25 Nov What are the characteristics of anomaly detection?? What are the detection problems and methods? What are the statistical approaches when there is an anomaly found? Compare and contrast pro
Q1. Read Chapter 9 in the textbook: Cluster Analysis
Textbook: Tan, Pang-Ning. Introduction to Data Mining
- What are the characteristics of anomaly detection?
- What are the detection problems and methods?
- What are the statistical approaches when there is an anomaly found?
- Compare and contrast proximity and clustering based approaches.
Follow APA7 guidelines and answer in Q&A format. There should be headings to each of the questions and include an introduction and conclusion. Ensure there are at least two-peer reviewed sources to support your work. The paper should be at least 2-3 pages of content (this does not include the cover page or reference page).
Q2. Read ch. 8 in the textbook: Annotation
Textbook: Kirk, Andy. Data Visualization: A Handbook for Data Driven Design
Select any example of a visualization or infographic. The task is to undertake a deep, detailed ‘forensic’ like assessment of the design choices made across each of the five layers of the chosen visualization’s anatomy. In each case your assessment is only concerned with one design layer at a time. For this task, take a close look at the annotation choices:
- Start by identifying all the annotation features deployed, listing them under the headers of either project or chart annotation.
- How suitable are the choices and deployment of these annotation features? If they are not, what do you think they should have been?
- Go through the set of ‘Influencing factors’ from the latter section of the book’s chapter to help shape your assessment and to possibly inform how you might tackle this design layer differently.
- Also, considering the range of potential annotation features, what would you do differently or additionally?
Be sure to show the visualization first and then thoroughly answer the above questions.
Answer in a Q&A format in 2-3 pages. Ensure that there are at least two-peer reviewed sources utilized this week to support your work.
Data Visualisation A Handbook for Data Driven Design
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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 978-1-4739-1214-4 (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
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
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 1.4–6 Demonstrating the Process of Understanding 24–27 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 Iraq’s 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 Zürcher 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 Mizzou’s 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 Y’all, Youse and You Guys Talk, by Josh Katz (The New York Times) 80 3.6 Spotlight on Profitability, by Krisztina Szücs 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
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 Szücs 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 5.2–4 Why Peyton Manning’s Record Will Be Hard to Beat, by Gregor Aisch and Kevin Quealy (The New York Times) 138–140 C.1 Mockup Designs for ‘Poppy Field’, by Valentina D’Efilippo (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
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 2014–2015, 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),
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, 1790–1890, 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), 1985–2015 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 1986–2008, 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,
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 Tröger, André Pätzold, David Wendler (Berliner Morgenpost) and Moritz Klack (webkid.io) 201 6.49 How Y’all, Youse and You Guys Talk, by Josh Katz (The New York Times) 202 6.50 Here’s 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), 110–141. 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 What’s 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
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 President’s Words, by Kennedy Elliott, Ted
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 O’Brien 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 President’s 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 Congress’s 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 Mizzou’s 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 D’Efilippo (co-author and designer);
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 O’Brien 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 Zürcher Zeitung) 271 9.13 Excerpt from ‘Obama’s 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
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 Viégas 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 GOP’s Moderate Backstop, by FiveThirtyEight 298
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, 2005−2009, 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 11.1–7 The Pursuit of Faster’ by Andy Kirk and Andrew Witherley 318–324
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.
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 Master’s (MA) Research Programme designed for members of staff at the University of Leeds. On completing this programme with distinction, Andy’s 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 Master’s 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.
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.
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
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? 22
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
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