This interactive workshop builds on foundational concepts covered in the first session, Foundations of Data Visualization: Theory and Techniques. Scheduled three weeks later to allow time for individual practice, this session provides an opportunity for participants to workshop their own data visualizations. Participants will engage in discussions about their data visualizations, receive and provide constructive feedback, and develop strategies to make their library data more accessible and impactful.
By the end of this session, attendees will be able to:
Apply visualization techniques to create compelling and effective representations of library data
Critically evaluate and refine your visualizations through peer feedback and iteration
Develop an approach to using visualization tools and techniques tailored to your specific data and goals
Jordan Packer (she/her) is a data analyst and educator based in Brooklyn, NY. As the Senior Data Analyst for the Assessment Program at Columbia University Libraries, Jordan leads library assessment and analytics initiatives, supports colleagues in their own assessment projects, and collaborates with staff to effectively build data analysis tools. Additionally, Jordan serves as a part-time faculty member at the Parsons School of Design, where she teaches undergraduate courses, such as Information Visualization and Politics and Ethics of Design.