![Christina Elmer, Lorenz Matzat (eds.). (2024). Handbuch Daten und KI im Journalismus. [Handbook of Data and AI in Journalism.]](https://journalistik.online/wp-content/uploads/2017/10/cropped-journalistik-hintergrund-groß.png)
Reviewed by Tanjev Schultz
The development of data journalism into a distinct professional field within the media has progressed so far that it can no longer be dismissed as mere »hype.« While the situation may currently still be different for »artificial intelligence« (AI), it is foreseeable that it, too, will soon become a standard tool in most newsrooms. Thus, the handbook edited by Christina Elmer and Lorenz Matzat, with twenty individual contributions covering many facets of the topic, fills a gap in the market for practical literature that few have attempted to address until now. The volume can be a useful companion, not least for students and those in journalism training.
Christina Elmer is a professor in Dortmund; previously, she was deputy head of development at Der Spiegel. Lorenz Matzat was a visiting professor in Leipzig and is one of the pioneers of data journalism in Germany. Thanks to their expertise and contacts, the two were able to assemble a group of competent authors, most of whom come from the field of journalism. At the same time, the handbook also provides insights from and for research, particularly through the contribution by Mario Haim and Valerie Hase on »Data Journalism from a Communication Studies Perspective« and the contribution by Jessica Heesen on the »Ethics of Data-Driven Journalism.«
It is noteworthy that while the volume itself is richly illustrated, it does not succumb to a fetish for numbers and graphics or a naive understanding of data. »Given the supposed inviolability of findings derived from data,« says Heesen, »journalists have a responsibility to critically deconstruct data and, especially in data journalism, to question the supposed objectivity of data.« (p. 218) Guiding questions might include: »Where is data collected? What data is (not) recorded? How is data interpreted and described?« (ibid.)
In the examples of data journalism and AI applications that run throughout the handbook, these questions could perhaps have been posed and answered even more systematically. Overall, however, the essays offer many suggestions and starting points for a reflective approach to data and statistics. This ranges from an overview of data sources that can be drawn upon in journalism, through a presentation of the use of geo- and satellite data, to large language models (LLM) and strategies for AI applications in a newsroom. From local journalism to investigative reporting and international division of labor in handling major leaks, the handbook addresses all currently important operational and organizational issues.
To pick one example: In her essay on the fundamentals and reception of data-driven graphics, Gianna-Carina Grün presents a »checklist for effective visualizations« that newsrooms could put on their desks. Among the questions on this list is: »If the chart is interactive: Is the interaction useful? How could the visualization have been implemented without interaction?« (p. 88) In fact, as a user, one occasionally gets the impression that a graphic contains interactive gimmicks simply because they are possible. Whether they are useful and truly help to uncover and understand something does not always seem to be a priority.
Another example: Uli Köppen explains how the public Bavarian broadcaster Bayerischer Rundfunk handles automation and AI and demonstrates how linear regional news broadcasts are broken down using algorithms so that individual segments can be »tagged« with geolocation – that is, linked to the location of the event – by another algorithm. »This makes our audio content usable for personalization.« (p. 293)
The technical jargon and Anglicisms common in this field might seem a bit annoying or off-putting to some readers. However, they are difficult to avoid. That said, the articles are easy to understand and not unnecessarily complicated. Most of the authors are closely connected to journalistic practice, so their style is correspondingly accessible. While the dynamic developments, especially in AI applications, could quickly make some contributions seem outdated, the handbook currently still feels up-to-date. Thus, in both form and content, it is an asset to journalism and the field of journalism.
About the reviewer
Tanjev Schultz is a professor of journalism at Johannes Gutenberg University in Mainz, Germany. He is one of the editors of Journalistik/Journalism Research – Journal of Journalism Research. Contact: tanjev.schultz@uni-mainz.de
A German version of this review was first published on January 28, 2026, on rezensionen:kommunikation:medien, available at https://www.rkm-journal.de/archives/25900
About this book
Christina Elmer, Lorenz Matzat (eds.). (2024). Handbuch Daten und KI im Journalismus. [Handbook of Data and AI in Journalism.] Herbert von Halem Verlag, 386 pages, 32 euros