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Research Data Management at Ryerson University

Introduction to Research Data Management

Ryerson University Library provides services to help you with Research Data Management (RDM). Managing your data throughout the life of a research project may save you time and effort overall. Thinking about organization, storage and security at the beginning of a project can make it easier to work with your data later on and may also help you to meet privacy requirements. Archiving and sharing data can help to reduce duplication of efforts, improve open science, help you meet funder or journal requirements and has even been shown to increase research impact. You can use Data Management Planning as a RDM starting point. 

Data Management Planning

A Data Management Plan is a document that outlines how you plan to manage your data from the beginning to end of your research project.

Data Management Checklist*

Reviewing the questions and concepts outlined below will help you think about important issues related to data management.

  • Data Collection
    • What type(s) of data will be produced?
    • What file format(s) will the data be saved as? Are those file formats proprietary? Will they degrade?
    • Will the data be reproducible?
    • Do you need tools or software to create/process/visualize the data?
    • How much data? 
    • Will it grow?
    • How often will it change?
  • Documentation & Metadata
    • Think about what is needed to make your data 'independently understandable'
    • How will you capture this information over the life of the project?
    • What directory and file naming conventions will be used?
    • Is there a descriptive schema or metadata standard commonly used in your field?
  • Storage & Backup
    • What are the strategies for storage and backup of the data?
    • Use the '3-2-1 Rule': 3 copies, 2 formats, and at least 1 off-site copy
    • Are you aware of backup options at Ryerson?
  • Preservation
    • Think about preservation-friendly, non-proprietary formats.
    • Where will you deposit your data for long-term preservation and access?
  • Sharing & Reuse
    • Think about what data you'll be sharing (raw data, processed data...)
    • Consider what end-user license you might use.
    • How will others learn about your data?
  • Responsibilities & Resources
    • Who in your research group will be responsible for data management?
    • Who controls the data (PI, student, lab, funder)?
    • What resources are required to manage your data?
  • Ethics & Legal Compliance
    • Consider how you'll store and transfer sensitive data securely.
    • Consider how you'll manage secondary use of sensitive data.
    • Can a 'public' (anonymized, de-identified) version of your data be created?
    • How will you manage legal, ethical, and intellectual property issues?

*Copied with permission from Queen's University Library's RDM Libguide.

Archiving and Sharing Research Data

Placing your data into a repository allows it to be saved after the life of a research project and makes sharing easier. There are a variety of repositories suited for different needs. Your repository choice may be based on data requirements, discipline as well as journal and funder requirements. One potential option is the Ryerson University Dataverse. Please consider contacting the Ryerson Library for advice about selecting a data repository. 

Get Help from the Library

The Ryerson Library is here to provide RDM assistance.  We are available to help you with Data Management Planning and archiving you data. Please contact Data Librarian Kevin Manuel at kevin.manuel@ryerson.ca for more information.