Open Data Training Workshop: Tri-Agency Research Data Management and Ethical Considerations of Open Data Sharing
Description
<strong>Objective(s):</strong> Momentum for open access to research is growing. Funding agencies and publishers are increasingly requiring researchers make their data and research outputs open and publicly available. However, this introduces many challenges, especially when managing potentially sensitive clinical data.<br /><br />The aim of this 1 hr virtual workshop is to provide participants with foundational knowledge that supports planning for open data in future research projects.<br /><br />Specifically, participants will:<br />1. Gain an understanding of the new Tri-Agency Research Data Management policy and the analogous progress of the University of British Columbia's (UBC) Research Data Management (RDM) strategy and how they can be applied.<br /><br />2. Gain an understanding of the ethical, privacy, and legal considerations of sharing data.<br /><br />3. Learn practical skills for incorporating open data language into REB applications and consent form.<br /><br />Workshop Agenda:<br /><br />1. "Becoming familiar with the new Tri-Agency Research Data Management Policy" - Speaker: Eugene Barsky, Research Data Librarian, UBC Library<br /><br />2. "Ethics and Practical Considerations of Open Data Sharing." - Speaker: Brittney Schichter, Director, Research Integration & Innovation, Provincial Health Service Authority (PHSA) Research and Academic Services<br /><br />This workshop draws on work supported by the Digital Research Alliance of Canada.<br /><br /><strong>Data Description:</strong> Presentation slides, Workshop Video, and Workshop Communication<br /><br />Eugene Barksy: Tri-Agency Research Data Management Policy presentation and accompanying PowerPoint slides.<br /><br />Brittney Schichter: Ethics and Practical Considerations of Open Data Sharing presentation and accompanying Powerpoint slides.<br /><br />This workshop was developed as part of Dr. Ansermino's Data Champions Pilot Project supported by the <a href = "https://alliancecan.ca/en">Digital Research Alliance of Canada</a>.<br />
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Publication Details
DOI
Publisher
Borealis
Subfield
Information Systems
Field
Computer Science
Domain
Physical Sciences
Confidence Score
48%
Source
Scholar Data Model