Visualising data a handbook for data driven design

Data Visualisation

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Data Visualisation

A Handbook for Data Driven Design

2nd Edition

Andy Kirk

Los Angeles London

New Delhi Singapore

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SAGE Publications Ltd

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© Andy Kirk 2019

First edition published 2016. Reprinted four times in 2016, twice in 2017, three times in 2018, and three times in 2019.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act, 1988, this publication may be reproduced, stored or transmitted in any form, or by any means, only with the prior permission in writing of the publishers, or in the case of reprographic reproduction, in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers.

Library of Congress Control Number: 2018964578

British Library Cataloguing in Publication data

A catalogue record for this book is available from the British Library

ISBN 978-1-5264-6893-2

ISBN 978-1-5264-6892-5 (pbk)

Editor: Aly Owen

Editorial assistant: Lauren Jacobs

Production editor: Ian Antcliff

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Copyeditor: Neville Hankins

Proofreader: Christine Bitten

Indexer: David Rudeforth

Marketing manager: Susheel Gokarakonda

Cover design: Shaun Mercier

Typeset by: C&M Digitals (P) Ltd, Chennai, India

Printed in the UK

At SAGE we take sustainability seriously. Most of our products are printed in the UK using responsibly sourced papers and boards. When we print overseas we ensure sustainable papers are used as measured by the PREPS grading system. We undertake an annual audit to monitor our sustainability.

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Contents

Acknowledgements About the Author Discover Your Textbook’s Online Resources Introduction PART A FOUNDATIONS

1 Defining Data Visualisation 2 The Visualisation Design Process

PART B THE HIDDEN THINKING 3 Formulating Your Brief 4 Working With Data 5 Establishing Your Editorial Thinking

PART C DEVELOPING YOUR DESIGN SOLUTION 6 Data Representation 7 Interactivity 8 Annotation 9 Colour 10 Composition

Epilogue References Index

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Acknowledgements

I could not have written this book without the unwavering support of my wonderful wife, Ellie, and my family. The book is dedicated to my inspirational Dad who sadly passed away before its publication. I want to acknowledge the contributions of the thousands of data visualisation practitioners who have created such a wealth of exceptional design work and smart writing. I have been devouring this for over a decade now and I am constantly inspired by the talents and minds behind it all. I also want to express my gratitude to the people and organisations who have granted me permission to reference and showcase their visualisation work in this book. Sincere thanks to the many people at Sage who have played a role in making this book grow from the first proposal and now to a second edition. Finally, to you the readers, I am hugely thankful that you chose to invest in this book. I hope it helps you in your journey to learning about this super subject.

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About the Author

Andy Kirk is a freelance data visualisation specialist based in Yorkshire, UK. He is a visualisation design consultant, training provider, teacher, author, speaker, researcher and editor of the award- winning website visualisingdata.com.

After graduating from Lancaster University in 1999 with a BSc (hons) in Operational Research, Andy’s working life began with a variety of business analysis and information management roles at organisations including CIS Insurance, West Yorkshire Police and the University of Leeds. He discovered data visualisation in early 2007, when it was lurking somewhat on the fringes of the Web. Fortunately, the timing of this discovery coincided with his shaping of his Master’s (MA) degree research proposal, a self-directed research programme that gave him the opportunity to unlock and secure his passion for the subject. He launched visualisingdata.com to continue the process of discovery and to chart the course of the increasing popularity of the subject. Over time, this award-winning site has grown to become a popular reference for followers of the field, offering contemporary discourse, design techniques and vast collections of visualisation examples and resources. Andy became a freelance professional in 2011. Since then he has been fortunate to work with a diverse range of clients across the world, including organisations such as Google, CERN, Electronic Arts, the EU Council, Hershey and McKinsey. At the time of publication, he will have delivered over 270 public and private training events in 25 different countries, reaching more than 6000 delegates. Alongside his busy training schedule, Andy also provides design consultancy, his primary client being the Arsenal FC Performance Team, since 2015. In addition to his commercial activities, he maintains regular engagements in academia. Between 2014 and 2015 he was an external consultant on a research project called ‘Seeing Data’, funded by the Arts & Humanities Research Council and hosted by the University of Sheffield. This study explored the issues of data visualisation literacy among the general public and, inter alia, helped to shape an understanding of the human factors that affect visualisation literacy and the effectiveness of design. Andy joined the highly respected Maryland Institute College of Art (MICA) as a visiting lecturer in 2013 teaching a module on the Information Visualisation Master’s Programme through to 2017. From January 2016, he taught a data visualisation module as part of the MSc in Business Analytics at the Imperial College Business School in London through to 2018. As of May 2019, Andy has started teaching at University College London (UCL).

