Refer to the attached dataset and address each of the following three questions. Each response should be 2-3 paragraphs with an explanation of all terms and reasons for your decisions.
Identify a chart type that could be used to display different editorial perspectives of your dataset and explain why you felt it to be appropriate.
Identify two other chart types that could show something about your subject matter, though maybe not confined to the data you are looking at. In other words, chart types that could incorporate data not already included in your selected dataset.
Review the classifying chart families in Chapter 6 of your textbook. Select at least one chart type from each of the classifying chart families (CHRTS) that could portray different editorial perspectives about your subject. This may include additional data, not already included in your selected dataset.
Data Visualisation
2
3
Data Visualisation
A Handbook for Data Driven Design
Andy Kirk
4
SAGE Publications Ltd
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Andy Kirk 2016
First published 2016
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: 2015957322
British Library Cataloguing in Publication data
A catalogue record for this book is available from the British Library
ISBN 978-1-4739-1213-7
ISBN 978-1-4739-1214-4 (pbk)
Editor: Mila Steele
Editorial assistant: Alysha Owen
Production editor: Ian Antcliff
Marketing manager: Sally Ransom
Cover design: Shaun Mercier
Typeset by: C&M Digitals (P) Ltd, Chennai, India
Printed and bound in Great Britain by Bell and Bain Ltd, Glasgow
6
Contents
List of Figures with Source Notes
Acknowledgements
About the Author
INTRODUCTION
PART A FOUNDATIONS
1 Defining Data Visualisation
2 Visualisation Workflow
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
PART D DEVELOPING YOUR CAPABILITIES
11 Visualisation Literacy
References
Index
7
List of Figures with Source Notes
1.1 A Definition for Data Visualisation 19
1.2 Per Capita Cheese Consumption in the U.S., by Sarah Slobin
(Fortune magazine) 20
1.3 The Three Stages of Understanding 22
1.46 Demonstrating the Process of Understanding 2427
1.7 The Three Principles of Good Visualisation Design 30
1.8 Housing and Home Ownership in the UK, by ONS Digital
Content Team 33
1.9 Falling Number of Young Homeowners, by the Daily Mail 33
1.10 Gun Deaths in Florida (Reuters Graphics) 34
1.11 Iraqs Bloody Toll, by Simon Scarr (South China Morning Post)
34
1.12 Gun Deaths in Florida Redesign, by Peter A. Fedewa
(@pfedewa) 35
1.13 If Vienna would be an Apartment, by NZZ (Neue Zrcher
Zeitung) [Translated] 45
1.14 Asia Loses Its Sweet Tooth for Chocolate, by Graphics
Department (Wall Street Journal) 45
2.1 The Four Stages of the Visualisation Workflow 54
3.1 The Purpose Map 76
3.2 Mizzous Racial Gap Is Typical On College Campuses, by
FiveThirtyEight 77
3.3 Image taken from Wealth Inequality in America, by YouTube
user Politizane (www.youtube.com/watch?v=QPKKQnijnsM) 78
3.4 Dimensional Changes in Wood, by Luis Carli (luiscarli.com) 79
3.5 How Yall, Youse and You Guys Talk, by Josh Katz (The New
York Times) 80
3.6 Spotlight on Profitability, by Krisztina Szcs 81
3.7 Countries with the Most Land Neighbours 83
3.8 Buying Power: The Families Funding the 2016 Presidential
Election, by Wilson Andrews, Amanda Cox, Alicia DeSantis, Evan
Grothjan, Yuliya Parshina-Kottas, Graham Roberts, Derek Watkins
and Karen Yourish (The New York Times) 84
3.9 Image taken from Texas Department of Criminal Justice
Website
(www.tdcj.state.tx.us/death_row/dr_executed_offenders.html) 86
8
3.10 OECD Better Life Index, by Moritz Stefaner, Dominikus Baur,
Raureif GmbH 89
3.11 Losing Ground, by Bob Marshall, The Lens, Brian Jacobs and
Al Shaw (ProPublica) 89
3.12 Grape Expectations, by S. Scarr, C. Chan, and F. Foo (Reuters
Graphics) 91
3.13 Keywords and Colour Swatch Ideas from Project about
