Syllabus

JOUR 72312 Data Visualization

Spring 2014 CHUN
Fridays, 9:30AM-12:20PM
Room 436

Public Class notes:
http://bit.ly/datavizspring2015

It isn’t hyperbole: journalists today have access to more data than ever before, as well as better tools to understand that data and expose the stories buried in the numbers. From election results, budgets and census reports, to Facebook updates and image uploads, journalists need to know how to find stories in data and shape them in compelling ways. This hands-on course teaches you to gather and analyze data, and visualize interactive data-driven stories. This burgeoning discipline touches on information and interactivity design, mapping, graphing, data analysis, and a bit of code. Participants are expected to pitch, report, and produce stories working alone and in teams. You’ll learn to use spreadsheets and online Web tools such as CartoDB, Refine, and HighCharts, and integrate them in a non code-intensive development environment. Familiarity with HTML/CSS is helpful, but not required. This is not a course in programming, but we will be dealing with some code.

Course objectives

This three-credit course explores complex storytelling using data. Students will pitch, report, conceptualize, design, and produce informative and compelling data-driven pieces. The course emphasizes:

Data collection
Editing and organizing data while maintaining its integrity
Basic statistical methods and concepts, the foundation of solid data reporting
Understanding technologies available to create online, interactive data-driven stories
Design basics, effective visual communication, and data visualization
Applying interactivity to data-driven stories
Critical evaluation of professional data-driven news stories (what makes a particular project successful?)
Seeking out innovative uses of data
Understanding the development process for creating data stories

Course outcomes

At the end of this course, students will be able to:
Identify patterns in data that help uncover news trends
Conceptualize clear and concise ways to illustrate these trends
Create interactive graphics using both custom tools and web-based services
Evaluate effectiveness of data-based storytelling projects, both of their own creation and across the industry.
Instruct and supervise fellow journalists and programmers in identifying and producing stories that can become effective data stories.

Faculty

Russell Chun Office: 432 russell.chun@journalism.cuny.edu

Thursdays 2-4:30 by appointment at least a day in advance

Fridays 2-4:30 drop in

Russell Chun is a multimedia developer, author, and educator specializing in visualizing science, data, and story ideas for the web. He is on the adjunct faculty at City University of New York (CUNY) Graduate School of Journalism where he teaches data-driven interactive journalism. He is also Department Head of the Illustration Program at Sessions College for Professional Design. He is the author of several books on multimedia, and has developed courses, and interactive and video products on effective multimedia. Russell previously taught at Columbia University and the University of California at Berkeley Graduate Schools of Journalism. He’s served as an interactive consultant and trainer for News21, a Carnegie/ Knight-funded national initiative to improve the quality of journalism education in the United States. He’s judged local and national multimedia news contests.

WordPress and Digital Storage

Your major stories will be uploaded to CUNY’s Digital Storage server. Note that this web hosting will be available to you for two years after you graduate, so you should make plans to backup work you are proud of and find hosting for it off of campus servers. Some assignments will be posted to a class blog. Students will be required to present their stories in class for critique. Posts to the class blog are public by default, but you can choose to keep them private if you prefer. Students are encouraged to submit superior and/or timely work for publication elsewhere, including school outlets such as the New York City News Service.

Software Requirements

Tabula allows you to extract structured data from PDFs
Open Refine is indispensable for cleaning messy data
An FTP client like Fetch or Cyberduck to transfer files to the server.
A text editor like TextWrangler.
Microsoft Excel
Google Chrome as your Web browser
Google Spreadsheets and Fusion Tables, which are available as apps from your Google Drive.
You will also be asked to create accounts on JS Fiddle, and CartoDB. Important: before you create your CartoDB account, make sure you have the information you need to get the free academic version.

Readings

Readings are available on e-reserve from the Research Center. We will be reading from:

Cairo, The Functional Art
Illinsky and Steele, Designing Data Visualizations
Tufte, Quantitative Display of Information

Readings: http://cunygsj.docutek.com/eres/coursepage.aspx?cid=166&page=docs

Password: dataviz15

Grading

Your grade is determined by three factors: participation, successful completion of all solo homework assignments, and successful completion of the two team stories and the one solo story. Your participation includes attending all classes, being active in discussions, workshops and critiques, presenting your story for the Data Festival, and participating in all in-class hands-on activities. Your assignments will be evaluated in terms of use of data, story and context, interactivity, and design.

