This Murrow College of Communication seminar focuses on understanding and using the principles of information graphics and basic data visualization. This is where you will find the course schedule and updated links to assignments and readings.<\/p>\n
Week 1: What is data visualization?<\/span><\/p>\n Aug. 22-28 |<\/strong> Definitions, examples, types of charts<\/p>\n Readings:<\/strong> Lessons:<\/strong> Assignments:<\/strong> Week 2: Data through history<\/span><\/p>\n Aug. 29-Sept. 5 |<\/strong> History of information graphics, collecting and questioning data<\/p>\n Readings:<\/strong> Lessons:<\/strong> Assignments:<\/strong> Week 3: What to do<\/span><\/p>\n Sept. 5-11 |<\/strong> Best practices for information graphics, anatomy of a chart, Edward Tufte<\/p>\n Readings:<\/strong> Lessons:<\/strong> Assignments:<\/strong> Monday is a university holiday for Labor Day. Assignments will be posted Tuesday to avoid confusion with the previous week’s assignments.<\/em><\/p>\n Week 4: What not<\/em> to do<\/span><\/p>\n Sept. 12-18 |<\/strong> Chartjunk, bad charts, optical illusions and deceptions<\/p>\n Readings:<\/strong> Lessons:<\/strong> Assignments:<\/strong> Week 5: Pie charts and beyond<\/span><\/p>\n Sept. 19-25 |<\/strong> The case against pie charts, part-to-whole alternatives<\/p>\n Readings:<\/strong> Lessons:<\/strong> Assignments:<\/strong> Week 6: Professional Approaches<\/span><\/p>\n Sept. 26-Oct. 2 |<\/strong> Professional standards, trends and controversies<\/p>\n Readings:<\/strong> Lessons:<\/strong> Assignments:<\/strong> Week 7: Midterms<\/span><\/p>\n Oct. 3-9 |<\/strong> Presenting projects<\/p>\n Readings<\/span> Lesson (only one this week):<\/strong> Assignments:<\/strong> Week 8: Maps<\/span><\/p>\n Oct. 10-16 |<\/strong> Basic cartography and mapping principles<\/p>\n Readings:<\/strong> Lessons:<\/strong> Assignments:<\/strong> Week 9: Geography Without Maps<\/span><\/p>\n Oct. 17-23 |<\/strong> When geographic data is better off without a map<\/p>\n Readings<\/strong> Lessons:<\/strong> Assignment:<\/strong> Week 10: Beyond Bars & Lines<\/span><\/p>\n Oct. 24-30 |<\/strong> A look at flowcharts, tree diagrams, illustrations and other forms<\/p>\n Reading<\/strong> Lessons:<\/strong> Assignment:<\/strong> Week 11: Interactivity<\/span><\/p>\n Oct. 31-Nov. 6 |<\/strong> Principles of interactive design and user experience<\/p>\n Readings<\/strong> Lessons:<\/strong> Assignments:<\/strong> Week 12: Charts Online<\/span><\/p>\n Nov. 7-13 |<\/strong> History of charts on the Internet and technological limitations<\/p>\n Readings:<\/strong> Lessons: <\/strong> Assignment: <\/strong> Week 13: The Guided Experience<\/span><\/p>\n Nov. 14-20 |<\/strong> Guided vs. exploratory graphics, the annotation layer<\/p>\n Readings:<\/strong> Lessons: <\/strong> Assignment: Visualizing Poll Data<\/a><\/p>\n Thanksgiving Break: Nov. 21-25<\/span><\/p>\n Week 14: Future of Graphics<\/span><\/p>\n Nov. 28-Dec. 4 |<\/strong> Pushing the boundaries and innovative new forms<\/p>\n Readings:<\/strong> Lessons:<\/strong> Assignment:<\/strong> Personal Data Project Draft<\/a><\/p>\n Week 15: Closed Week<\/span><\/p>\n Dec. 5-11 |<\/strong> Sharing the Personal Data Projects<\/p>\n Readings:<\/strong> Lesson:<\/strong> Assignment:<\/strong> Week 16: Finals Week<\/span><\/p>\n Dec. 12-16 |<\/strong> No lecture or exams<\/p>\n The final project is due on Wednesday, Dec. 14. All late or missing assignments are accepted for partial credit until Friday, Dec. 16, at 11:59 p.m.