Psychotherapy Treatment in the Arctic 92
3.14 An Example of a Concept Sketch, by Giorgia Lupi of Accurat 92
4.1 Example of a Normalised Dataset 99
4.2 Example of a Cross-tabulated Dataset 100
4.3 Graphic Language: The Curse of the CEO, by David Ingold and
Keith Collins (Bloomberg Visual Data), Jeff Green (Bloomberg
News) 101
4.4 US Presidents by Ethnicity (1789 to 2015) 114
4.5 OECD Better Life Index, by Moritz Stefaner, Dominikus Baur,
Raureif GmbH 116
4.6 Spotlight on Profitability, by Krisztina Szcs 117
4.7 Example of Transforming to Convert Data 119
4.8 Making Sense of the Known Knowns 123
4.9 What Good Marathons and Bad Investments Have in Common,
by Justin Wolfers (The New York Times) 124
5.1 The Fall and Rise of U.S. Inequality, in Two Graphs Source:
World Top Incomes Database; Design credit: Quoctrung Bui (NPR)
136
5.24 Why Peyton Mannings Record Will Be Hard to Beat, by
Gregor Aisch and Kevin Quealy (The New York Times) 138140
C.1 Mockup Designs for Poppy Field, by Valentina DEfilippo
(design); Nicolas Pigelet (code); Data source: The Polynational War
Memorial, 2014 (poppyfield.org) 146
6.1 Mapping Records and Variables on to Marks and Attributes 152
6.2 List of Mark Encodings 153
6.3 List of Attribute Encodings 153
6.4 Bloomberg Billionaires, by Bloomberg Visual Data (Design and
development), Lina Chen and Anita Rundles (Illustration) 155
6.5 Lionel Messi: Games and Goals for FC Barcelona 156
6.6 Image from the Home page of visualisingdata.com 156
6.7 How the Insane Amount of Rain in Texas Could Turn Rhode
Island Into a Lake, by Christopher Ingraham (The Washington Post)
156
9
6.8 The 10 Actors with the Most Oscar Nominations but No Wins
161
6.9 The 10 Actors who have Received the Most Oscar Nominations
162
6.10 How Nations Fare in PhDs by Sex Interactive, by Periscopic;
Research by Amanda Hobbs; Published in Scientific American 163
6.11 Gender Pay Gap US, by David McCandless, Miriam Quick
(Research) and Philippa Thomas (Design) 164
6.12 Who Wins the Stanley Cup of Playoff Beards? by Graphics
Department (Wall Street Journal) 165
6.13 For These 55 Marijuana Companies, Every Day is 4/20, by Alex
Tribou and Adam Pearce (Bloomberg Visual Data) 166
6.14 UK Public Sector Capital Expenditure, 2014/15 167
6.15 Global Competitiveness Report 20142015, by Bocoup and the
World Economic Forum 168
6.16 Excerpt from a Rugby Union Player Dashboard 169
6.17 Range of Temperatures (F) Recorded in the Top 10 Most
Populated Cities During 2015 170
6.18 This Chart Shows How Much More Ivy League Grads Make
Than You, by Christopher Ingraham (The Washington Post) 171
6.19 Comparing Critics Scores (Rotten Tomatoes) for Major Movie
Franchises 172
6.20 A Career in Numbers: Movies Starring Michael Caine 173
6.21 Comparing the Frequency of Words Used in Chapter 1 of this
Book 174
6.22 Summary of Eligible Votes in the UK General Election 2015
175
6.23 The Changing Fortunes of Internet Explorer and Google Chrome
176
6.24 Literarcy Proficiency: Adult Levels by Country 177
6.25 Political Polarization in the American Public, Pew Research
Center, Washington, DC (February, 2015) (http://www.people-
press.org/2014/06/12/political-polarization-in-the-american-public/)
178
6.26 Finviz (www.finviz.com) 179
6.27 This Venn Diagram Shows Where You Can Both Smoke Weed
and Get a Same-Sex Marriage, by Phillip Bump (The Washington
Post) 180
6.28 The 200+ Beer Brands of SAB InBev, by Maarten Lambrechts
for Mediafin: www.tijd.be/sabinbev (Dutch),
10
www.lecho.be/service/sabinbev (French) 181
6.29 Which Fossil Fuel Companies are Most Responsible for Climate
Change? by Duncan Clark and Robin Houston (Kiln), published in
the Guardian, drawing on work by Mike Bostock and Jason Davies
182
6.30 How Long Will We Live And How Well? by Bonnie
Berkowitz, Emily Chow and Todd Lindeman (The Washington Post)