Participation : 20%
Homework assignments: 20%
Story 1 (team): 20%
Story 2 (solo): 20%
Story 3 (team): 20%

Grades for your two team stories are further broken down as follows:

Pitch (25%)
Storyboard (12.5%)
Draft (25%)
Final (25%)
Revision (12.5%)

Grades for your individual stories are further broken down as follows:

Pitch (20%)
Final (40%)
Revision (40%)

This means that if you complete a brilliant story but don’t put real effort into the initial pitch or rough draft, you can’t get better than a C on the story. All assignments are due at the beginning of class. E-mail all assignments directly to the professor with “Homework Week X” in the subject line, where X is number of the week. If we can’t find your homework because an incorrect subject line, you won’t get credit for it. What do I mean when we say “Pitch” or “Rough draft”? This is what I mean:

Pitches: A complete pitch should tell us who cares, why we care now, and what pre-reporting you’ve done. You must include:

a proposed title or headline
a news hook, or explanation of why this story matters now. Why should I care?
your nut that captures the essence of the story. 1-2 sentences only.
a description of and link to the data (which means you must already have your data)
one source you have already spoken with or at least three potential expert sources and your plans for reaching them

Storyboards: A storyboard organizes your content conceptually and spatially. This semester, when you turn in storyboards, you should also include a revised pitch. We use wireframe and storyboards interchangeably here. We’re looking for a simple sketch (on paper, in Word, or PowerPoint, Illustrator, or any number of online storyboarding tools) that shows us how you intend to integrate your visualizations, words, and navigation elements. Use simple boxes to tell us where your different elements will be positioned in a design, and how a user will navigate through the content. Check out Mark Luckie’s thoughts on sketching/storyboarding, with examples, from 10,000 Words.

Rough Drafts: A rough draft does not have the polish of a final project, but it should be close. You should have created all the visualizations that you plan to use. Your classmates should be able to evaluate a rough draft on its merits, without a guided tour of forthcoming features. A complete rough draft includes:

Clean data in spreadsheets, already normalized, sorted, manipulated
Visualizations of the data with proper labels, keys, and/or legends
Captions
Credits
A headline
At least three hyperlinks to other reporting, integrated in the body of your text that puts your story in a broader context.
Text that incorporates reporting from at least one human source. You’re not required to quote your source, but you do need to be able to tell the class what insights your human source provided.

Final Story: Your story must be posted to the class blog. The blog will be kept private to keep rough drafts private. If you wish to host your final story elsewhere, you may, but you still need to post a headline, excerpt, image and link to the class blog. Plagiarism It is a serious ethical violation to take any material created by another person and represent it as your own original work. Any such plagiarism will result in serious disciplinary action, possibly including dismissal from the CUNY J-School. Plagiarism may involve copying text from a book or magazine without attributing the source, or lifting words, code, photographs, videos, or other materials from the Internet and attempting to pass them off as your own. Please ask the instructor if you have any questions about how to distinguish between acceptable research and plagiarism. Copyright In addition to being a serious academic issue, copyright is a serious legal issue. Never “lift” or “borrow” or “appropriate” or “repurpose” graphics, audio, or code without both permission and attribution. This applies to scripts, audio, video clips, programs, photos, drawings, and other images, and it includes images found online and in books. Create your own graphics, seek out images that are in the public domain or shared via a creative commons license that allows derivative works, or use images from the AP Photo Bank or which the school has obtained licensing. If you’re repurposing code, be sure to keep the original licensing intact. If you’re not sure how to credit code, ask. The exception to this rule is fair use: if your story is about the image itself, it is often acceptable to reproduce the image. If you want to better understand fair use, the Citizen Media Law Project is an excellent resource. http://www.citmedialaw.org/legal-guide As with plagiarism, when in doubt: ask. Deadlines Deadlines on assignments – as in any newsroom – are sacrosanct and should not be missed without exceptionally good reason, and only when your instructors have been notified in advance. If you are taking the course for credit, late assignments will be assessed a one-half grade penalty for every day overdue. Absences and Tardiness Participation and attendance are important ingredients to your success in the class, especially in this course where your major assignments are team-based. Please be on time for class and back to class from breaks. Repeated tardiness will result in a reduction of grade in participation. Notify the instructors of any absences before class, or as soon as you know you will be out.

SYLLABUS in BRIEF

Lecture:What you can expect from us

Homework:What we expect from you (due)

1/30 Course intro. What is data?
2/6 Numeracy, spreadsheet review
2/13 Cleaning data, adv spreadsheets
2/20 Graphical encodings: charting
2/27 Geographic encoding: mapping
3/6 Presentation, Information design, Ethics
3/13 Open workshop
3/20 Critique of Story 1
3/27 Adv tools: SQL, Interactive tables
SPRING BREAK 4/3 and 4/10
4/17 Open workshop
4/24 Critique Story 2, decide on class project
5/1 Pitches for class project
5/8 Open workshop
5/15 Critique of Story 3, wrap-up
5/22 No class

Data journalism pre-reading/viewing
Datasets
Spreadsheet exercise
Clean a dataset
Pitch 1
Storyboard 1
Rough draft 1
Story 1 final
Revisions 1, Solo Pitch 2
SPRING BREAK 4/3 and 4/10
Solo rough draft 2
Solo story final
Pitch 3 Class project
Rough draft 3
Story 3, Solo Story revisions
Revisions 3, course evaluations

Festival of Data: Every week one student will choose a data driven story to present in class. Prepare to discuss the strengths and weaknesses of the story, the authors’ use of data as well as their use of interactivity, and to identify the underlying technology. Blog your story in the “Festival of Data” category by the start of class time on your week.

Data Visualization Spring 2015