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Cool Creative Communications: Dazzling Data Visualizations. K iri Burcat, MLIS Data and Evaluation Coordinator National Network of Libraries of Medicine (NNLM). COURSE OBJECTIVES. Use National Library of Medicine resources to locate data sets Develop data visualizations using Tableau Public
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Cool Creative Communications: Dazzling Data Visualizations Kiri Burcat, MLIS Data and Evaluation Coordinator National Network of Libraries of Medicine (NNLM)
COURSE OBJECTIVES Use National Library of Medicine resources to locate data sets Develop data visualizations using Tableau Public Critique peer data visualizations using an evaluation model
FUNDAMENTALS OF DATA VISUALIZATION Image from d3js.org
WHY VISUALIZE DATA? Photo by Andrew Neel on Unsplash.com
Visualization enables viewers to quickly glean insights from data. Data and image from Census.gov
FIND PATTERNS John Snow mapped the locations of water pumps and cholera deaths during an outbreak in London in 1854. He is credited with the discovery that cholera is transmitted through contaminated water. Image after John Snow [Public domain], from Wikimedia commons
MAKE DECISIONS Image from Babynamewizard.com/voyager
COMMUNICATE Graphic from the Wall Street Journal
PERSUADE By w:Florence Nightingale (1820–1910). Public Domain, https://commons.wikimedia.org/w/index.php?curid=1474443
HOW DO WE VISUALIZE DATA? HOW DO WE VISUALIZE DATA? Photo by Markus Spiske on Unsplash.com
VISUAL VARIABLES Position Changes in the x, y location Size Change in length, area, or repetition Color Hue Changes in hue at a given value Shape Color Value Changes from light to dark Orientation Changes in alignment Texture
How many 3s? 193484059849506849002569864175369222689214785625978625258796356788952156785556421897512470025456970159786023682597462101025498567895165289
How many 3s? Part 2 How many 3s? 193484059849506849002569864175369222689214785625978625258796356788952156785556421897512470025456970159786023682597462101025498567895165289
PERCEPTION AND COGNITION PERCEPTION AND COGNITION “Vision Optimization”: We are always looking for patterns, form, and structure Image: Paul Rand (A note on IBM website) [Public domain]
GESTALT PRINCIPLES GESTALT PRINCIPLES Image by Krisztina Szerovay, UX Knowledge Base
GESTALT PRINCIPLES GESTALT PRINCIPLES SLIDE 2 Image by Krisztina Szerovay, UX Knowledge Base
GESTALT PRINCIPLES GESTALT PRINCIPLES SLIDE 3 Image by Krisztina Szerovay, UX Knowledge Base
GESTALT PRINCIPLES GESTALT PRINCIPLES SLIDE 4 Image by Krisztina Szerovay, UX Knowledge Base
SIMPLICITY Humans have a limited capacity for processing input 19348405984950684900256986417536922268921478562597862525879635678895215678555642189751247002545697015978602368259746210102549856789516528916 19348405384950684900256986417536922268931478562593862525379635678895215678555632189751247002545697013978602368259746210102543856783516528916 VS
PROXIMITY Objects that are closer to each other are perceived as being more related than the ones that are not positioned near them
PROXIMITY PROXIMITY CONTINUED www.lib.umd.edu/stem
PROXIMITY PROXIMITY SLIDE 3 www.lib.umd.edu/stem
SIMILARITY If two objects have similar characteristics, we perceive these objects to be more related than the ones that don’t share these qualities.
SIMILARITY slide 2 SIMILARITY If two objects have similar characteristics, we perceive these objects to be more related than the ones that don’t share these qualities.
