Insightful, substantive and a must-read for anyone working with data visualisation as consumer or designer. Julie Steele and Noah Ilinsky’s new volume – Designing Data Visualisations – from O’Reilly succeeds in applying a long overdue and well crafted taxonomic process to the art of Data Vis. Building on their previous volume – Beautiful Visualisations – the authors take to the underpinnings of the pretty pictures and case studies presented in their edited volume. This shorter work would form a superb basis for an introduction to Data Vis course.
The structure starts with a smooth introduction to the terms that underlie visualisation breaking them down into a lovely typology bridging the discussion between the explanatory versus exploratory uses and techniques. The next section takes the data vis practitioner through the creative process (setting goals, choosing the right visualisation and then building the visualisation itself). This is not a hands-on manual and the use of particular tools is left to other specific volumes, although a list of tools and resources is helpfully provided.
Although a concise volume, the wealth of useful information conveyed as both hints ‘use text sparingly – don’t feel obliged top label every tick mark’ to a five-page colour theory introduction provide hands-on and immediately usable nuggets. The nuggets are often basic – a demonstration of why mixed up lower case letters read easier than upper case letters – but as basic as they are great reminders that it’s all about conveying a message in the most effective way possible. Keeping things clear and concise and ensuring that the technology doesn’t get in the way of the message. The concluding checklist of best practices in data visualisation is a concise summary of the material covered in the book.
I would highly recommend this book to any academic researcher or digital humanities scholar and commend it as a superb overview of the practice of data visualisation.
