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Research Data Management

Choosing Where to Deposit

Canadian Research Data Repositories

  Scholars Portal Dataverse Federated Research Data Repository (FRDR)
UWinnipeg data repository? Yes, University of Winnipeg Research Data Repository No
Maximum File Size Maximum of 3 GB pre upload Any size
Location of Data Servers Ontario, Canada Canada
Creates DOIs Yes Yes
File types accepted All All
Versioning Yes, updating datasets is easy and users can track and download older versions of your data. Updating difficult and only the most recent version kept
Control access* Files and datasets can be restricted or embargoed but data are intended to be made open and accessible. Temporary embargo available but all files must eventually be made openly available.
Ability to collaborate with research team Yes Yes
Specialized or discipline specific metadata General and specialized citation and description fields for Social Sciences, Geosciences, Health and Life Sciences, and Astronomy Default, general standards for data description with the ability to request custom metadata fields and discipline specific web forms.
Discoverability DataCite, FRDR, Google, ORCID DataCite, Google, OpenAIRE
FAIR Compliant Data curated to meet FAIR Principles Data curated to meet FAIR Principles

*Neither repository option is suitable for sensitive research data at this time.

Other Research Data Repositories

Dryad

The Dryad Digital Repository is a curated resource based in the United States that makes research data discoverable, freely reusable, and citable. Dryad provides a general-purpose home for a wide diversity of data types and allows up to 10GB per file and 300 GB per data publication. Review Dryad's Submission & Publication Process and FAQs for more details.

Discipline Specific Repositories

Registry of Research Repositories: There are hundreds of research data repositories across Canada and thousands around the world. If the above options do not meet your needs, talk to your colleagues about discipline/subject specific data repositories and browse the Registry of Research Repositories at re3data.org.

Nature's Scientific Data Data Repository Guidance: Scientific Data recommends data be submitted to discipline-specific, community-recognized repositories where possible. Their Data Repository Guidance list "is intended as a guide for those who are unsure where to deposit their data, and provides examples of repositories from a number of disciplines. The repositories on this list met all of the journal’s data hosting requirements at the time of listing. As of 2021, this list will not be expanded further and therefore the use of an alternative data repository is not precluded, provided it meets the above stated criteria."

Selecting data for preservation

Prioritize data for deposit and sharing by assessing:

  • uniqueness or rarity of the data
  • historical significance or value of the data
  • how well the data supports your published (or soon to be published) research
  • the data sharing requirements of your funder or publisher

The following are general guidelines to consider when deciding what research data to deposit in a data repository:

YES

  • Original datasets and raw data that cannot be regenerated
  • Non-original datasets that are not easily available online and you have permission to share
  • Documentation to understand/interpret raw data: codebooks, study descriptions, ReadMe files, consent forms, and summary statistics (especially for social science data)

MAYBE

  • Intermediate versions of analyses that were used in your publication(s) that may be useful to others
  • Output files from analyses that are difficult or time consuming to recreate from the original data

UNNECESSARY

  • Incomplete, non-functional, or intermediate versions of code that are marginally useful to others,
  • Charts and graphs that can be easily created from original data
  • Output files from analyses easily recreated from original data

NO

  • Data containing personal identifying information of human subjects
  • Data concerning First Nations, Metis, and/or Inuit people and/or communities without their permission and control

Sample Language to Deposit and Share Data

Including RDM Language in Grant Proposals

Granting agencies are increasingly investing in projects that have demonstrated data management planning in their proposals. The following is a generic example but the more specific details you can provide the better.

Sample Language:

"Our team is committed to best practices in Research Data Management and strictly adheres to the ethics and research policies of the University of Winnipeg as to the management of our research data. With respect to storing data collected, we will use secure data storage options and security measures that are most appropriate for the sensitivity level of the data. After the project is concluded, the research outputs from this project will be shared via a general research data repository such as Scholars Portal Dataverse, or a domain-specific repository such as ________, which will further broaden the reach of the research outputs of this project."

Informed Consent Language

Participant consent and information materials should include future use of data. Participant consent is required in order for data to be shared and used beyond the scope of the immediate project. The following are examples of language for participants to consent to the reuse of their quantitative or qualitative data:

Quantitative: "By participating in this research, I hereby consent to my de-identified information be used for research purposes beyond this immediate project"

Qualitative: “De-identified transcripts and/or summaries of interviews will be deposited in the University’s Research Data Repository, to gain access, researches will have to get approval by the principle investigator and/or organization and transcripts will be redacted or summarized so researchers will gain a general idea of what was said but may not have access to the exact words”

Resources

Recommended Informed Consent Language for Data Sharing (ICPSR): This guide includes: language to avoid, model language, known concerns and recommended alternatives and conventional language used in the past.

Copyright

Databases Terms of Use