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Introduction to Best Practices for Creating Infographics Online
- What: Learn to use best practices to create infographics, which are a specific type of data visualization that uses a mix of data, visuals, and text to inform or persuade.
- Why: Learning infographic creation skills and tools will help you promote yourself and your research findings, more effectively communicate with wide audiences, and make you stand out in the job market.
- Who: This workshop is designed for those new to infographics. Skills gained can help participants from any discipline: Humanities, Social Sciences, or Sciences. There are no prerequisites or assumptions of knowledge of statistics or programming.
- How: This is a 1-hour online workshop, consisting of a lecture, followed by an activity (done individually), where we critique and discuss an example infographic. There are no breaks.
- Where: Online via Zoom link (provided upon registration). [Also available In-Person on a different day/time.]
- When: Tuesday, October 29, 2-3pm.
- Code of Conduct: Map & Data Library (MDL) workshops are a welcoming and inclusive environment for learning. To learn more, check out our Code of Conduct.
- Accessibility: The MDL is committed to making our workshops accessible to everyone. If you require an accommodation to fully participate in the workshop, please contact Kelly Schultz (kelly.schultz@utoronto.ca) to discuss options.
- Complementary Learning Materials: Check out our Getting Started Guide for a recording of this workshop, more tutorials, and online data visualization courses.
Join your peers to meet new people and learn new skills in a welcoming and encouraging environment!
- Date:
- Tuesday, October 29, 2024
- Time:
- 2:00pm - 3:00pm
- Time Zone:
- Eastern Time - US & Canada (change)
- Online:
- This is an online event. Event URL will be sent via registration email.
- Categories:
- Data & Statistics
Registration has closed.
Event Organizer
Kelly Schultz
Kelly Schultz (she/her) is a Data Librarian at the Map & Data Library. She has a BASc (Computer Engineering) and a MI, both from UofT.
She supports Data Visualization; Qualitative Data Analysis; Data Cleaning; Text and Data Mining; Network Visualization and Analysis; Finding Data.
Map & Data Library