Qualitative Data: Practices for RDM Planning and Sharing Online
Qualitative methods let us share nuanced interpretations of multifaceted issues. They let us understand lived experiences and motivations, see a research question from different standpoints, and highlight contexts. Qualitative research data can take the form of interview transcripts, oral histories, focus groups, field notes, audio, video, and more. Some qualitative researchers are accustomed to research data management (RDM) and data sharing, while others are less familiar.
This workshop welcomes both groups to learn about best practices and considerations for managing and sharing quantitative data. We’ll start with practical skills and workflows, and then move on to a discussion about hesitations and urgencies. Qualitative research often grows out of relationships of trust, and information is deeply contextual, making data sharing sticky. However, communities are often approached by different researchers for similar information, and data sharing can also help alleviate research fatigue. Let’s learn and unpack together!
*Presented by Danica Evering (Research Data Management Specialist). The virtual presentation by Danica Evering will be recorded and shared on the Sherman Centre's website. The discussion section of the event, however, will NOT be recorded or shared.
- Wednesday, April 5, 2023
- 10:30am - 11:30am
- Time Zone:
- Eastern Time - US & Canada (change)
- This is an online event. Event URL will be sent via registration email.
More information on Sherman Centre Events can be found on the SCDS Events page.
CODE OF CONDUCT
The Sherman Centre and the McMaster University Library are committed to fostering a supportive and inclusive environment for its presenters and participants. As a participant in this session, you agree to support and help cultivate an experience that is collaborative, respectful, and inclusive, as well as free of harassment, discrimination, and oppression. We reserve the right to remove participants who exhibit harassing, malicious or persistently disruptive behaviour. Please refer to our code of conduct webpage for more information.
Research Data Management