The Data Journalism Handbook

Reviewed by Megan Duncan, assistant professor, Virginia Tech on 12/8/21

Comprehensiveness rating: 4 see less

This textbook covers many, many case studies and examples. It's lighter on the tangible skills, details, and complexities that can be applied to the projects the students would encounter.

Content Accuracy rating: 5

At the time that this book was written, I found no untrue or incorrect info. A lot has changed since then, though, and people, software and ways of doing work aren't as relevant now.

Relevance/Longevity rating: 3

It's been a decade since the book was written. This book serves as a historical text that shows how the industry was born and who was responsible for early decisions. However, the quickly-developing state of data journalism has made this text age faster than that a more developed discipline. There's a beta version of a second edition available online (also free!) that has excellent updates.

Clarity rating: 4

The students appreciated the examples and generalized principles. They were often not sure how to use those ideas in practice. The text could be more clear about how to make decisions, specific skills, and tangible techniques for the students to put into practice.

Consistency rating: 5

I found to the text to be highly consistent.

Modularity rating: 5

Students appreciated reading only chapters of the text because it was always a quick and breezy read, not loaded down by context from previous chapters.

Organization/Structure/Flow rating: 5

The outline of the text is logical and easy to understand. Yet, it is also quite modular. You don't have to read it front to back to understand.

Interface rating: 5

Never any navigation or UX issues.

Grammatical Errors rating: 5

The text is well-written.

Cultural Relevance rating: 5

Lots of international examples to help students think about data journalism's role globally.

Reviewed by Geoffrey Campbell, Adjunct Assistant Professor, University of Texas at Arlington on 4/9/21

Comprehensiveness rating: 4 see less

This is an engaging text that shows student journalists why data journalism is important--and the vital stories they can tell with it. While it would be an improvement if the text spent more time on helping students understand how to gather, sift and interpret data, this is nonetheless an important resource for anyone teaching or studying the field.

Content Accuracy rating: 5

This textbook does a terrific job of accurately explaining the Himalayas of data available, but instructors will have to roll up their sleeves to show students how to harvest it. And that's actually OK because tools for sifting and analyzing data are changing all the time. If the text got too far into the weeds, it would have to be updated with troublesome regularity. That being said, spending some time on how to look at data tables and understand what they can tell you--and what they can't--would be a useful addition.

Relevance/Longevity rating: 5

While it's true that data can be fudged or misinterpreted (correlation does not imply causation, for example), the use of data in journalism can provide a bedrock of facts that can enhance credibility. By showing readers the kind of stories that can be bolstered by the use of credible data, this book is not only relevant but vital. That's especially true in a period in which journalists are cursed and attacked--and their work labeled as "fake news." By tethering their stories to credible data, journalists can show they're honoring their obligation to truth.

Clarity rating: 5

One of the text's greatest strengths is its clarity. The text's contributors are practicing journalists who understand that the industry's practitioners have a native distaste for numbers and math. The same is naturally true for journalism students, and this easy-to-read text can inspire student journalists to overcome their distaste and phobia and make a foray into this rich and growing field.

Consistency rating: 5

While written by a host of contributors, this text is remarkably consistent in its use of terminology and intellectual framework.

Modularity rating: 5

This text provides information in easy-to-digest chunks, which makes it perfect for student journalists who may have mental blocks about anything having to do with numbers and spreadsheets. It is also tailor-made for the instructor who might want to combine a chunk of a later chapter with a chunk of material earlier in the text.

Organization/Structure/Flow rating: 5

The book's organization is sensible, progressing in a way that helps the reader gain knowledge, retain it and enlarge upon it as he/she/they go through the text.

Interface rating: 5

This text is easy-to-use and easy-to-follow. I encountered no navigation problems, and nothing came out distorted or pixelated.

Grammatical Errors rating: 5

While the careful reader might encounter an odd typo or two, the text does not contain anything so glaring as to push the reader away. One thing that may be distracting to some readers is the use of British English in the spellings of some words, but that's certainly not enough to pull the reader out of the narrative.

Cultural Relevance rating: 5

The focus of this text is on data and data analysis, so it does not delve into cultural issues. That being said, the close reader will be able to see opportunities for data journalism stories that touch on hot-button cultural issues, like income inequality, disparate treatment in criminal justice and health outcomes by race and sex.

Comments

While data journalism is growing in importance, there are remarkably few salient textbooks available. The Data Journalism Handbook is a welcome addition to the canon. It's an accessible book, allowing the reader without any previous experience in the field to learn and grow. I am proudly adopting it as my text for the data journalism course I teach.

Reviewed by James Spencer, Washington correspondent and Adjunct Professor, The George Washington University on 1/27/21

Comprehensiveness rating: 4 see less

This textbook thoroughly explains the why of data journalism and what data journalism can accomplish. It needs more focus on the how of data journalism. No one can use data if they are not taught how to gather it in the first pl;ace.

Content Accuracy rating: 5

The book accurately reflects the wealth of data avaialble to journalists who understand how to mine it.

Relevance/Longevity rating: 5

In an era when journalists are dismissed as fakes, liars and enemies of the people, data reinforces the credibility of media focused on truth rather than propaganda.

Clarity rating: 4

The collective contributors generally write in understandable prose. They use graphic devices to add to the ability of people interested in pursuing data journalism to get a basic gist for what possibilities exist. But the book needs to do less promoting of the value of data journalism and more to build a practical foundation upon which novice data gatherers can build to more sophisticated information searches.

Consistency rating: 5

For what it covers, the book is remarkably consistent.

Modularity rating: 5

The format offers small bites of information. That is a critical element for technical subject matter.

Organization/Structure/Flow rating: 5

The progression of chapters and the organization within each chapter allows for a logical path to understanding the book.

Interface rating: 5

The textbook is easy to move through and visually consistent.

Grammatical Errors rating: 5

The book has a few typos, but not enough to distract from or confuse the message.

Cultural Relevance rating: 5

There is not really a discussion of culture. This is about data anlysis.

Comments

I think with a little more emphasis on how to gather data to go along with the explanation of why it matters, the book could fit easily into a journalism curriculum.

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.