Data Journalism: Six books to read

Data Journalism: Six books to read

There many great tutorials online for data-journalists. But especially for beginners, a printed book might be the best way to build initial skills. Here are six recommendations, for starters and practitioners alike.

Photo: Brian Suda, all rights reserved

When learning something new we know that these rules apply: Do it slowly, but steadily - from the first awkward step to running full speed. Do not expect too much in the first phase, be patient and persistent.

Starters need know-how in a variety of fields

Data-Journalism is something that needs to be learned and trained. Not because it is so awfully complex, but because there are several bodies of knowledge that need to be connected and understood: Knowing to tell stories, to search for data, how to refine the data and finally visualize what you found and publish it.

This is why the five books below are very helpful. They all have great content, covering different angles of know-how to get you started. Plus, they have a practical angle, so much of what you will learn can which can be easily be transferred into productive projects of your own quite quickly.

1. The Data-Journalism Handbook

The crowd-sourced book was written by data journalists from around the world and is now published in print. There is a free online version, too. accessed as a free online resource as well. It‘s the first recommendation, because it effectively presents collective experience from many newsrooms and many projects. iPlus: Because the chapters are short, just having it on your bookshelf will introduce you to how journalists around the world approach the task of turning numbers into stories.
This is on the list, because it is so motivating and quite entertaining. If you are starting in data-journalism and have seen only a few examples of what can be done, this is for you.  David McCandless started this book by asking questions to data. In the beginning he was just a curious journalist, not a pro at visualizations. By the end of his process (which is well documented in the back of the book, including the catastrophes that happened) "Information is Beautiful“ is a wonderful collection of visualizations, driven by impressive curiosity and creativity of just one person.

This is the most practical book to understand what makes visualization easy to understand and correct in terms of sizes, axis legends and all the little parts that should be right. Plus: It is a book for people who want to learn. There is a short introduction, then in the main part, Donna M. Wong shows what is usually done wrong when charting and how it should be done. Work with this book for one or two focused days and you will gain much, much knowledge how to create charts, including line charts, multiple line charts, bar charts and pie charts. There is a section on “tricky“situations too.

If you feel you are not a graphic design pro and want to get a quick, easy to understand and correct overview, this is for you.

4. Andrew Dilnot, Michael Blastland: The Tiger that Isn't

Journalists often misread numbers, tend to blow up a trend and like to speculate about future events based on some numbers. More often than not the claims made are embarrassingly wrong.

This is why "data literacy“ or "number literacy“ are important. Instead of snickering at data, every practitioner of data-journalism should be on guard when seeing a new dataset. Sometimes a surprising story is hidden in a spreadsheet, at other times the quality of the data published by some official institution is so bad, that this is the story to publish. This is what "The Tiger that Isn‘t“ is about. It lists up examples, shows why extrapolating a trend from today into the future is often false. P.S.: When shopping for this book, do not be confused by two different titles from the same authors. The book here was published in 2007, later it was re-published for the US with changed examples under the title "The Numbers Game“. If you are European, buy "The Tiger that isn‘t“.

5. Brian Suda, Designing with Data

This is a short book, but it helps to put thinks into perspective. Suda has a great style of writing. The book provides an overview why and how data can be used in visuals. What‘s more is it preaches reducing clutter in infographics and leave out all elements that are not really needed. Short, helpful, great read.
This book shows anyone how to scribble ideas and concepts before actually working with software. It applies even to people who say "I can‘t draw“.

Why is that relevant for data-journalism? There are several reasons: The editor working with the data needs to be the "director“ of a data project. If she or he is not, has no idea of the later outcome and a limited understanding of why some data projects are complex and others are not, there is a high risk that the data project takes much longer and will eventually be left unfinished.

The book teaches you visually thinking, using simple and quick visualization techniques. All you need is a pen, a piece of paper and 10-20 minutes of focus. With the techniques shown in this book everyone can scribble along very fast, firstly answering basic journalistic questions like what, when, where, why and how. We use it in data-journalism trainings all the time. A sample of the process can be found here.
Our tip: Particularly helpful is the 6x6 process - a way to ask (journalistic) questions and then try the most appropriate type of visualization - as a quick drawing. You can use this link a sample of the process. Print this out large and use when discussing your next data project. Pin it on the wall. Throw away the first ideas and start over. Scribbling it first makes iterations easy and fast and helps to find the story. The key process is simple and has been published on the web under various links. Here is one, to provide an example. Even if you don‘t find the time to read that book, do no skip the process of iterative scribbling when starting a any data-journalism project.