Updated training schedule

Just a quick note to share an update on my upcoming ‘Introduction to Data Visualisation & Infographic Design’ public training workshops. Due to a particularly packed schedule for the rest of 2014 (especially due to private workshops) I’ve only got capacity to fit in 3 additional public events. These will be in San Francisco, Leeds and another event in London later in the year.

Schedule

You will see I have put an early call out for folks in Australia and New Zealand. I visited Sydney, Canberra and Melbourne in November 2013 and will be heading back down under in April 2015. Whilst I have a outstanding demand expressed to visit certain locations from last year I am keen to gather additional suggestions to ensure my schedule is best serving the demands out there. Get in touch!

Finally, in the next few weeks I will be (finally!) relaunching my website and this will include an updated profile of all my training activities and menu of offerings. So that will be nice.

Best of the visualisation web… May 2014

At the end of each month I pull together a collection of links to some of the most relevant, interesting or thought-provoking web content I’ve come across during the previous month. Here’s the latest collection from May 2014.

Visualisations/Infographics

Includes static and interactive visualisation examples, infographics and galleries/collections of relevant imagery.

National Climate Assessment | Some nice graphics across this report: “Explore highlights and the full report of the National Climate Assessment”

Moebio | Santiago creates a whole new way of looking at the world wide web via a trace of site links over time “The First Web, and Beyond”

ONS | Slopegraph showing ranking relationship between countries and their number of visits to UK and the spending per day of visitors from those countries in 2013

New Yorker | Interactive and video exploring the most radioactive place in New York City

Guardian | ‘Lesbian, gay, bisexual and transgender rights around the world’

Vizual-Statistix | ‘A career shooting percentages of every NBA player’

WSJ | Long form piece from the WSJ exploring the phenomena of Alibaba, China’s biggest online commerce company

mdaniels | Examining the vocabulary of hip hop artists based on the number of unique words used within artist’s first 35000 lyrics

Smartmine | Who wouldn’t want to watch tracking data for whales? This tool lets you “follow sperm, beaked, false killer, and pigmy killer whales as they migrate around the Hawaiian Islands” (love the Ocean view especially)

Australian Financial Review | My friends at Small Multiples did this really nice interactive to explore language used by the current and previous Treasurers to explain their budgets

Washington Post | ‘The most lethal actors of all time, by number of career kills on screen’

CartoDB | Animated map showing the geotagged tweets mentioning Arsenal or Hull City during the FA Cup final in May

New York Times | ‘Rating a Health Law’s Success’ – with a sequence of slopegraphs. Yes!

BigtimeBCN | More ‘Age of a city’ goodness, this time for Barcelona

Forum | Infographic showing how Africa tweets

CS 171 | Always look forward to the publication of the Harvard ‘CS 171 – Visualization’ course end of year best student visualisation projects gallery

LA Times | Take a video-flyover across the LA area showing the updated location of the earthquake fault zones routes.

Urban Demographics | 3D projections that show ‘Urban Density Patterns in 9 Global Cities’

Lincolnmullen | Animated map that shows the spread of US slavery between 1790 and 1860

The Upshot | ‘Which Team to you Cheer For?’ a map of NBA fans across the US

The Upshot | Music to my ears, or eyes, as this graphic comprehensively shows how Liverpool were robbed of the Premier League title – ‘The Premier League Standings if Only Goals by English Players Counted’

Andreapinchi | ‘No Country for Young Men’ – analysis of the age of Italian Parliament members

Dark Horse Analytics | ‘Breathing City’ Joey takes a look at Manhattan’s population who are at home or at work, by hour

Guardian | Profiling the animated mapping project by CASA to look at the evolution of London’s 2000 year history

Seventeenpeople | ‘A modest tribute to – and deconstruction of – my favourite hour of television’ – an ode to Aaron Sorkin

Retale | ’13 Years of Apple Stores in 60 Seconds’

Vimeo | Discovered via Jer Thorp’s datastories episode. This is a video of actors reading the most common first names for artists in MOMA’s accessioned collection, in order, by gender (hint: listen for the occasional female speakers)

Prooffreader | ‘Graphing the distribution of English letters towards the beginning, middle or end of words’

Slavery Footprint | ‘How many slaves work for you?’

FastCo Design | ‘Falling In Love, Visualize’ – work by Lam Thuy Vo using text message data to visualize the sparks of love

Washington Post | ‘Weapons and mass shootings’ – chart showing every gun that was used in a mass shooting and how those guns were obtained.

SCMP | An incredible attempt to portray the hugely complex issue of the conflicts in the waters between China and Vietnam.

New York Times | ‘A New Story Told at Ground Zero: The National September 11 Memorial Museum’

The Upshot | ‘Is It Better to Rent or Buy?’

The Atlantic | ‘The World of Starbucks, Mapped’ [+ subtitle of the month: "No matter where you are on the planet, you're never more than 5,000 miles from a Starbucks."]

