The Data Journalism Handbook

Reviewed by Heather McIntosh, Assistant Professor, Minnesota State University, Mankato on 6/29/19

Comprehensiveness rating: 4 see less

The Data Journalism Handbook offers a great overview of the importance of data analysis and visualization in journalism in various environments, including newsrooms and independent organizations. Its key strength lies in the diversity of voices that bring their personal experiences to the subject. The first half of the book sets the foundations. The extensive introduction provides a history, key definitions, and examples. (The 1812 example is particularly interesting.) The second chapter brings data journalism into the newsroom and shows how it relates to newsgathering practices in different venues, particularly emphasizing its value in long-term reporting and journalism traditions. The case studies chapter, chapter 3, shows the extensive possibilities of data journalism through numerous examples from around the world. The second half of the book is more practical. Chapter 4 investigates the challenges and processes of gathering data. Chapter 5 delves into the critical thinking about data from a journalist's perspective and applying that thinking through the processes of working with data, including cleaning and visualizing. The final chapter brings the data analysis and its conclusions to audiences through various forms of data presentation and publication. While the book features extensive images, it would benefit from an index, a glossary, critical thinking questions, chapter conclusions, and short exercises or problems to apply the thinking and the tools.

Content Accuracy rating: 5

Much of the content in this volume comes directly from newsrooms and organizations using data journalism as part of their missions. This grounded perspective helps show the diversity of data journalism and its applications in a way that is accurate and useful for readers.

Relevance/Longevity rating: 4

Published in 2012, the volume contains examples timely to that period. But these examples age well in that they show techniques that still are in use today, which could be a possible example in class for bringing in a more recent example for comparison and discussion. It would be easy to add supplemental paragraphs or examples of more recent applications within the materials already available in the volume. Some links embedded in the volume need to be updated or removed as they are no longer functioning. Further, some discussions of tools need to be removed as the tools are no longer functioning or soon-to-be-retired.

Clarity rating: 3

The book is written mostly by journalists, so the writing is generally clear and accessible. The book includes a lot of international contributors, and that variety of voices makes the book more engaging to read. However, the book assumes a level of knowledge among its readers that might not be clear from the outset. For example, several writers talk about pivot tables, heat maps, algorithms, SQL (server query language), coding, and other terms that students new to data journalism might be unfamiliar with. Some terms, such as web scraping, do gain definition later in the volume, but others go without definition or further explanation. Professors would need to bring these explanations into their instruction.

Consistency rating: 3

The book's primary strength is also its primary weakness. With the diversity of voices and writings comes an inconsistency in content, structure, and tone. While everything is quite readable, with lots of great ideas and themes embedded in the prose, some consistency across these writings is needed. For example, one section contains a list of pros and cons, a tool that would be helpful for readers in multiple places. For another example, one used a header called "Key Insights," which would have been a great tool for processing all the case studies.

Modularity rating: 5

This book is easy to divide into shorter reading segments, such as choosing one or two case studies. The chapters also stand alone well. They can be read without need the other chapters to process them.

Organization/Structure/Flow rating: 4

The book is well organized with the foundations in the first half and the applications in the second half. The topics as presented are clear and accessible for the most part. However, lots of great ideas are buried in the writings that could benefit from more signposting and focus, such as the question about if journalists need to learn code, the emphasis on collaboration, and the struggles of data cleaning, to name three. Sharp readers will see these themes; students might benefit from having them made more apparent.

Interface rating: 5

The formatting is clean, with proper chapter introductions, section headers, and bullet lists. The graphics are informative. The screen shots and photos are relevant to their discussions.

Grammatical Errors rating: 5

The volume is largely free of grammatical errors.

Cultural Relevance rating: 5

The book uses examples from around the world and includes voices of people working around the world as well. While project examples concentrate on Western Europe and North America, they also include Japan and South America. The volume also cautions about making mistaken cultural assumptions during data gathering, cleaning, and analysis, which could result in mistaken reporting, as one key example showed.

Comments

This book offers an engaging introduction to the art of data journalism. It is smart about its thinking regarding data journalism -- not as a novelty, but as a tool to be used critically and carefully. It makes smart points about engaging the practice and its relevance to contemporary journalism. Though published in 2012, the points remain relevant, particularly with the long-term focus that data-driven journalism provides, the respite it creates from "fake news," and the engagement it offers to individual readers. The assumptions the book makes about reader knowledge become opportunities for instructors to provide further skills and applications within the classroom, such as doing data analysis through pivot tables, cleaning data through application, and attempting scraping through code or APIs. The book provides enough foundations and contexts for these activities to be seen as relevant and necessary. While the volume does discuss crowdsourcing at points, further iterations could benefit from a user interaction / user engagement chapter to show the flow among data, visualization, and what users do and why.