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Discover Your Textbook’s Online Resources

Want more support around understanding and creating data visualisations? Andy Kirk is here to help, offline and on!

Hosted by the author and with resources organized by chapter, the supporting website for this book has everything you need to explore, practice, and hone your data visualisation skills.

Explore the field: expand your knowledge and reinforce your learning about working with data through libraries of further reading, references, and tutorials. Try this yourself: revise, reflect, and refine your skill and understanding about the challenges of working with data through practical exercises. See data visualisation in action: get to grips with the nuances and intricacies of working with data in the real world by navigating instalments of the narrative case study and seeing an additional extended example of data visualisation in practice. Follow along with Andy’s video diary of the process and get direct insight into his thought processes, challenges, mistakes, and decisions along the way. Chartmaker directory: access crowd-sourced guidance that aims to answer the crucial question ‘which tools make which charts?’ with this growing directory of examples and technical solutions for chart building.

Ready to learn more? Go beyond the book and dive deeper into data visualisation via the rest of Andy’s website (www.visualisingdata.com), which contains data visualisation tools and software, links to additional influential further reading, and a blog with monthly collections of the best data visualisation examples and resources each month.

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http://www.visualisingdata.com
Introduction

The primary challenge one faces when writing a book about data visualisation is to determine what to leave in and what to leave out. Data visualisation is a big subject. There is no single book to rule it all because there is no one book that can truly cover it all. Each and every one of the topics covered by the chapters in this book could (and, in several cases, do) exist as books in their own right.

The secondary challenge when writing a book about data visualisation is to decide how to weave the content together. Data visualisation is not rocket science; it is not an especially complicated discipline, though it can be when working on sophisticated topics and with advanced applications. It is, however, a complex subject. There are lots of things to think about, many things to do and, of course, things that will need making. Creative and journalistic sensibilities need to blend harmoniously with analytical and scientific judgement. In one moment, you might be checking the statistical rigour of an intricate calculation, in the next deciding which shade of orange most strikingly contrasts with a vibrant blue. The complexity of data visualisation manifests in how the myriad small ingredients interact, influence and intersect to form a whole.

The decisions I have made when formulating this book’s content have been shaped by my own process of learning. I have been researching, writing about and practising data visualisation for over a decade. I believe you only truly learn about your own knowledge of a subject when you have to explain it and teach it to others. To this extent I have been fortunate to have had extensive experience designing and delivering commercial training as well as academic teaching.

I believe this book offers an effective and proven pedagogy that successfully translates the complexities of this subject in a form that is fundamentally useful. I feel well placed to bridge the gap between the everyday practitioners, who might identify themselves as beginners, and the superstar talents expanding the potential of data visualisation. I am not going to claim to belong to the latter cohort, but I have certainly been a novice, taking tentative early steps into this world. Most of my working hours are spent helping others start their journey. I know what I would have valued when I started out in this field and this helps inform how I now pass this on to others in the same position I was several years ago.