183
6.31 Crime Rates by State, by Nathan Yau 184
6.32 Nutrient Contents Parallel Coordinates, by Kai Chang
(@syntagmatic) 185
6.33 How the Avengers Line-up Has Changed Over the Years, by
Jon Keegan (Wall Street Journal) 186
6.34 Interactive Fixture Molecules, by @experimental361 and
@bootifulgame 187
6.35 The Rise of Partisanship and Super-cooperators in the U.S.
House of Representatives. Visualisation by Mauro Martino, authored
by Clio Andris, David Lee, Marcus J. Hamilton, Mauro Martino,
Christian E. Gunning, and John Armistead Selde 188
6.36 The Global Flow of People, by Nikola Sander, Guy J. Abel and
Ramon Bauer 189
6.37 UK Election Results by Political Party, 2010 vs 2015 190
6.38 The Fall and Rise of U.S. Inequality, in Two Graphs. Source:
World Top Incomes Database; Design credit: Quoctrung Bui (NPR)
191
6.39 Census Bump: Rank of the Most Populous Cities at Each
Census, 17901890, by Jim Vallandingham 192
6.40 Coal, Gas, Nuclear, Hydro? How Your State Generates Power.
Source: U.S. Energy Information Administration, Credit: Christopher
Groskopf, Alyson Hurt and Avie Schneider (NPR) 193
6.41 Holdouts Find Cheapest Super Bowl Tickets Late in the Game,
by Alex Tribou, David Ingold and Jeremy Diamond (Bloomberg
Visual Data) 194
6.42 Crude Oil Prices (West Texas Intermediate), 19852015 195
6.43 Percentage Change in Price for Select Food Items, Since 1990,
by Nathan Yau 196
6.44 The Ebb and Flow of Movies: Box Office Receipts 19862008,
by Mathew Bloch, Lee Byron, Shan Carter and Amanda Cox (The
New York Times) 197
6.45 Tracing the History of N.C.A.A. Conferences, by Mike Bostock,
11
Shan Carter and Kevin Quealy (The New York Times) 198
6.46 A Presidential Gantt Chart, by Ben Jones 199
6.47 How the Avengers Line-up Has Changed Over the Years, by
Jon Keegan (Wall Street Journal) 200
6.48 Native and New Berliners How the S-Bahn Ring Divides the
City, by Julius Trger, Andr Ptzold, David Wendler (Berliner
Morgenpost) and Moritz Klack (webkid.io) 201
6.49 How Yall, Youse and You Guys Talk, by Josh Katz (The New
York Times) 202
6.50 Heres Exactly Where the Candidates Cash Came From, by Zach
Mider, Christopher Cannon, and Adam Pearce (Bloomberg Visual
Data) 203
6.51 Trillions of Trees, by Jan Willem Tulp 204
6.52 The Racial Dot Map. Image Copyright, 2013, Weldon Cooper
Center for Public Service, Rector and Visitors of the University of
Virginia (Dustin A. Cable, creator) 205
6.53 Arteries of the City, by Simon Scarr (South China Morning
Post) 206
6.54 The Carbon Map, by Duncan Clark and Robin Houston (Kiln)
207
6.55 Election Dashboard, by Jay Boice, Aaron Bycoffe and Andrei
Scheinkman (Huffington Post). Statistical model created by Simon
Jackman 208
6.56 London is Rubbish at Recycling and Many Boroughs are Getting
Worse, by URBS London using London Squared Map 2015
www.aftertheflood.co 209
6.57 Automating the Design of Graphical Presentations of Relational
Information. Adapted from McKinlay, J. D. (1986). ACM
Transactions on Graphics, 5(2), 110141. 213
6.58 Comparison of Judging Line Size vs Area Size 213
6.59 Comparison of Judging Related Items Using Variation in Colour
(Hue) vs Variation in Shape 214
6.60 Illustrating the Correct and Incorrect Circle Size Encoding 216
