Syllabus

An overview of data journalism practice.

Wednesdays, 6-8:50pm, June 23rd - August 25th, 2016. You must bring a laptop to class.

Professor: David Eads, NPR Visuals Team / email / twitter / github

Calendar: Add to your Google calendar to automatically get schedule updates.

Slack group chat: To share links, ask questions, and get help. You must be logged into the Slack chat during class so we can share links and files.

If you have a question or comment, use Slack first. Google Chat or email is best way to reach me privately outside of Slack. Also feel free to text, but not after 10pm.

Our focus

Online data journalism: Finding, analyzing and presenting structured information on the Internet as part of your journalistic work.

Data has never been more plentiful, or important, in human history. It shapes business decisions and government policies at the highest levels. It is a constant part of our daily lives in the most mundane ways. Presidential campaigns and scientists wrangle vast amounts of data, but so does your phone, car, even fridge.

Understanding data and visualizing it clearly, compellingly, and truthfully is an essential skill for journalists. It’s an important part of the world we cover, and often misunderstood. Without it, our stories are missing a key source. With it, we can evaluate how we frame our stories and deepen our reporting.

Good data visualization and graphic analysis can expand the range of stories we tell, and how we tell them. Our goal is to understand these themes of online data journalism through practical examples:

Because it the election season, we’re going to be diving deep on election related data. The election is the most important and all-encompassing data story of 2016. Because your professor is covering the election, he will maintain his sanity.

Our goal is to shape data into appropriate and powerful reporting and visual storytelling on the Internet.

Class

Every class will be structured roughly the same way:

Homework

Every week, you should send an email with a link to a data journalism project to discuss in class and a few sentences explaining why you think it’s interesting.

Every week, you’ll be tasked with one or more of:

Final group projects

Just kidding, no final projects this time.

Grading

Class participation: 40%

You are expected to be timely, contribute to discussions, and tackle hands-on work in class.

Guests require your full attention, which means no devices. Students who spend more than a few minutes on their phones or laptops while a guest is speaking will be given a participation grade of zero for that session.

Homework: 60%

Submit your homework by the evening of class unless otherwise specified.

Late homework will be docked 5% per day late. Homework turned in later than 3 days will not be accepted.

Weekly schedule:

The class calendar is available via Google Calendar.

This outline is tentative and could be changed! Check the lesson page for detailed upcoming lesson plans.

Your responsibilities

In addition to the expectations of this class, these are your responsibilities as students:

All students are required to adhere to the Medill Integrity Code as well as Northwestern University’s Academic Conduct Policies, which are found in the Student Handbook.

Academic dishonesty can result in penalties ranging from letters of warning to dismissal from the university. Instructors may give a failing grade in a course for academic dishonesty. It is also university policy that instructors can require students to submit their work electronically to be analyzed for possible plagiarism.

Equal access

Northwestern University works to provide a learning environment for students with disabilities that affords equal access and reasonable accommodation. Any student who has a documented disability and needs accommodations for classes and/or course work is requested to speak directly to the Office of Services for Students with Disabilities (847-467-5530) and the instructor as early as possible in the quarter (preferably within the first two weeks of class). All discussions will remain confidential. Accommodations can be made by instructors once OSSD has met with the student and verified the disability.