Here you will find an outline of the coursework. For a complete syllabus with details on how assignments will be graded, refer to the syllabus posted in Canvas.
Course Description: This course is designed for the Graduate Journalism Program. Students should have already completed Public Affairs Data Journalism One in the fall 2016. Enrollment otherwise is subject to instructor approval.
Some data journalism assignments for this class can be coordinated with reporting efforts from other journalism courses with approval from all instructors.
Students will produce timely data-driven stories for Peninsula Press. You will learn to go deep on mining data for story, reporting and writing out that story. You will learn the basics of mapping and visualizing data. Instruction will include the use of a variety of software programs. Among them: spreadsheets, OpenRefine, DocumentCloud, SQL, ESRI Desktop and ESRI Storymaps, Tableau Software and Python. During the course, you may work with other journalism organizations on collaborative projects. You will work on a data project either of your own choosing or one we come up with together. Content approved by editors will be published on the Peninsula Press news site, http://peninsulapress.com/.
Professional journalism disclosure: When interviewing anyone for a story (on or off campus) you need to properly identify yourself “as a student reporter writing BOTH an in-class assignment AND a PUBLIC story – one that could be published by major media outlets: sfgate.com, The San Francisco Chronicle or KQED via the Peninsula Press.”
Learning Goals: By the end of the quarter, you should demonstrate:
- Integration of narrative writing style with data-driven
- Proficiency in finding, cleaning, analyzing and visualizing data for
- Proficiency in mining unstructured text for news nuggets and trends.
- Proficiency in Web research and data collection
Here are the main assignment categories, some of which may be done in tandem with reporting for other classes.
- Group project — Group work and possible stories on a campaign finance This section will focus on learning Python and Jupyter Notebook.
- Individual project — One data-driven individual news project, including a story and interactive data visualization or map. This can be off of your beat or on a story subject decided upon with me.
- Short stories/other assignments — Data visualization and/or short explanatory stories out of data analysis which may be published via Peninsula Press. These will be both team-centered and individual assignments.
- Participation: Discussion, participation in class activities, quizzes, promptness, staying off of devices except when needed for classroom use, etc.
- Data Negotiation — Each student will be responsible for negotiating for police stop and search data from one or two cities.
Deadlines: Assignments should be uploaded to Google Drive before the start of class, on the dates assigned. Screenshots and links to data visualizations should be included in Google Docs along with headlines, accompanying stories, etc. In most cases, you will also need to submit the url to your Google document or other completed work via Canvas.
Some assignments may also be uploaded to the Peninsula Press WP site or to other shared folders/drives.
Just as in a newsroom, you cannot miss deadlines. Late submissions will be penalized. If you are having difficulty completing an assignment, you need to email me in advance so we can address the situation. Often, obtaining and analyzing data is difficult and depends on others. But keeping your partners and your editor informed is critical.
Structure: Most classes will include discussion on facets of data journalism and either hands-on data journalism practice or class discussion on your projects.
Each student is expected to participate in class discussions, contribute constructive critique of work, and come to class having completed assignments and readings. Assignments and student work may be discussed and critiqued in class.
Class begins promptly. Lateness or unexcused absence will affect your grade. If you have to miss class, notify me in advance. Also, avoid being on a device unless it is related to class. Here are a few interesting articles about the pros and cons of using devices in the classroom.
Multitasking and learning, Slate article.
Clay Shirky’s ban on laptops in class.
How students contribute when they use devices in classes, by Steve Buttry.
Stanford’s Honor Code applies: http://www.stanford.edu/dept/vpsa/judicialaffairs/guiding/honorcode.html
Data journalism involves a lot of moving parts. You will be graded on your ability to find and obtain data, your ability to accurately analyze data for a story, how you tell a story both in the narrative and through visualization or maps.
Readings and viewings: Much of the reading will be assigned via online links or for you to look up in the IRE archives. Be prepared to discuss clips and readings and lead discussions as assigned.
Student membership in Investigative Reporters and Editors