Storytelling With Data Visualization
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README.md

###JOUR479D / JOUR779D: Storytelling with Data Visualization - Fall 2016### University of Maryland, College Park, College of Journalism
Mondays 1:00pm - 3:45pm
Location: Knight Hall Room 2107

Instructor: Assistant Professor Dr. Nicholas Diakopoulos, nad@umd.edu, nickdiakopoulos.com, @ndiakopoulos
Office Hours: Knight Hall Room 3207 from 4-5pm Mondays, or by appointment
Course Website: https://github.com/comp-journalism/UMD-J479D-J779D-Fall2016

Please refer to The University's Office of Undergraduate Studies for links to course related polices: http://www.ugst.umd.edu/courserelatedpolicies.html

####Course Description#### This course covers the use of data visualization as a method to communicate news stories (narrative visualization) and as a way to explore and analyze data as a method to find new news stories (visual analytics) in a journalism context. Students will learn to apply core principles of visualization related to perception, color, and visual mapping, while also practicing design skills, and implementing interactive data visualizations using both off-the-shelf tools as well as custom-built code. Critical skills and thinking about data visualization will be developed through the study of rhetoric, advocacy graphics, and ethics. Different types of data will be explored to understand a range of visual forms from networks, to timelines, trees, and maps. Several assignments, both critical and creative in nature, as well as an integrative final project will serve to underscore the concepts taught and provide practice in the craft of visualization.

####Learning Goals and Objectives#### By the end of the course students should expect to have gained:

  • An understanding of the concepts and techniques that result in effective visualization design in the context of journalism.
  • An ability to apply those concepts through critical thinking, design, and creation of data visualizations.
  • Practical experience in using visualization as a method to explore and communicate data using standard tools as well as javascript programming, resulting in portfolio-ready or otherwise publishable pieces.

####Prerequisites####

  • JOUR352 / JOUR652 (or equivalent experience with CSS / HTML), or permission of the instructor
  • A university-level statistics course

####Textbook and readings####

  • Alberto Cairo. The Functional Art: An introduction to information graphics and visualization. New Riders. 2012. ISBN-13: 978-0321834737
  • Other Readings will draw on a wide range of texts including books, articles, and research papers. Readings will be linked to the syllabus but hosted on UMD's ELMS so you'll need to log in there to download PDFs. Since readings may be updated over the course of the semester please check the online schedule on a weekly basis in order to get that week’s readings.

####Blogs and other online resources####

####About the Instructor#### Dr. Nicholas Diakopoulos is an Assistant Professor at the University of Maryland College of Journalism, with courtesy appointments in the College of Information Studies and Department of Computer Science. His research is in computational and data journalism with an emphasis on algorithmic accountability, narrative data visualization, and social computing in the news. He received his Ph.D. in Computer Science from the School of Interactive Computing at Georgia Tech where he co-founded the program in Computational Journalism. Before UMD he worked as a researcher at Columbia University, Rutgers University, and CUNY studying the intersections of information science, innovation, and journalism.

####Attendance and punctuality#### It is important that you attend every class and show up on time. To do otherwise will negatively affect your grade, because you will miss instruction and class discussions. Please notify the professor in advance, if possible, if you will be missing class due to illness or emergency.

####Religious Holidays#### There will be no tests or major assignments scheduled on religious holidays identified by the university. If you expect to miss a class due to a religious holiday, please notify the professor in writing before the start of the second class.

####Inclement weather#### If the university closes due to foul weather (hurricanes, tornadoes, earthquakes, blizzards, ice) or other emergencies and class must be canceled, students will be advised of assignment adjustments by the instructor. We will likely use email or our class site to make these notifications. Please check the university's home page if in doubt about whether or not classes have been canceled on campus.

####Academic integrity#### Along with certain rights, students have the responsibility to behave honorably in an academic environment. Academic dishonesty, including cheating, fabrication, facilitating academic dishonesty and plagiarism, will not be tolerated. Adhering to a high ethical standard is of special importance in journalism, where reliability and credibility are the cornerstones of the field. Therefore, the college has adopted a “zero tolerance” policy on academic dishonesty. Any abridgment of academic integrity standards in a College of Journalism course will be referred to the university’s Student Honor Council (see http://www.shc.umd.edu and the college's deans. To insure this is understood, all students are asked to sign an academic integrity pledge at the beginning of the semester that will cover all assignments in this course. Students found to have violated the university's honor code may face sanctions, including a grade of XF for the course, suspension or expulsion from the university.

