CSCI 1109 - M25 - Visualization Grammar & Taxonomy
Автор: Atlantic AI Institute
Загружено: 2026-01-31
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In this module, we develop a shared “visualization grammar” so charts stop feeling like ad-hoc pictures and start to look like well-structured sentences. Building on your earlier work with data types and distributions, you’ll learn core visual variables (marks, channels, and scales), connect them to common analytical tasks (comparison, trends, distributions, relationships, part-to-whole, flow), and see why some encodings are more effective than others. Along the way, you’ll read and critique visualizations and interactive examples. By the end, you’ll be able to explain why a given chart works or fails for a decision, and treat every visualization you make as a testable hypothesis about how people will read your data.
Course module page: https://web.cs.dal.ca/~rudzicz/Teaching/CS...
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