ZUR589q Data Journalism
Fall Semester 2016
Faculty of Social Studies
Masaryk University
Instructor: Prof. Stephen Doig Hours: 1.30-3pm
E-mail, Twitter: steve.doig@asu.edu, @sdoig Days: Thursdays
Office hours (from 19th of Sept): 3-5pm Tuesday and Thursday, office 5.51
About lecturer: Steve Doig is a Fulbright Scholar who holds the Knight Chair,
specializing in data journalism, at the Cronkite School of Journalism of Arizona State
University. Before joining ASU in 1996, he was research editor of the Miami Herald in
Florida. Data projects on which he worked at The Herald and at ASU have won the
Pulitzer Prize for Public Service, the Investigative Reporters & Editors Award, the
Goldsmith Prize for Investigative Reporting, the George Polk Award for Medical
Reporting, and other recognition. He consults actively with news organizations on
complex data analysis stories, and has done data workshops and lectures in 18
countries. He is a political science graduate of Dartmouth College and the Defense
Information School, where he trained to be a journalist for the U.S. Army during the
Vietnam War.
Course Description: Through most of the history of journalism, reporters who wanted to
examine difficult social problems had to rely on studies done by government or
academics. But today’s computer and communications revolution has given reporters
the power to do their own original studies of complicated questions. This kind of
investigative reporting might be considered social science done on deadline, allowing
you to inform your readers and viewers on issues ranging from the performance of
public authorities to inequality in this diverse society.
In this course, you’ll learn to use computer spreadsheets, database software, mapping
programs and statistical techniques to examine public data in ways that would be
impossible for reporters who rely only on their eyes and attention span. You’ll also learn
to use the Internet and other online sources to find information and sources for your
stories. And you’ll learn to negotiate with government officials for public records.
We’ll explore how these tools can be used across a wide variety of subject areas. Often
we’ll take a specific beat (crime, government, education, demographics, elections,
sports, business, environment, etc.) and discuss the kinds of data you might use in
stories covering that beat. Also, we’ll look at some good sources of that data, whether
from government agencies or on the Internet. Then you’ll do some sort of in-class live
data exercise concerning that data.
Most classes also will have a short segment on how journalists can use various statistical
tools. These lessons will be followed with quizzes to make sure you understand the
concepts.
You’ll also do a variety of short graded homework assignments designed to further your
skills. In addition, there will be two longer assignments: A report describing the details
of a useful government data source, and finally a "memo to your editor" proposing a
data story based on your preliminary analysis of some interesting dataset. More details
will be given to you during the semester.
Required materials:
Access to a computer with Microsoft Excel: Ideally, this class would be taught in a
computer lab, but that couldn’t be scheduled. Second best will be having you bring
your own laptop to class to do exercises here. At the very least, you’ll need to find a
computer with Excel (or other spreadsheet software) to do homework exercises.
Readings: There is no required textbook for this course, but I will give you a number
of printouts or readings from the web for you to do as assigned. A first such
assignment will be for you to download “The Data Journalism Handbook” from
http://datajournalismhandbook.org/; it is free. A number of other readings are in
the attached list; many are handouts that I will give you.
Listservs: You will subscribe (free) to two data journalism email lists:
a. NICAR-L: To subscribe to this list run by Investigative Reporters & Editors, go
to https://www.ire.org/resource-center/listservs/subscribe-nicar-l/
b. Data Driven Journalism: To subscribe to this list run by the European
Journalism Centre, go to http://datadrivenjournalism.net/mailinglist.
Grade: Your grade will be based on the following elements:
Quizzes and non-lab exercises (10%): There will be occasional open-book quizzes on
Excel or perhaps on current postings/discussions in NICAR-L or DDJ.
Statistics quizzes (25%): In most classes, I will lecture on statistical concepts and
tools. After each statistics segment, you will do a short open-notes homework
exercise that will be graded.
Report on a recently published data journalism project (15%): Each class, one or two
of you will give the class an oral (5 minutes) and written (two-page double-spaced)
report describing a significant journalism project that used computer-assisted
reporting. I will give you a handout with more details soon.
Public data description project (20%): I will assign each of you a good data site to
explore and then write a 2-3 page description of the kind of data it has and other
details I will specify in an assignment sheet I will give you.
Data analysis project (20%): Using a database of your choosing (with my approval),
you will do a data analysis project that will culminate in a 4-5 page project memo,
plus documentation, pitching what you found as a story idea. Later in the semester, I
will give you a handout with more details about this.
Final exam: There will be a final during the January exam period that will be worth
10% of your grade.
Make-up Work: The unexpected does happen. When it does, I will accept make-up work
for full credit, including any exercises and quizzes, if you can convince me there was a
non-frivolous reason for missing your deadline. Obviously, it will get harder to convince
me if there are multiple occasions.
Hashtag: If you are a Twitter user and want to post something of interest to other class
members, use #doigdata.
News media: You are expected to read a good newspaper or news website every day.
Look particularly for stories using data journalism -- or, even better, where it should
have been used.
Schedule: The schedule at the end of the document is subject to revision as I see
necessary, depending on our progress, the possibility of guest speakers and other
factors.
SUGGESTED READINGS
http://datajournalismhandbook.org/
http://towcenter.org/wp-content/uploads/2014/05/Tow-Center-Data-Driven-
Journalism.pdf
http://www.holovaty.com/writing/fundamental-change/
http://www.niemanlab.org/2014/07/alberto-cairo-data-journalism-needs-to-up-
its-own-standards/
http://www.niemanlab.org/2012/05/how-la-nacion-is-using-data-to-challenge-a-
foia-free-culture/
SOME GOOD PUBLIC DATA SOURCES
Czech National Statistics office: https://www.czso.cz/csu/czso/home
EU statistics: http://ec.europa.eu/eurostat
Public records in Europe: http://www.wobbing.eu/