####Students with Special Needs#### Students with a specific disability (permanent or temporary, physical or learning) needing special accommodation during the semester should make an appointment to meet with the professor immediately after the first class. Students may be asked to provide the instructor accommodation forms given to them after testing by the Disability Support Service on campus, 301-314-7682

####Learning Assistance Service#### If you are experiencing difficulties in keeping up with the academic demands of this course, contact the Learning Assistance Service, 2202 Shoemaker Building, 301-314-7693. Their academic coaches can help with time management, reading, math learning skills, note-taking and exam preparation skills. All their services are free to UM students.

####Assignments & Evaluation### All assignments and projects are due at the start of the class unless otherwise noted. Detailed instructions for each instruction and project will be provided as per the class schedule.

  • Assignments (45%)
    • For 479D there will be a total for three assignments due in the class each worth 15% of your grade. Assignments will be evaluated based on accuracy, design and usability, aesthetic appeal, critical and analytic rigor, writing quality, and functionality.
    • For 779D there will be three assignments due in the class each worth 12% of your grade. In addition, students in 779D will select, present, and lead discussion on one of the research papers listed on the syllabus and this will count for 9% of your grade.
  • Final Project Proposal (10%)
    • You will develop a final integrative data visualization project that utilizes the knowledge you acquire throughout the semester. Your project proposal will describe what you intend to visualize including the data you have acquired, and what you think the story is in the data based on any exploratory visualization and analysis.
  • Final Project (25%)
    • Your final data visualization project should show that you have integrated the knowledge you acquire in this class. Your final grade will incorporate aspects of the design and usability of your visualization, the clarity and newsworthiness of the story, and how much your project has improved through various stages of iteration, criticism, and improvement since the initial project proposal.
  • Class Participation (20%)
    • Students are expected to read and engage with the assigned texts, and to be prepared to discuss those texts critically. In class you will be assessed according to the insightfulness of contributions, critiques, and questions you raise during class discussion.
    • To show that you are prepared to discuss an assigned article, you should prepare at least one question based on your reading.

#####Late Work Policy##### Assignments will be marked down by one full letter grade for every 24 hours (or fraction thereof) that the assignment is late past the posted deadline. For example, an assignment that would normally receive an A- if submitted on time would receive a B- if it was submitted 1 day late. Assignments more than five days late will not be accepted. Work that is not turned in will receive zero points. In extreme cases (such as a death in the family, or severe illness), an extension may be granted, but students must communicate with the professor in advance of the deadline in these cases. Over the course of the semester you have one "slip" day. This day can be applied to any of the three primary assignments in the class (excluding the research paper presentation and final project) and allows you to hand in that assignment up to 24 hours late with no penalty. Use it wisely!

###Schedule### ####August 29 - Introduction to Data Visualization####

  • Lecture Slides PPT

  • Additional tutorials / resources:

  • 779D Assignment: Research Paper Presentation Out

    • Research Paper Presentation. Link

####September 5 - No class, Labor Day!####

####September 12 - Data, Data, Data####

  • Lecture Slides PPT

  • Readings Due

    • Diakopoulos. The Rhetoric of Data. 2013. Link
    • The Data Journalism Handbook. Chapter 5: Understanding Data. Link
    • Brademann & Gregory. Data + Design. Chapter 8: Data Cleaning. Link
  • Recommended Readings

    • J. Stray. The Curious Journalist's Guide to Data. Chapter 3 "Quantification". Link
    • C. Groskopf. The Quartz guide to bad data. Link
  • Additional tutorials / resources:

    • JSON Link
    • Where to find data. ProPublica. 2016. Link
  • Assignment One OUT

    • Exploratory Visualization for News Finding Link

####September 19 - Exploratory Visualization: Finding Insights####

  • Lecture Slides PPT
  • Readings Due
    • Few. Now You See It. Chapter 4: Analytic Interaction and Navigation. Link
    • Few. Now You See It. Chapter 5: Analytic Techniques and Practices. Link

####September 26 - Visualization Design: Conveying Insights####

  • Lecture Slides PPT

  • Readings Due

    • Cairo. The Functional Art. Chapter 2: Forms and Functions: Visualizations as a Technology
    • Cairo. The Functional Art. Chapter 3: The Beauty Paradox: Art and Communication"
    • Wong. WSJ Guide to Information Graphics. Chapter 1: Basics. Link
  • Recommended Reading