6.61 Illustrating the Distortions Created by 3D Decoration 217
6.62 Example of a Bullet Chart using Banding Overlays 218
6.63 Excerpt from Whats Really Warming the World? by Eric
Roston and Blacki Migliozzi (Bloomberg Visual Data) 218
6.64 Example of Using Markers Overlays 219
6.65 Why Is Her Paycheck Smaller? by Hannah Fairfield and Graham
Roberts (The New York Times) 219
12
6.66 Inside the Powerful Lobby Fighting for Your Right to Eat Pizza,
by Andrew Martin and Bloomberg Visual Data 220
6.67 Excerpt from Razor Sales Move Online, Away From Gillette,
by Graphics Department (Wall Street Journal) 220
7.1 US Gun Deaths, by Periscopic 225
7.2 Finviz (www.finviz.com) 226
7.3 The Racial Dot Map: Image Copyright, 2013, Weldon Cooper
Center for Public Service, Rector and Visitors of the University of
Virginia (Dustin A. Cable, creator) 227
7.4 Obesity Around the World, by Jeff Clark 228
7.5 Excerpt from Social Progress Index 2015, by Social Progress
Imperative, 2015 228
7.6 NFL Players: Height & Weight Over Time, by Noah Veltman
(noahveltman.com) 229
7.7 Excerpt from How Americans Die, by Matthew C. Klein and
Bloomberg Visual Data 230
7.8 Model Projections of Maximum Air Temperatures Near the
Ocean and Land Surface on the June Solstice in 2014 and 2099:
NASA Earth Observatory maps, by Joshua Stevens 231
7.9 Excerpt from A Swing of Beauty, by Sohail Al-Jamea, Wilson
Andrews, Bonnie Berkowitz and Todd Lindeman (The Washington
Post) 231
7.10 How Well Do You Know Your Area? by ONS Digital Content
team 232
7.11 Excerpt from Who Old Are You?, by David McCandless and
Tom Evans 233
7.12 512 Paths to the White House, by Mike Bostock and Shan Carter
(The New York Times) 233
7.13 OECD Better Life Index, by Moritz Stefaner, Dominikus Baur,
Raureif GmbH 233
7.14 Nobel Laureates, by Matthew Weber (Reuters Graphics) 234
7.15 Geography of a Recession, by Graphics Department (The New
York Times) 234
7.16 How Big Will the UK Population be in 25 Years Time? by ONS
Digital Content team 234
7.17 Excerpt from Workers Compensation Reforms by State, by
Yue Qiu and Michael Grabell (ProPublica) 235
7.18 Excerpt from ECB Bank Test Results, by Monica Ulmanu,
Laura Noonan and Vincent Flasseur (Reuters Graphics) 236
7.19 History Through the Presidents Words, by Kennedy Elliott, Ted
13
Mellnik and Richard Johnson (The Washington Post) 237
7.20 Excerpt from How Americans Die, by Matthew C. Klein and
Bloomberg Visual Data 237
7.21 Twitter NYC: A Multilingual Social City, by James Cheshire,
Ed Manley, John Barratt, and Oliver OBrien 238
7.22 Killing the Colorado: Explore the Robot River, by Abrahm
Lustgarten, Al Shaw, Jeff Larson, Amanda Zamora and Lauren
Kirchner (ProPublica) and John Grimwade 238
7.23 Losing Ground, by Bob Marshall, The Lens, Brian Jacobs and
Al Shaw (ProPublica) 239
7.24 Excerpt from History Through the Presidents Words, by
Kennedy Elliott, Ted Mellnik and Richard Johnson (The Washington
Post) 240
7.25 Plow, by Derek Watkins 242
7.26 The Horse in Motion, by Eadweard Muybridge. Source: United
States Library of Congresss Prints and Photographs division, digital
ID cph.3a45870. 243
8.1 Titles Taken from Projects Published and Credited Elsewhere in
