9 a.m. to 12:30 p.m. M-F
Office Hours: 1-2 p.m. daily
Associate Professor Ryan Thornburg
The economics of digital publishing technology have opened a floodgate of raw data, and journalism is just one of many fields that are being rapidly transformed by that floodgate. In law, medicine, business, politics, and ecology, people are using data to understand the social and natural worlds. They are also using data to tell stories.
To retain their position as brokers of trust and hubs of community conversation, reporters must understand how the people they cover are using data, and how journalists can use data to improve our shared understand of an increasingly complex world.
Your decision to take this course indicates that you are interested in learning the skills and concepts of data-driven reporting. My expectation is that you already have demonstrated clear news judgment and precise, brief storytelling either in or out of a classroom.
The class starts from the assumption that you’ve never or rarely used even a basic spreadsheet to aid either your reporting or storytelling. That’s where the semester will begin. We will end just shy of an introduction to how computer programming and algorithms are using journalistic data to create new editorial products.
The Goal of This Course
Students who successfully complete this course will be able to acquire, organize, analyze and present data to a general news audience.
What You Will Learn
The first few weeks of class will be dedicated to an introduction to basic statistics and numerical and mathematical literacy, as well as a look at professional data-driven journalism projects.
The bulk of the course will be spent on practical skills exercises using tools such as Excel, Access, Fusion Tables, Open Refine, Tableau and QGIS.
The culmination of the course will be an explanatory or accountability news story and prototype of a working news data visualization or application.
The best way to learn about the changing journalism environment is to keep a close eye on professionals working in the industry. The bulk of our reading will be contemporary articles and research about data driven reporting.
Books and articles you will need for this class:
- IRE Tipsheets available to IRE Student Members. Register at httpss://www.ire.org/membersonly/join/register for $25.
- Other readings and tutorials available on this site and Sakai.
Exercises – 60%
Some exercises will be done in class as a group, while others will be done on your own outside of class. These will also include reading assignments and quizzes.
You may miss one class for any reason, as long as you meet with me and make up your work within one week. After that, each missed class will result in one full letter reduction of your attendance grade. You will also not be able to make up any work missed in subsequent classes.
Final Project:– 40%
Due: May 29, 5 p.m. (Story proposal memo due May 22, 5 p.m.)
The final project has two components: a publication-ready data-driven story and a written narrative reflection that describes how you did the story. More details
What grades mean
A – Mastery of course content at the highest level of attainment that can reasonably be expected of students at a given stage of development. The A grade states clearly that the student has shown such outstanding promise in the aspect of the discipline under study that he or she may be strongly encouraged to continue.
B – Strong performance demonstrating a high level of attainment for a student at a given stage of development. The B grade states that the student has shown solid promise in the aspect of the discipline under study.
C – A totally acceptable performance demonstrating an adequate level of attainment for a student at a given stage of development. The C grade states that, while not yet showing unusual promise, the student may continue to study in the discipline with reasonable hope of intellectual development.
D – A marginal performance in the required exercises demonstrating a minimal passing level of attainment for a student at a given stage of development. The D grade states that the student has given no evidence of prospective growth in the discipline.
F – For whatever reason, an unacceptable performance. The F grade indicates that the student’s performance in the required exercises has revealed almost no understanding of the course content. A grade of F should warrant an advisor’s questioning whether the student may suitably register for further study in the discipline before remedial work in undertaken.
The University of North Carolina at Chapel Hill has had a student-led honor system for over 100 years. Academic integrity is at the heart of Carolina and we all are responsible for upholding the ideals of honor and integrity. The student-led Honor System is responsible for adjudicating any suspected violations of the Honor Code and all suspected instances of academic dishonesty will be reported to the honor system.
All academic work in this course, including homework, quizzes, and exams, is to be your own work, unless otherwise specifically provided. It is your responsibility if you have any doubt to confirm whether or not collaboration is permitted. If the work is truly your own, you will be able to explain and demonstrate to my satisfaction how you did it.
Do not represent someone else’s words, thoughts, or ideas as your own without attribution in connection with submission of academic work, whether graded or otherwise.
Further information about the student Honor Code is available at https://studentconduct.unc.edu/honor-system