Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Research Data Management (RDM): RDM?

This guide explains the what, why and how of Research Data Management at Sheridan College.

What is Research Data Management?

Data Management refers to the storage, access and preservation of data produced from a given investigation. Data management practices cover the entire lifecycle of the data, from planning the investigation to conducting it, and from backing up data as it is created and used to long term preservation of data deliverables after the research investigation has concluded. Specific activities and issues that fall within the category of data management include: File naming (the proper way to name computer files); data quality control and quality assurance; data access; data documentation (including levels of uncertainty); metadata creation and controlled vocabularies; data storage; data archiving and preservation; data sharing and reuse; data integrity; data security; data privacy; data rights; notebook protocols (lab or field). Source: https://casrai.org/term/research-data-management/

A brief guide to research data management

Why is Sheridan developing a RDM policy and strategy?

Sheridan continues its efforts in the implementation of a Research Data Management (RDM) strategy across the college. This policy works to further Canadian research excellence by promoting sound data management and data stewardship practices. Sheridan has chosen to take a broader approach to research data management by ensuring best practices in the management of research data are inclusive of all Scholarship, Research and Creative Activities (SRCA) at Sheridan.

  • enables researchers to meet funding, and publication requirements
  • supports more competitive grant applications to the Tri-Agencies, and other funding agencies
  • ensures researchers get credit for their data and research
  • increases exposure to research data and, and increases its impact and visibility
  • encourages discovery and use of research data to explore new and related research questions
  • improves research data's accuracy, completeness and usability
  • ensures long term preservation of data for future researchers
  • ensures compliance with ethics and privacy regulations and policies
  • enables scrutiny of research findings

The Research Data Lifecycle


 What is research data?

data types word cloud

 

Data that are used as primary sources to support technical or scientific enquiry, research, scholarship, or artistic activity, and that are used as evidence in the research process and/or are commonly accepted in the research community as necessary to validate research findings and results. All other digital and non-digital content have the potential of becoming research data. Research data may be experimental data, observational data, operational data, third party data, public sector data, monitoring data, processed data, or repurposed data.

Source:. CASRAI