This blog will function as our living syllabus for JRL 593F, Graphics and Data Journalism. It was originally created for the Blogging and Interactive Journalism course (offered every spring – talk to me for details), but this class is a close cousin to that one. Also I got tired of the blog being dormant every fall.
There are two major (and overlapping) parts of this course. As the title suggests, you will learn how to work with 1) graphics, and 2) data. Here are some points about those two areas and how they are alike/different. Please note: These are all generalizations to help you thinking about these two closely related areas of journalism – you will find many exceptions as we progress through the course.
- Although both have been around for a while, information graphics as a newsroom institution is probably a bit older, tracing to the 1980s advent of desktop publishing.
- Data journalism has been around in a variety of forms for decades (Philip Meyer was doing computer assisted reporting in the 1960s!), but its current form can reasonably be tied to the (late) 2000s.
- If the name of the job is important to you: Both forms can exist as part of departments or as skills tied to more traditional reporting jobs. In general, however, the infographics path tends to lead to the graphics/news visuals department, and the data path is more likely to be applied as a skillset by a traditional reporter.
- That said, both deal heavily in visualization. The infographics side tends exclusively visual, while the data side visualizations may be text only (e.g., interactive tables). Tables are visual, of course, but they lack the illustrative component more commonly seen in infographics, and a data journalist can do his/her job without ever learning Adobe Illustrator.
- The role of linear storytelling is also a point of distinction. Although both are nonlinear to an extent, infographics are more likely to take a narrative path with clear beginnings, middles, and ends (such as artist Wayne Dorrington’s retelling of Star Wars in icon form). Data journalism, on the other hand, often takes a form where Reader X can obtain an entirely different story than Reader Y (e.g., ProPublica’s Opportunity Gap).
- Regardless of the above distinctions, however, BOTH require a sense for visual, nonlinear storytelling.
So that should help you to think a bit about what we’ll be doing in here. In addition to the readings on eCampus, we’ll be using The Digital Journalism Handbook. This is new, and we’re going to try it out in the data components of this course. It’s a tremendous source of case studies and tips to what we’ll be doing.
This blog will continue to be a source of course material, so bookmark it, RSS it, do whatever you need to check it regularly. We’ll also be using the Twitter hashtag #WVUdataJ to share information with the group. Post a comment there, or to this page, as we get rolling.
See you in class!