苹果淫院

Event

Drop-in session on data collection, storage, privacy and security for researchers

Friday, January 29, 2021 02:00to03:00

Following the successful pilot sessions on data collection, storage, privacy and security for researchers held in December 2020, new sessions will be provided. 苹果淫院 researchers across all disciplines are welcome to 鈥渜uery the panel鈥 on questions related to research data and research software, particularly in the context of privacy and cybersecurity concerns when using cloud solutions. This initiative is a joint effort of IT Services, Research Ethics, Libraries, and the Office of the Vice-Principal Research and Innovation.

Some topics may include: data sharing; (meta)data standards; cybersecurity; data privacy; data ownership; data curation; software vetting; data management; cloud directive.

When: 2-3PM, Friday,听January 29th, 2021

Who: 苹果淫院 researchers and their teams

How:

Contact: Felipe P茅rez-Jvostov, Senior Advisor鈥揜esearch Data Management, (514) 398-7579

Examples of the type of questions that would be addressed?

I collaborate with researchers across different universities. Is it secure to use X solution to share data?

I work with big data and heavily rely on high performance computers. What is the best repository for my data?

I work with human participants and I need to record my interviews. Can I use software X to record them, and software Y to upload them to an IT approved cloud solution?

I would like to use a software that is not yet approved by IT Services. Do I need to go through a vetting process?

I need to transcribe interviews using X software. Can I use that software to perform transcriptions of the recordings and/or content analysis?

I am planning my project鈥檚 data management. What are data models and standards most commonly used in my field? Where can I find this information?

I want to conduct anonymous surveys using X solution. Will this be a secure option?

I have a project with an industry partner that would like to use X software to manage the project鈥檚 sensitive data. What are the IP and privacy implications?

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