This Book 248
8.2 Excerpt from The Color of Debt: The Black Neighborhoods
Where Collection Suits Hit Hardest, by Al Shaw, Annie Waldman
and Paul Kiel (ProPublica) 249
8.3 Excerpt from Kindred Britain version 1.0 2013 Nicholas
Jenkins designed by Scott Murray, powered by SUL-CIDR 249
8.4 Excerpt from The Color of Debt: The Black Neighborhoods
Where Collection Suits Hit Hardest, by Al Shaw, Annie Waldman
and Paul Kiel (ProPublica) 250
8.5 Excerpt from Bloomberg Billionaires, by Bloomberg Visual
Data (Design and development), Lina Chen and Anita Rundles
(Illustration) 251
8.6 Excerpt from Gender Pay Gap US?, by David McCandless,
Miriam Quick (Research) and Philippa Thomas (Design) 251
8.7 Excerpt from Holdouts Find Cheapest Super Bowl Tickets Late
in the Game, by Alex Tribou, David Ingold and Jeremy Diamond
(Bloomberg Visual Data) 252
8.8 Excerpt from The Life Cycle of Ideas, by Accurat 252
8.9 Mizzous Racial Gap Is Typical On College Campuses, by
FiveThirtyEight 253
8.10 Excerpt from The Infographic History of the World, Harper
Collins (2013); by Valentina DEfilippo (co-author and designer);
14
James Ball (co-author and writer); Data source: The Polynational War
Memorial, 2012 254
8.11 Twitter NYC: A Multilingual Social City, by James Cheshire,
Ed Manley, John Barratt, and Oliver OBrien 255
8.12 Excerpt from US Gun Deaths, by Periscopic 255
8.13 Image taken from Wealth Inequality in America, by YouTube
user Politizane (www.youtube.com/watch?v=QPKKQnijnsM) 256
9.1 HSL Colour Cylinder: Image from Wikimedia Commons
published under the Creative Commons Attribution-Share Alike 3.0
Unported license 265
9.2 Colour Hue Spectrum 265
9.3 Colour Saturation Spectrum 266
9.4 Colour Lightness Spectrum 266
9.5 Excerpt from Executive Pay by the Numbers, by Karl Russell
(The New York Times) 267
9.6 How Nations Fare in PhDs by Sex Interactive, by Periscopic;
Research by Amanda Hobbs; Published in Scientific American 268
9.7 How Long Will We Live And How Well? by Bonnie
Berkowitz, Emily Chow and Todd Lindeman (The Washington Post)
268
9.8 Charting the Beatles: Song Structure, by Michael Deal 269
9.9 Photograph of MyCuppa mug, by Suck UK
(www.suck.uk.com/products/mycuppamugs/) 269
9.10 Example of a Stacked Bar Chart Based on Ordinal Data 270
9.11 Rim Fire The Extent of Fire in the Sierra Nevada Range and
Yosemite National Park, 2013: NASA Earth Observatory images, by
Robert Simmon 270
9.12 What are the Current Electricity Prices in Switzerland
[Translated], by Interactive things for NZZ (the Neue Zrcher
Zeitung) 271
9.13 Excerpt from Obamas Health Law: Who Was Helped Most,
by Kevin Quealy and Margot Sanger-Katz (The New York Times) 272
9.14 Daily Indego Bike Share Station Usage, by Randy Olson
(@randal_olson)
(http://www.randalolson.com/2015/09/05/visualizing-indego-bike-
share-usage-patterns-in-philadelphia-part-2/) 272
9.15 Battling Infectious Diseases in the 20th Century: The Impact of
Vaccines, by Graphics Department (Wall Street Journal) 273
9.16 Highest Max Temperatures in Australia (1st to 14th January
2013), Produced by the Australian Government Bureau of
15
Meteorology 274
9.17 State of the Polar Bear, by Periscopic 275