    • Makulec. Data + Design. Chapter 14: Anatomy of a Graphic. Link
    • Groeger. Design Principles for News Apps & Graphics. Link
    • Financial Times' Visual Vocabulary. Link
    • Emery. Telling a story with a chart. Link
  • Tutorials

  • Assignment One DUE

  • Assignment Two OUT

    • Illustrating a Data-driven News Investigation Link

####October 3 - Designing for Visual Perception####

  • Lecture Slides PPT

  • Readings Due

    • Cairo. The Functional Art. Chapter 6: Visualizing for the Mind
    • Ware. Visual Thinking for Design. Chapter 1: Visual Queries Link
    • Ware. Visual Thinking for Design. Chapter 4: Color Link
  • Tutorials

    • Vega Embed Example Link

####October 10 - Design & Production Practices####

  • Guest Speaker: Lisa Charlotte Rost, Open News Fellow at NPR.

  • Lecture Slides PPT

  • Readings / Viewings Due

    • Cairo. The Functional Art. Chapter 8: Creating Information Graphics
    • Bostock. Design is a Search Process. Link
    • Unger & Chandler. Project Guide to UX Design. Chapter 10: Site Maps and Task Flows Link
    • Unger & Chandler. Project Guide to UX Design. Chapter 11: Wireframes and Annotations Link
  • Assignment Two DUE

  • Final Project Proposal OUT

    • Final Project Link

####October 17 - Narrative Visualization: Connecting Insights####

  • Lecture Slides PPT

  • Readings Due

    • Segel & Heer. Narrative Visualization: Telling Stories with Data. IEEE Transactions on Visualization & Computer Graphics. 2010 Link
    • Tufte. Beautiful Evidence. The Fundamental Principles of Analytic Design. Link
    • Cairo. The Functional Art. Chapter 9: The Rise of Interactive Graphics.

####October 24 - Visualization Rhetoric, Ethics, and Critique####

  • Lecture Slides PPT

  • Readings Due

    • Hullman & Diakopoulos. Visualization Rhetoric: Framing Effects in Narrative Visualization. IEEE Transactions on Visualization & Computer Graphics. 2011. Link
    • Tufte. The Visual Display of Quantitative Information. Graphical Integrity. Link
    • Viégas and Wattenberg. Design and Redesign in Data Visualization. Link
  • Assignment Three OUT

    • Visualization Critique Link

October 28####

  • Final Project Proposal DUE

####October 31 - User Experience####

  • Lecture Slides PPT

  • Readings Due

    • Krug. Don't Make Me Think (revisited). Chapter 9: Usability Testing on 10 cents a day. Link
    • Nielson. Usability Engineering. Chapter 2: What is Usability. Link
    • Nielson. Usability Engineering. Chapter 6: Usability Testing. Link
  • Heuristics

    • Nielson's List Link
    • Vizualization Specific List Link

####November 7 - Maps####

  • Lecture Slides PPT

  • Readings Due

    • Cairo. The Truthful Art. Chapter 10: Mapping Data. Link
    • MapSchool Link
    • Ericson. When Maps Shouldn't Be Maps. Link
  • Recommended Reading

    • Ingraham. The dirty little secret that data journalists aren’t telling you. Washington Post. Link
  • In-class Tutorials

    • Carto Academy Link
  • Assignment Three DUE

####November 14 - Network, Timeline, and Text Visualizations####

  • Lecture Slides PPT

  • Readings Due

    • Meirelles. Design for Information. Chapter 2: Relational Structures: Networks. Link
    • Meirelles. Design for Information. Chapter 3: Temporal Structures: Timelines and Flows. Link
    • Meirelles. Design for Information. Chapter 6: Textual Structures. Link

####November 21 - Final Project Progress Presentations####

  • Readings Due
    • Irizarry and Connor. Discussing Design: Improving Communication and Collaboration through Critique. Apendix A. The 10 Bad Habits That Hurt Critique. Link

####November 28 - Final Project Work & Research Paper Presentations####

####December 5 - Emerging Topics: Mobile, Artistic, & Collaborative Visualization####

  • Lecture Slides PPT
  • Readings Due
    • Heer et al. Voyagers and Voyeurs: Supporting Asynchronous Collaborative Visualization. Communications of the ACM. 2009. Link
    • Florit. The Boston Globe’s Gabriel Florit on Responsive Visualizations. Link
    • MobileVis Patterns and Best Practices. Link

####December 12 - Final Project Presentations####