ATLS 3519: Vis Introduces principles and methods of using quantitative information as material for design. Trains artists to captivate and/or persuade audiences using data within client communication or mass media. Surveys the design landscape of professional dashboards, data art, and data-driven journalism to discuss how audience needs impact visualization form. Delves into perceptual psychology to evaluate what makes one visualization more effective than others. Explores the history of visualization practice and examines philosophies underlying various approaches. Students will design client-facing visualizations for their final project. Other special topics include animated visualizations, data comics, or quantified self. No previous experience in statistics is necessary. Students who successfully complete this course will be able to: Critical Thinking & Theory / History: ● Apply both psychological and philosophical perspectives to information design ● Discuss the development of creative movements within data visualization ● Discuss ethical perspectives on the communication of empirical data ● Critique visualizations with the relevant vocabulary and concepts ● Intelligently break the ‘rules’ of best principles when appropriate Design/Creative: ● Tackle common design challenges in visualization design ● Develop a personal taste for what constitutes ‘good’ visualization design ● Put creative spins on basic chart techniques ● Tell engaging stories with data ● Leverage interaction techniques for online visualizations Technical: ● Explore datasets and create interactive visualizations using Tableau ● Create vector-based data illustrations using RAWGraphs and Illustrator Course material: Textbook: Storytelling with Data by Cole Nussbaumer-Knaflic ​ ​ - Additional readings and tutorials will be assigned - Guest lecturers will join in through Skype Weekly plan (Practice with Tableau will happen daily): ​ ​ Week 1: Foundations ​ ​ A. History of visualization We will have some fun discussing early work by Florence Nightingale and W.E.B. Du Bois. B. Terminology & techniques Review graphical and statistical vocabulary, such as: measure, category, axes, marks, ticks, scales, maps, filters, aggregation. We will explore various chart techniques. C. Perception of basic charts Through peer-reviewed research, we will discuss how function affects the forms of line charts, bar charts, scatter plots and pie charts. D. Professional practices We will critique contemporary examples selected from: -Journalistic media, where communication is framed by an expectation of objectivity -Decision-making contexts, where communication is framed by an expectation of efficiency Key practitioners discussed this week include Florence Nightingale, W.E.B. Du Bois, Edward Tufte, Steven Pinker, Hans Rosling, Al Gore, Alberto Cairo, and Nate Silver. Week 2: Creative practice A. Cognition, rhetoric, and ethics We will review concepts of cognitive load and bias, and how they impact attention and persuasion. B. Data art and society We will critique selections of data-driven artwork from The Museum of Modern Art. Questions will be asked and (possibly) answered, such as: What is data art? Why do they exist? Do we need more of them? Are they applicable in everyday design practice? C. Data exploration practicum Students will each explore a dataset with Tableau and prepare for next week’s studio sessions. Key practitioners discussed this week include Nigel Holmes, Georgia Lupi, Stefanie Posavec, Mona Chalabi, XKCD, Martin Wattenberg, and Fernanda Viegas. Week 3: Studio Possible final projects, depending on student’s technical expertise: Create an Instagram account with at least 6 data sketches Create a single-page interactive visualization with D3.js Create a full-page infographic with Adobe Illustrator .