9.18 Excerpt from Geography of a Recession by Graphics
Department (The New York Times) 275
9.19 Fewer Women Run Big Companies Than Men Named John, by
Justin Wolfers (The New York Times) 276
9.20 NYPD, Council Spar Over More Officers by Graphics
Department (Wall Street Journal) 277
9.21 Excerpt from a Football Player Dashboard 277
9.22 Elections Performance Index, The Pew Charitable Trusts 2014
278
9.23 Art in the Age of Mechanical Reproduction: Walter Benjamin by
Stefanie Posavec 279
9.24 Casualties, by Stamen, published by CNN 279
9.25 First Fatal Accident in Spain on a High-speed Line [Translated],
by Rodrigo Silva, Antonio Alonso, Mariano Zafra, Yolanda Clemente
and Thomas Ondarra (El Pais) 280
9.26 Lunge Feeding, by Jonathan Corum (The New York Times);
whale illustration by Nicholas D. Pyenson 281
9.27 Examples of Common Background Colour Tones 281
9.28 Excerpt from NYC Street Trees by Species, by Jill Hubley 284
9.29 Demonstrating the Impact of Red-green Colour Blindness
(deuteranopia) 286
9.30 Colour-blind Friendly Alternatives to Green and Red 287
9.31 Excerpt from, Pyschotherapy in The Arctic, by Andy Kirk 289
9.32 Wind Map, by Fernanda Vigas and Martin Wattenberg 289
10.1 City of Anarchy, by Simon Scarr (South China Morning Post)
294
10.2 Wireframe Sketch, by Giorgia Lupi for Nobels no degree by
Accurat 295
10.3 Example of the Small Multiples Technique 296
10.4 The Glass Ceiling Persists Redesign, by Francis Gagnon
(ChezVoila.com) based on original by S. Culp (Reuters Graphics)
297
10.5 Fast-food Purchasers Report More Demands on Their Time, by
Economic Research Service (USDA) 297
10.6 Stalemate, by Graphics Department (Wall Street Journal) 297
10.7 Nobels No Degrees, by Accurat 298
10.8 Kasich Could Be The GOPs Moderate Backstop, by
FiveThirtyEight 298
16
10.9 On Broadway, by Daniel Goddemeyer, Moritz Stefaner,
Dominikus Baur, and Lev Manovich 299
10.10 ER Wait Watcher: Which Emergency Room Will See You the
Fastest? by Lena Groeger, Mike Tigas and Sisi Wei (ProPublica) 300
10.11 Rain Patterns, by Jane Pong (South China Morning Post) 300
10.12 Excerpt from Pyschotherapy in The Arctic, by Andy Kirk 301
10.13 Gender Pay Gap US, by David McCandless, Miriam Quick
(Research) and Philippa Thomas (Design) 301
10.14 The Worst Board Games Ever Invented, by FiveThirtyEight
303
10.15 From Millions, Billions, Trillions: Letters from Zimbabwe,
20052009, a book written and published by Catherine Buckle
(2014), table design by Graham van de Ruit (pg. 193) 303
10.16 List of Chart Structures 304
10.17 Illustrating the Effect of Truncated Bar Axis Scales 305
10.18 Excerpt from Doping under the Microscope, by S. Scarr and
W. Foo (Reuters Graphics) 306
10.19 Record-high 60% of Americans Support Same-sex Marriage,
by Gallup 306
10.20 Images from Wikimedia Commons, published under the
Creative Commons Attribution-Share Alike 3.0 Unported license 308
11.17 The Pursuit of Faster by Andy Kirk and Andrew Witherley
318324
17
Acknowledgements
This book has been made possible thanks to the unwavering support of my
incredible wife, Ellie, and the endless encouragement from my Mum and
Dad, the rest of my brilliant family and my super group of friends.