<\/p>\n","protected":false},"excerpt":{"rendered":" This Murrow College of Communication seminar focuses on understanding and using the principles of information graphics and basic data visualization. This is where you will find the course schedule and updated links to assignments and readings. Week 1: What is data visualization? Aug. 22-28 | Definitions, examples, types of charts Readings: \u2022 Data + Design… Read more »<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-3245","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/murrowcourses.com\/graphics\/wp-json\/wp\/v2\/pages\/3245","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/murrowcourses.com\/graphics\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/murrowcourses.com\/graphics\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/murrowcourses.com\/graphics\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/murrowcourses.com\/graphics\/wp-json\/wp\/v2\/comments?post=3245"}],"version-history":[{"count":6,"href":"https:\/\/murrowcourses.com\/graphics\/wp-json\/wp\/v2\/pages\/3245\/revisions"}],"predecessor-version":[{"id":3332,"href":"https:\/\/murrowcourses.com\/graphics\/wp-json\/wp\/v2\/pages\/3245\/revisions\/3332"}],"wp:attachment":[{"href":"https:\/\/murrowcourses.com\/graphics\/wp-json\/wp\/v2\/media?parent=3245"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\n\u2022 Data + Design<\/em> Foreword<\/a> and Chapter 1<\/a> and Chapter 2<\/a>
\n\u2022 Designing Data Visualizations<\/em> Chapter 1<\/a> (first half only; you can stop at “Exploration versus Explanation”)<\/p>\n
\n• Course Introduction<\/a>
\n• What is Data Visualization?<\/a><\/p>\n
\n• Syllabus Visualization<\/a>
\n• Scavenger Hunt<\/a><\/p>\n
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\n\u2022 The Surprising History of the Infographic<\/a> (Smithsonian Magazine)
\n• Choose one biographical feature: William Playfair<\/a>, Florence Nightingale<\/a>, W.E.B. Du Bois<\/a>, Marie Neurath<\/a>
\n\u2022 A Brief History of Data Visualization<\/a>
\n\u2022 Data + Design<\/em> Chapter 4<\/a>
\n• Visualization: Encoding Data Using Visual Cues<\/a><\/p>\n
\n• History of Data Visualization<\/a>
\n• Elements of Data Visualizations<\/a><\/p>\n
\n• Charting WSU Demographics<\/a>
\n• Working with Pivot Tables<\/a><\/p>\n
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\n\u2022 Data + Design<\/em> Chapter 14<\/a> and Chapter 15<\/a><\/p>\n
\n• Principles for Visual Impact<\/a>
\n• Practical Design Tips<\/a><\/p>\n
\n• Answering Questions with Pivot Tables<\/a>
\n• Organizing Tuition Data<\/a><\/p>\n
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\n\u2022 Stephanie Evergreen’s Data Visualization Checklist<\/a>
\n\u2022 Designing for the Human Brain<\/a>
\n\u2022 Data + Design<\/em> Chapter 17<\/a> and Chapter 18<\/a><\/p>\n
\n• The Problem with “Chartjunk”<\/a>
\n• Common Chart Problems<\/a><\/p>\n
\n• Good and Bad: Pet Ownership<\/a>
\n• Visualizing Data in Tableau<\/a><\/p>\n
\n
\n\u2022 “Understanding Pie Charts”<\/a> (EagerEyes)
\n• “Save the Pies for Dessert”<\/a> (Stephen Few)
\n\u2022 Visualizing Proportions<\/a><\/p>\n
\n• All About Pie Charts<\/a>
\n• Visualizing Part-to-Whole Relationships<\/a><\/p>\n
