PhDigital Data Journalism
Thursday, May 17, 9 a.m. – noon
Instructors: Daniel Carter & Kelly Kaufhold
Description:
Data Journalism isn’t new (as we discussed on #Slack and as we’ll touch on in class) but there are three substantial differences in Data Journalism in the digital era:
1) The easy availability of substantial amounts of data;
2) How data is generated (including through our own behavior) and how we can capture that;
3) How we interpret and show/share data
Outline:
- Introduction to Data Journalism
- Evolution of Data Journalism
(Coddington article: Computer-Assisted Reporting; Data Journalism; Computational Journalism)
III. A few examples
(Individual vs. aggregate-level data)
- Data searching
- Data cleaning
- Some tools for visualizing data
Data Journalism data sources and FOIA requests
VII. How Data Journalism differs from other data disciplines, like social science
VIII. Issues in teaching Data Journalism
- Time to work with visualization tools
- Examples (if time allows)
=== From the online module ===
Discussion Assignment:
What are some of the tensions created by the availability/use/ubiquity/openness/secrecy of data in news (and in society where it intersects with news, like the current Facebook/Cambridge Analytica saga);
- How might you measure or study that? Where might you find relevant data?
- What are your favorite data projects?
- What questions do you have about Data Journalism?
Resources