From a professional standpoint I also need to acknowledge the
fundamental role played by the hundreds of visualisation practitioners (no
matter under what title you ply your trade) who have created such a wealth
of brilliant work from which I have developed so many of my convictions
and formed the basis of so much of the content in this book. The people
and organisations who have provided me with permission to use their work
are heroes and I hope this book does their rich talent justice.
18
About the Author
Andy Kirk
is a freelance data visualisation specialist based in Yorkshire, UK. He
is a visualisation design consultant, training provider, teacher,
researcher, author, speaker and editor of the award-winning website
visualisingdata.com
After graduating from Lancaster University in 1999 with a BSc
(hons) in Operational Research, Andy held a variety of business
analysis and information management positions at organisations
including West Yorkshire Police and the University of Leeds.
He discovered data visualisation in early 2007 just at the time when
he was shaping up his proposal for a Masters (MA) Research
Programme designed for members of staff at the University of Leeds.
On completing this programme with distinction, Andys passion for
the subject was unleashed. Following his graduation in December
2009, to continue the process of discovering and learning the subject
he launched visualisingdata.com, a blogging platform that would
chart the ongoing development of the data visualisation field. Over
time, as the field has continued to grow, the site too has reflected this,
becoming one of the most popular in the field. It features a wide
range of fresh content profiling the latest projects and contemporary
techniques, discourse about practical and theoretical matters,
commentary about key issues, and collections of valuable references
and resources.
In 2011 Andy became a freelance professional focusing on data
visualisation consultancy and training workshops. Some of his clients
include CERN, Arsenal FC, PepsiCo, Intel, Hershey, the WHO and
McKinsey. At the time of writing he has delivered over 160 public
and private training events across the UK, Europe, North America,
Asia, South Africa and Australia, reaching well over 3000 delegates.
In addition to training workshops Andy also has two academic
teaching positions. He joined the highly respected Maryland Institute
College of Art (MICA) as a visiting lecturer in 2013 and has been
teaching a module on the Information Visualisation Masters
Programme since its inception. In January 2016, he began teaching a
data visualisation module as part of the MSc in Business Analytics at
the Imperial College Business School in London.
19
Between 2014 and 2015 Andy 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, among many things, helped to shape
an understanding of the human factors that affect visualisation
literacy and the effectiveness of design.
20
Introduction
I.1 The Quest Begins
In his book The Seven Basic Plots, author Christopher Booker investigated
the history of telling stories. He examined the structures used in biblical
teachings and historical myths through to contemporary storytelling
devices used in movies and TV. From this study he found seven common
themes that, he argues, can be identifiable in any form of story.
One of these themes was The Quest. Booker describes this as revolving
around a main protagonist who embarks on a journey to acquire a
treasured object or reach an important destination, but faces many
obstacles and temptations along the way. It is a theme that I feel shares
many characteristics with the structure of this book and the nature of data
visualisation.
You are the central protagonist in this story in the role of the data
visualiser. The journey you are embarking on involves a route along a
design workflow where you will be faced with a wide range of different
conceptual, practical and technical challenges. The start of this journey
will be triggered by curiosity, which you will need to define in order to
accomplish your goals. From this origin you will move forward to
initiating and planning your work, defining the dimensions of your
challenge. Next, you will begin the heavy lifting of working with data,
determining what qualities it contains and how you might share these with
others. Only then will you be ready to take on the design stage. Here you
will be faced with the prospect of handling a spectrum of different design
options that will require creative and rational thinking to resolve most
effectively.
The multidisciplinary nature of this field offers a unique opportunity and
challenge. Data visualisation is not an especially difficult capability to
acquire, it is largely a game of decisions. Making better decisions will be
your goal but sometimes clear decisions will feel elusive. There will be
occasions when the best choice is not at all visible and others when there
will be many seemingly equal viable choices. Which one to go with? This
book aims to be your guide, helping you navigate efficiently through these
21
difficult stages of your journey.
You will need to learn to be flexible and adaptable, capable of shifting
your approach to suit the circumstances. This is important because there
are plenty of potential villains lying in wait looking to derail progress.
