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7AAVDM12 Introduction to Data Journalism

Module convenor: Dr Jonathan Gray and Dr Liliana Bounegru 
Teaching pattern: Six one-hour lectures, six one-hour seminars, and one seven-hour intensive workshop
Module description:

What is data journalism? What kinds of techniques and approaches are journalists using to create, use and tell stories with data? How can data be used for analysis but also for interactivity?

In the last few years, journalists have been experimenting with different techniques for investigation, analysis, storytelling and interactivity with digital data. These developments have been referred to as “data journalism”. This module will explore this emerging field, including how digital data is being put to work to enable different forms of making sense, telling stories and involving publics.

Students will learn how to develop a “critical data practice” for understanding and working with data. This will include critically reflecting on the data sources, tools, techniques and methods of data journalism through a series of readings, as well as learning how to assemble, clean, analyse, visualise and tell stories with data through their own projects.

Draft teaching syllabus

Week 1 (lecture) | Introduction to the different traditions of data journalism

Week 2 (lecture & seminar) | Finding data

Week 3 (lecture & seminar) | Treating data

Week 4 (Self-guided learning) | Corpus collection

Week 5 (lecture & seminar) | Visualising data

Week 6 (lecture & seminar) | Narrating data

Week 7 (self-guided learning) | Corpus preparation

Week 8 (lecture & seminar) | Review of the projects in preparation for the workshop

Week 9 (intensive workshop) | Data newsroom hands-on workshop

Week 10 (lecture & seminar) | Conclusion: taking stock of the course

* Note: This is a sample outline of the teaching schedule.

Module aims

This module aims to:

  • Provide an introduction to the field of data journalism, as well as research about it and practices, methods and technologies associated with it;
  • Develop a sensibility for “critical data practice” by combining hands-on experimentation with key readings from research about data journalism and associated developments;
  • Learn about different ways of telling stories with data, as well as critically accounting for the socio-technical infrastructures and practices involved in creating, using and sharing data in journalism.

Learning outcomes

By the end of this module students will be able to:

  • Understand and account for what is involved in assembling, analysing, visualising and telling stories with digital data from a variety of sources;
  • Design, implement and reflect on their own data journalism project;
  • Critically assess and engage with recent research and debates about data journalism and the politics of data from a range of disciplinary perspectives, including science and technology studies, media studies and internet studies;
  • Analyse and empirically study conventions and practices associated with data journalism in the context of social and cultural research on quantification and datafication.

Core reading

  • Gray, J., Bounegru, L., & Chambers, L. (Eds.). (2012). The Data Journalism Handbook. Sebastopol, CA: O’Reilly Media. Available at:
  • Gray, J. & Bounegru, L. (Eds.). (forthcoming). The Data Journalism Handbook: Towards a Critical Data Practice. Amsterdam: Amsterdam University Press.
  • Bounegru, L., Venturini, T., Gray, J., Jacomy, M. (2016) “Narrating Networks: Exploring the Affordances of Networks as Storytelling Devices in Journalism”, Digital Journalism.
  • Gray, J., Lämmerhirt, D. and Bounegru, L. (2016). Changing What Counts: How Can Citizen-Generated and Civil Society Data Be Used as an Advocacy Tool to Change Official Data Collection? Available at SSRN:


The assessment is based on the results produced during the intensive
workshop and on a short journalistic piece that each student will individually write around them.

The modules run in each academic year are subject to change in line with staff availability and student demand so there is no guarantee every module will run. Module descriptions and information may vary depending between years.  

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