There is a large and growing library of fantastic books offering different theoretical and practical viewpoints on this subject. My aim is to add value to this existing collection by approaching the subject through the perspective of process. I believe the path to mastering data visualisation is achieved by making better decisions: namely, effective choices, efficiently made. I will help you understand what decisions need to be made and give you the confidence to make the right choices. Before moving on to discuss the book’s intended audience, here are its key aims:

To challenge your existing approaches to creating and consuming visualisations. I will challenge your beliefs about what you consider to be effective or ineffective visualisation. I will encourage you to eliminate arbitrary choices from your thinking, rely less on taste and instinct, and become more reasoned in your judgements. To enlighten you I will increase your awareness of the possible approaches to visualising

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data. This book will broaden your visual vocabulary, giving you a wider and more sophisticated understanding of the contemporary techniques used to express your data visually. To equip is to provide you with robust tactics for managing your way through the myriad options that exist in data visualisation. To help you overcome the burden of choice, an adaptable framework is offered to help you think for yourself, rather than relying on inflexible rules and narrow instruction. To inspire is to open the door to a subject that will stimulate you to elevate your ambition and broaden your confidence. Developing competency in data visualisation will take time and will need more than just reading this book. It will require a commitment to embrace the obstacles that each new data visualisation opportunity poses through practice. It will require persistence to learn, apply, reflect and improve.

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Who Is This Book Aimed At?

Anyone who has reason to use quantitative and qualitative methods in their professional or academic duties will need to grasp the demands of data visualisation. Whether this is a large part of your duties or just a small part, this book will support your needs.

The primary intended audiences are undergraduates, postgraduates and early-career researchers. Although aimed at those in the social sciences, the content will be relevant to readers from across the spectrum of arts and humanities right through to the natural sciences.

This book is intended to offer an accessible route for novices to start their data visualisation learning journey and, for those already familiar with the basics, the content will hopefully contribute to refining their capabilities. It is not aimed at experienced or established visualisation practitioners, though there may be some new perspectives to enrich their thinking: some content will reinforce existing knowledge, other content might challenge their convictions.

The people who are active in this field come from all backgrounds. Outside academia, data visualisation has reached the mainstream consciousness in professional and commercial contexts. An increasing number of professionals and organisations, across all industry types and sizes, are embracing the importance of getting more value from their data and doing more with it, for both internal and external benefit. You might be a market researcher, a librarian or a data analyst looking to enhance your data capabilities. Perhaps you are a skilled graphic designer or web developer looking to take your portfolio of work into a more data-driven direction. Maybe you are in a managerial position and though not directly involved in the creation of visualisation work, you might wish to improve the sophistication of the language you coordinate or commission others who are. Everyone needs the lens and vocabulary to evaluate work effectively.

Data visualisation is a genuinely multidisciplinary discipline. Nobody arrives fully formed with all constituent capabilities. The pre-existing knowledge, skills or experiences which, I think, reflect the traits needed to get the most out of this book would include:

Strong numeracy is necessary as well as a familiarity with basic statistics. While it is reasonable to assume limited prior knowledge of data visualisation, there should be a strong desire to want to learn it. The demands of learning a craft like this take time and effort; the capabilities will need nurturing through ongoing learning and practice. They are not going to be achieved overnight or acquired alone from reading this book. Any book that claims to be able magically to inject mastery through just reading it cover to cover is over- promising and likely to under-deliver. The best data visualisers possess inherent curiosity. You should be the type of person who is naturally disposed to question the world around them. Your instinct for discovering and sharing answers will be at the heart of this activity. There are no expectations of your having any prior familiarity with design principles, but an appetite to embrace some of the creative aspects presented in this book will heighten the impact of your work. Time to unleash that suppressed imagination! If you are somebody fortunate to possess already a strong creative flair, this book will guide you through when and crucially when not to tap into this sensibility. You should be willing

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to increase the rigour of your analytical decision making and be prepared to have your creative thinking informed more fundamentally by data rather than just instinct. No particular technical skills are required to get value from this book, as I will explain shortly. But you will ideally have some basic knowledge of spreadsheets and experience of working with data irrespective of which particular tool.