\n• Making Dashboards in Tableau<\/a>
\n• Athletics Expenses in Tableau<\/a><\/p>\n
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\n\u2022 “What We Talk About When We Talk about Beautiful Data Visualizations,”<\/a> a book chapter from Data Visualizations in Society<\/em>
\n• Data Visualization Society Strategic Plan 2020<\/a>
\n\u2022 Talk to the Newsroom: Graphics Director Steve Duenes<\/a> <\/p>\n
\n• Beauty in Data Visualization<\/a>
\n• Professional Community<\/a><\/p>\n
\n• Midterm Comparison Project<\/a><\/p>\n
\n
\n\u2022 Tweaking and Cleaning Up Data Visualizations: The Role of Adobe Illustrator<\/a>
\n• What does “clean it up in Illustrator” mean?<\/a>
\n• Adobe: Design professional charts and graphs<\/a><\/p>\n
\n• Midterm Presentations<\/a><\/p>\n
\n• Basic Charts in Illustrator<\/a>
\n• Food Consumption Pictogram<\/a><\/p>\n
\n
\n\u2022 Introduction to Map Design<\/a> (Esri)
\n\u2022 The Cartographer Who’s Transforming Map Design<\/a> (Wired) PDF version if the article won’t load<\/em><\/a>
\n\u2022 \u2018X\u2019 Marks the Spot: Officials Map a Route Out of the Pandemic<\/a> (NYT) PDF version<\/em><\/a>
\n\u2022 Mapping the Future: Cartography Stages a Comeback<\/a> (Wired) PDF version<\/em><\/a><\/p>\n
\n• Lesson: Maps and Cartography<\/a>
\n• Lesson: Why Map Projections Matter<\/a><\/p>\n
\n• Mapping Point Data<\/a>
\n• Making a Cartogram<\/a><\/p>\n
\n
\n\u2022 When Maps Shouldn\u2019t Be Maps<\/a>
\n\u2022 Election maps are telling you big lies about small things<\/a>
\n\u2022 5 Ways to Read a Scatterplot<\/a><\/p>\n
\n• Geography Without Maps<\/a>
\n• The Case for Dot Plots<\/a><\/p>\n
\n• Choropleth Maps in Tableau<\/a><\/p>\n
\n
\n\u2022 Interview with the South China Morning Post Infographics Team<\/a><\/p>\n
\n• Chart Variations and Tree Diagrams<\/a>
\n• Exploring “Xenographics”<\/a><\/p>\n
\n• Youth Sports Infographics<\/a><\/p>\n
\n
\n\u2022 Design Principles for News Apps (ProPublica)<\/a>
\n\u2022 The death of interactive infographics? (Dominikus Baur)<\/a>
\n\u2022 In Defense of Interactive Graphics (Gregor Aisch)<\/a><\/p>\n
\n• Principles of Interactivity<\/a>
\n• Interactive Connections<\/a><\/p>\n
\n• Interactive Map Comparison<\/a>
\n• Advice Flowchart<\/a><\/p>\n
\n
\n\u2022 What interactives can do (that articles can\u2019t)<\/a>
\n\u2022 Choosing a Font for your Data Visualization<\/a>
\n• How to Create Brand Colors for Data Visualization Style Guidelines<\/a>
\n• Optional recommended reading: Which fonts to use for your charts and tables<\/a><\/p>\n
\n• Evolution of Visualization Technology<\/a>
\n• Sports Interactive Pioneers<\/a><\/p>\n
\n• Esri StoryMaps Tour<\/a><\/p>\n
\n
\n• Three Ways to Annotate your Graphs<\/a>
\n\u2022 Patterns for Humane Data Visualization<\/a> (Source)
\n• Human-Looking Data Visualizations Don\u2019t Boost Empathy \u2014 Yet<\/a><\/p>\n
\n• Guided vs. Exploratory Graphics<\/a>
\n• Storytelling with Data Dimensions<\/a><\/p>\n
\n
\n
\n• None! But it may be helpful to review previous readings as you work on your project.<\/p>\n
\n• Trends and Innovations<\/a>
\n• Inspirations and Audiences<\/a><\/p>\n
\n
\n• None \u2014 Week 15 Quiz is review from previous weeks<\/p>\n
\n• Beyond the Course<\/a><\/p>\n
\n• Personal Data Project<\/a> (Wednesday, Dec. 14, 11:59 p.m.)<\/p>\n
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