, and
- help researchers maximize the impact of their work.
The guidance provided here has been streamlined to make it as straightforward as possible. Follow the links provided for more in-depth information and reach out to librarians at your institution to see if further support is available. Many Canadian universities have dedicated research data librarians who can help you to better understand these guidelines.
How do I Prepare Research Data for Sharing and Deposit?
- Plan to Share
- Make Your Data Understandable
- Make Your Data Open and FAIR
- Protect the Privacy of Research Participants
- Help Others Discover and Use Your Data
Plan to Share
RDA Guidance: Researchers should create a Data Management Plan (DMP) at the beginning of the research process so that it can be included in the work plan and the budget (2.2.4 Data Management Planning, p. 17).
- Create a Data Management Plan (DMP) at the start of your project and update it as the project evolves. Use one of the templates available in the Portage DMP Assistant to get started.
- Looking at DMPs published by others may also be helpful in developing your own. The Digital Curation Centre’s Example DMPs and Guidance is a good place to start.
Make Your Data Understandable
RDA Guidance: Research outputs need to be documented, which includes documentation of methodologies used to define and construct data, data cleaning, data imputation, data provenance and so on. Software should provide documentation that describes at least the libraries, algorithms, assumptions and parameters used (2.2.6 Documentation, p. 19).
- Organize your files using well-documented file naming conventions.
- Check out UBC’s guidance on organizing research data for examples of simple file naming strategies.
- Provide documentation and supporting information, which may include describing your data workflow and methodologies in a codebook or README file.
- Learn more about preparing appropriate research data documentation with Portage’s Documentation and Supporting Materials Required for Deposit.
- Identify and properly cite any secondary data used in your research.
Make Your Data Open and FAIR
RDA Guidance: Research outputs should align with the FAIR principles, meaning that data, software, models and other outputs should be Findable, Accessible, Interoperable and Reusable (2.2.3 FAIR and Timely, p. 17).
- Familiarize yourself with the FAIR principles with this checklist: How FAIR are your data?
- Get permission to share:
- If your data were originally generated or collected by a third party, do you have permission and the rights to redistribute them?
- Be aware that data collected from Indigenous participants, or on Indigenous lands, can only be deposited after consultation with community leaders.
- Understand that data from human participants must be de-identified prior to deposit if respondents were promised confidentiality, and consent must be obtained. Share only what participants have agreed to share. (Need help figuring out what you can share? Jump to the next section on Protecting the Privacy of Research Participants.)
- Share your data using an open license:
Making your data FAIR can be a big undertaking. It may be useful to hire a research assistant or train someone on your team to manage permissions and licenses. If you have questions about licensing your data, you may also want to contact your institution’s copyright officer.
Protect the Privacy of Research Participants
RDA Guidance: Access to individual participant data and trial documents should be as open as possible and as closed as necessary, to protect participant privacy and reduce the risk of data misuse. [Executive Summary, p. 7].
Although the FAIR principles above outline an ideal of openness, research with human participants may require you to hold back some data or edit it before sharing. The following guidance documents will help you understand how to prepare your data to share. For help understanding any terms used in this section, please see Portage’s Glossary of Terms for Sensitive Data Used for Research Purposes.
- Prepare consent forms that describe what data will be shared. For examples of informed consent language that allows for data sharing, or precludes it, please see Portage’s Research Data Management Language for Informed Consent. The ICPSR also has some helpful tips for developing consent form language in their Recommended Informed Consent Language for Data Sharing.
- How does your consent form control what data you can share? Do you understand what your consent form language allows or prohibits? We recommend starting with Portage’s decision tree Can I Share My Data? You may also wish to review Portage’s Human Participant Research Data Risk Matrix for more information.
If there may be restrictions on what you can share, follow Portage’s De-identification Guidance to protect the privacy of research participants and reduce the risk of harm.
Help Others Discover and Use Your Data
RDA Guidance: Data should be deposited in data repositories...widely used disciplinary repositories are recommended for maximum accessibility and accessibility of the data, followed by general or institutional repositories… By providing persistent identifiers, demanding preferred formats, rich metadata, etc., certified trustworthy repositories already guarantee a baseline FAIRness of and sustained access to the data, as well as citation (2.2.7 Use of Trustworthy Data Repositories, p. 19).
- Describe your data using a metadata standard that works best for your discipline. Check out this list put together by the Digital Curation Centre.
- Save your data in appropriate data formats for preservation. Consult OpenAIRE’s Guides for Researchers: Data Formats for Preservation.
- Deposit your data and all associated documentation in a recognized repository. Consult Portage’s Recommended Repositories for COVID-19 Research Data.
This guide is modelled on the previous work of Tayler and Ripp (2020) FAQ: COVID-19 Rapid Response Data Sharing and Deposit Support. Scholars Portal Dataverse. https://doi.org/10.5683/SP2/522KV2.