This is a portable practice involving techniques that are subject-matter agnostic. Throughout this book you will see a broad array of examples from different industries covering many different topics. Do not be deterred by any example being about a subject different to your own area of interest. Look beyond the subject and you will see analytical and design choices that are just as applicable to you and your work: a line chart showing political forecasts involves the same thought process as would a line chart showing stock prices changing or average global temperatures rising. A line chart is a line chart, regardless of the subject matter.

The type of data you are working with is the only legitimate restriction to the design methods you might employ, not your subject and certainly not traditions in your subject. ‘Waterfall charts are only for people in finance’, ‘maps are only for cartographers’, ‘Sankey diagrams are only for engineers’. Enter this subject with an open mind, forget what you believe or have been told is the normal approach, and your capabilities will be expanded.

Data visualisation is an entirely global community, not the preserve of any geographic region. Although the English language dominates written discourse, the interest in the subject and work created from studios through to graphics teams originates everywhere. There are cultural influences and different flavours in design sensibility around the world which enrich the field but, otherwise, it is a practice common and accessible to all.

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Finding the Balance

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Handbook vs Manual

The description of this book as a ‘handbook’ positions it as distinct from a tutorial-based manual. It aims to offer conceptual and practical guidance, rather than technical instruction. Think of it more as a guidebook for a tourist visiting a city than an instruction manual for how to fix a washing machine.

Apart from a small proportion of visualisation work that is created manually, the reliance on technology to create visualisation work is an inseparable necessity. For many beginners in visualisation there is an understandable appetite for step-by-step tutorials that help them immediately to implement their newly acquired techniques.

However, writing about data visualisation through the lens of selected tools is hard, given the diversity of technical options that exist in the context of such varied skills, access and needs. The visualisation technology space is characterised by flux. New tools are constantly emerging to supplement the many that already exist. Some are proprietary, others are open source; some are easier to learn but do not offer much functionality; others do offer rich potential but require a great deal of foundation understanding before you even accomplish your first bar chart. Some tools evolve to keep up with current techniques; they are well supported by vendors and have thriving user communities, others less so. Some will exist as long-term options whereas others depreciate. Many have briefly burnt brightly but quickly become obsolete or have been swallowed up by others higher up the food chain. Tools come and go but the craft remains.

There is a role for all book types and a need for more than one to acquire true competency in a subject. Different people want different sources of insight at different stages in their development. If you are seeking a text that provides instructive tutorials, you will learn from this how to accomplish technical developments in a given technology. However, if you only read tutorial-based books, you will likely fall short in the fundamental critical thinking that will be needed to harness data visualisation as a skill.

I believe a practical, rather than technical, text focusing on the underlying craft of data visualisation through a tool-agnostic approach offers the most effective guide to help people learn this subject.

The content of this book will be relevant to readers regardless of their technical knowledge and experience. The focus will be to take your critical thinking towards a detailed, fully reasoned design specification – a declaration of intent of what you want to develop. Think of the distinction as similar to that between architecture (design specification) and engineering (design execution).

There is a section in Chapter 3 that describes the influence technology has on your work and the places it will shape your ambitions. Furthermore, among the digital resources offered online are further profiles of applications, tools and libraries in common use in the field today and a vast directory of resources offering instructive tutorials. These will help you to apply technically the critical capabilities you acquire throughout this book.

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Useful vs Beautiful

Another important distinction to make is that this book is not intended to be seen as a beauty pageant. I love flicking through glossy ‘coffee table’ books as they offer great inspiration, but often lack substance beyond the evident beauty. This book serves a different purpose to that. I believe, for a beginner or relative beginner, the most valuable inspiration comes more from understanding the thinking behind some of the amazing works encountered today, learning about the decisions that led to their conceptual development.