GESTALT PRINCIPLES APPLIED Gestalt Principles • Proximity • Similarity • Simplicity (an attempt, at least) Visual Variables • Hue • Position Image from Economist.com
CHOOSING A VISUALIZATION CHOOSING A VISUALIZATION
PRACTICAL DESIGN TIPS • Be mindful of cultural and symbolic connotations of color • Get it right in black and white – accessibility for people who are color blind • Stick to ~6 or fewer different colors • Follow familiar patterns and structure Image from d3js.org
DESIGN CRITIQUE Image from Fundamentals of Data Visualization by Claus O. Wilke
DESIGN CRITIQUE Continued DESIGN CRITIQUE The colors are misleading! • Shifts between hues look abrupt • Unintentionally draws attention to blue areas • 0% and 100% would look more similar than 0% and 50% • Defies conventional color associations Image from Fundamentals of Data Visualization by Claus O. Wilke
DESIGN CRITIQUE Slide 3 DESIGN CRITIQUE The colors are misleading! • Shifts between hues look abrupt • Unintentionally draws attention to blue areas • 0% and 100% would look more similar than 0% and 50% • Defies conventional color associations Solutions: • Monochromatic palette • Colorbrewer2.org Image from Fundamentals of Data Visualization by Claus O. Wilke
DESIGN CRITIQUE Slide 4 DESIGN CRITIQUE Image from Fundamentals of Data Visualization by Claus O. Wilke
DESIGN CRITIQUE Slide 5 DESIGN CRITIQUE d The colors are meaningless! Image from Fundamentals of Data Visualization by Claus O. Wilke
DESIGN CRITIQUE Slide 6 DESIGN CRITIQUE The colors are meaningless! Solution: • Choose 1, less saturated color for all the bars Image from Fundamentals of Data Visualization by Claus O. Wilke
DESIGN CRITIQUE Slide 7 DESIGN CRITIQUE Image from Fundamentals of Data Visualization by Claus O. Wilke
DESIGN CRITIQUE Slide 8 DESIGN CRITIQUE Too many colors! Image from Fundamentals of Data Visualization by Claus O. Wilke
DESIGN CRITIQUE Slide 9 DESIGN CRITIQUE Too many colors! Solutions: • Color code dots by region of the US, rather than individual state • Selectively label dots on the chart to draw attention to outliers or interesting cases Image from Fundamentals of Data Visualization by Claus O. Wilke
ASSIGNMENT ASSIGNMENT Data visualization Hall of Fame/Hall of Shame Find an example of a data visualization that you think is either especially effective or especially ineffective. Post on the discussion board with a link to the visualization and the answers to the following questions: • What is the data relationship that is being represented? • How is the creator representing it? • Why do you think this visualization is especially effective/ineffective? Image from the Junkcharts blog
ADDITIONAL RESOURCES • Document on Moodle • List of visualization blogs and galleries for your assignment • Color choosing tools and accessibility information • Two supplemental resources • The best stats you’ve ever seen, by Hans Rosling, founder of Gapminder • 39 Studies of Human Perception in 30 minutesby Kennedy Elliot, graphics editor at the Washington Post
Thank you! Kiri Burcat – kburcat@hshsl.umaryland.edu
Cool Creative Communications: Dazzling Data Visualizations Module 2: Finding Data
IN THIS MODULE • NLM Data Discovery platform • Watch webinar excerpt • Other Data Sources • Review document in Moodle • Assignment: Finding Data • Post on discussion board Photo by Fredy Jacob on Unsplash
Assignment ASSIGNMENT Finding Data Find and download a dataset (or datasets) that you think would make for an interesting visualization. On the discussion board, attach the file as a CSV or Excel worksheet and answer the following questions: • What information is contained in this dataset? • What would be your goal in visualizing the data? • Would you need to further curate the data to achieve your goal? (ie delete unnecessary information or extract only certain information) Photo by Simson Petrol on Unsplash.com
Thank you! kburcat@hshsl.umaryland.edu
Cool Creative Communications: Dazzling Data Visualizations Module 3: Getting Started in Tableau Public
IN THIS VIDEO • Downloading Tableau Public • Downloading Data from the World Bank data bank • Formatting Data • Create a simple visualization in Tableau Public
FURTHER RESOURCES Required • Tony Nguyen’s Cats vs. Dogs video Supplemental: • Tableau’s “Formatting Data” video • Tableau’s “How to get your data into Tableau Public” video • Tableau’s “How to pivot data in the Data Source” video
Thank you! kburcat@hshsl.umaryland.edu
Cool Creative Communications: Dazzling Data Visualizations Module 4: Dashboards, Stories, Interactivity