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Data Journalism | EUJ 209

Instructor: Andreas Veglis

Course Description
The course studies the issue of data journalism. Today there is a significant availability of data in digital form, which makes necessary the introduction of this form of journalism. Thus the journalist must be able to find, extract, adapt, visualize and interpret data. In order to succeed in such a task he must possess all the theoretical knowledge concerning data manipulation as well as the necessary ICT skills in order to create data visualizations (static or interactive) that will be embedded in his news articles.

 

Course Objectives

  • Understand the concept of data journalism.
  • Acquire the basic skills in finding and cleaning data sets.
  • Comprehend the basic concepts of statistical analysis.
  • Acquire the basic skills of using statistical software packages
  • Comprehend the basic concepts of data visualization.
  • Acquire the basic skills of using data visualization web tools.

 

Learning Outcomes

  • Define the core concepts of data journalism
  • Working efficient with data sets
  • Define basic concepts of statistical analysis
  • Build on data visualization with advanced web tools

 

Class/Learning activities

Lectures, software packages presentations, web tools presentations, computer assignments, computer laboratory exercises.

 

Workload

Type of work Description Hours
Lectures Thirteen 1-hour lectures 13
Laboratory presentations Thirteen 1-hour presentations 13
Laboratory exercises Thirteen 1-hour exercises 13
Independent study Study of compulsory and optional literature 40-45
Short assignments 4 short assignments after the completion of the core modules 120-140
Final Data Project Create and publish a data project 60-70
Total workload 259-294

 

Assessment

Type of assessment Learning outcome Impact on final grade Date of assessment
Participation in group  discussion 1 10% 1st-3rd week
Laboratory exercises 2-4 20% Regularly
Short assignments 2-4 30% 4th-11th week
Final Data Project 1-4 40% 13th week

 

Required Reading

Data Journalism Handbook, Jonathan Gray, Liliana Bounegru, Lucy Chambers, http://datajournalismhandbook.org/.

Interactive Data Visualization for the Web, Scott Murray, O Reilly 2010.

Data Journalism: Mapping the future, John Mair, Richard Lance Keeble, Abramis Academic Publishing, 2014.

Data Journalism Heist, Paul Bradshaw, LeanPub 2013.

Scraping for Journalists, Paul Bradshaw, LeanPub 2014.