These are the forces that manifest through the imposition of restrictive
creative constraints and the pressure created by the relentless ticking clock
of timescales. Stakeholders and audiences will present complex human
factors through the diversity of their needs and personal traits. These will
need to be astutely accommodated. Data, the critical raw material of this
process, will dominate your attention. It will frustrate and even disappoint
at times, as promises of its treasures fail to materialise irrespective of the
hard work, love and attention lavished upon it.
Your own characteristics will also contribute to a certain amount of the
villainy. At times, you will find yourself wrestling with internal creative
and analytical voices pulling against each other in opposite directions.
Your excitably formed initial ideas will be embraced but will need taming.
Your inherent tastes, experiences and comforts will divert you away from
the ideal path, so you will need to maintain clarity and focus.
The central conflict you will have to deal with is the notion that there is no
perfect in data visualisation. It is a field with very few always and
nevers. Singular solutions rarely exist. The comfort offered by the rules
that instruct what is right and wrong, good and evil, has its limits. You can
find small but legitimate breaking points with many of them. While you
can rightly aspire to reach as close to perfect as possible, the attitude of
aiming for good enough will often indeed be good enough and
fundamentally necessary.
In accomplishing the quest you will be rewarded with competency in data
visualisation, developing confidence in being able to judge the most
effective analytical and design solutions in the most efficient way. It will
take time and it will need more than just reading this book. It will also
require your ongoing effort to learn, apply, reflect and develop. Each new
data visualisation opportunity poses a new, unique challenge. However, if
you keep persevering with this journey the possibility of a happy ending
will increase all the time.
I.2 Who is this Book Aimed at?
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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 big. It is too big a subject even to attempt to cover it all, in
detail, in one book. There is no single book to rule them all because there
is no one book that can 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 whole books in their own right.
The secondary challenge when writing a book about data visualisation is to
decide how to weave all the content together. Data visualisation is not
rocket science; it is not an especially complicated discipline. Lots of it, as
you will see, is rooted in common sense. It is, however, certainly a
complex subject, a semantic distinction that will be revisited later. There
are lots of things to think about and decide on, as well as many things to
do and make. Creative and analytical sensibilities blend with artistic and
scientific judgments. In one moment you might be checking the statistical
rigour of your calculations, in the next deciding which tone of orange most
elegantly contrasts with an 80% black. The complexity of data
visualisation manifests itself through how these different ingredients, and
many more, interact, influence and intersect to form the whole.
The decisions I have made in formulating this books content have been
shaped by my own process of learning about, writing about and practising
data visualisation for, at the time of writing, nearly a decade. Significantly
from the perspective of my own development I have been fortunate to
have had extensive experience designing and delivering training
workshops and postgraduate teaching. I believe you only truly learn about
your own knowledge of a subject when you have to explain it and teach it
to others.
I have arrived at what I believe to be an effective and proven pedagogy
that successfully translates the complexities of this subject into accessible,
practical and valuable form. I feel well qualified to bridge the gap between
the large population of everyday practitioners, who might identify
themselves as beginners, and the superstar technical, creative and
academic minds that are constantly pushing forward our understanding of
the potential of data visualisation. I am not going to claim to belong to that
latter cohort, but I have certainly been the former a beginner and most
of my working hours are spent helping other beginners start their journey.
I know the things that I would have valued when I was starting out and I
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know how I would have wished them to be articulated and presented for
me to develop my skills most efficiently.
There is a large and growing library of fantastic books offering many
different theoretical and practical viewpoints on the subject of data
visualisation. My aim is to bring value to this existing collection of work
by taking on a particular perspective that is perhaps under-represented in
other texts exploring the notion and practice of a visualisation design
process. As I have alluded to in the opening, the central premise of this
book is that the path to mastering data visualisation is achieved by making
better decisions: effective choices, efficiently made. The books central
goal is to help develop your capability and confidence in facing these
decisions.
Just as a single book cannot cover the whole of this subject, it stands that a
single book cannot aim to address directly the ne