Washington Post | Connected Scatterplot showing how ‘Inequality and political polarization have been rising in tandem for three decades’

Flowing Data | Analysis of ‘Where Bars Outnumber Grocery Stores’

Washington Post | A scatter-plot showing the best and worst ceremonial first pitches (showing that 50 Cent’s was possibly the worst)

Articles

The emphasis on these items is that they are less about visualisation images and are more article-focused, so includes discussion, discourse, interviews and videos

Int3rhacktives | An interview with data visualiser Ri Liu from Pitch Interactive

Periscopic | Dino discusses the issue that data – and what data is or isn’t – is a point of view.

GiorgiaLupi | ‘Bellas Razones [Beautiful Reasons]‘ A super Italian/English article by Giorgia sharing the approach Accurat take to balance their aesthetic and practical choices across their portfolio of work (based on her Visualized talk of 2014)

YouTube | ‘CHI Belgium Hangouts with interesting people: Moritz Stefaner’

New York Times | ‘The United States of Metrics’

Junk Charts | Nice piece by Kaiser discussing ‘how effective visualisation brings data alive’

JSK | Shazna Nessa discusses ‘how journalists can turn raw information into data visualizations that are both appealing and understandable to real people’

Ghostweather | A great article by Lynn, offering a second-part to her discussion about Implied Stories.

Scientific American | When an article begins with ‘Andy Kirk…’ and has ‘clever’ in the same sentence then there’s a good chance I’m going to be loving it! (It is a really nice piece by Jen looking ‘Under the Hood of Online Data Visualization’)

Nieman Journalism Lab | ‘The leaked New York Times innovation report is one of the key documents of this media age’

Ampp3d | ’11 mistakes that will drive data nerds crazy’

Source | Lovely article by one of my favourite people in viz – Sarah Slobin – as she ‘discovers that all the facts and numbers didn’t add up to the humans in her story’

BBC Internet Blog | ‘To mark 20 years of the BBC being online, we wanted to see if there was a way of representing the growth and changing shape of the site over the last 20 years.’

OpenVisConf | A beautiful way to break down and share the videos from the OpenVisConf 2014 (My ‘The Design of Nothing’ is in there…)

Simon Rogers | ‘Data journalism needs to go mobile’

Tow Center | Report: ‘The Art and Science of Data-Driven Journalism’

Michael Babwahsingh | Michael discusses how rarely ‘information design acknowledges the missing, the unknown’

The Functional Art | Yes >> ‘Infographics that just work better on paper’

Aeon | Quite a long article looking at the relationship between truth and beauty. Some Operators in particular may find this interesting.

SND | ‘Infographic case study: Boston Globe’s energetic interactive and print graphics’

Policy Viz | Jon shares his thoughts on the ‘So What?’ test as introduced by Alberto in the Datastories episode 35

Gravy Anecdote | Continuing the recent discussions about storytelling, Andy Cotgreave challenges some of the views (of Moritz in particular) from the same episode 35

Juice Analytics | Great message: ’10 Ways to Reduce to Improve Your Data Visualizations’

Utah.edu | Paper: ‘Reflections on How Designers Design With Data’

Contently | Interview with Bloomberg Visual’s leader, Lisa Strausfeld

Source | ‘Distrust your data: Jacob Harris on Six Ways to Make Mistakes with Data’

Learning & Development

These links cover presentations, tutorials, learning opportunities, case-studies, how-tos etc.

Perceptual Edge | Nice summary from Stephen about some of the methods of displaying change between two points in time – such a frequent task

Sankeymatic | Tool: SankeyMATIC – a Sankey diagram builder built in d3.js

tylervigen | Loads and loads and loads of brilliant charts that show some spurious correlations eg. Number people who drowned in a swimming pool correlates with the number of films Nicolas Cage has been in. Obviously.

Sorting | ‘An attempt to visualise and help to understand how some of the most famous sorting algorithms work.’

Medium | A write up of ‘Experiences & insights from a course by Jonathan Corum, Bret Victor, Mike Bostock & Edward Tufte’

GiorigaLupi | Another great contribution for Giorgia this month, this time a nice project narrative from Accurat’s work on ‘The Life Cycle of Ideas’ for Popular Science

Well Formed Data | Moritz outlines some of the updated features of the Better Life Index 2014

Source | Project narrative by Alastair Dant and Hannah Fairfield as they discuss the work behind the scenes of their ‘Few Helmets, More Deaths’ project

Mic | ’9 Things You’d Believe About World Geography if You Only Listened to Fox News’

Evergreen Data | Great work by Stephanie and Ann Emery to create a data visualisation creation checklist

Storytelling With Data | Really useful article from Cole, ‘the story you want to tell…and the one your data shows’

Stamen | ‘Stamen’s Checklist for Maps’ – Here’s another super useful checklist, but this more narrowly focused on maps

Collossal | ‘The Cyanometer, a 225-Year-Old Tool for Measuring the Blueness of the Sky’

Caroline Beavon | A long article by Caroline about infographics, making them accessible and many other design considerations

Subject News

Includes announcements within the field, brand new sites, new (to me) sites, new books and generally interesting developments.

Global Editors Network | Announcing the nine winners of the Data Journalism Awards 2014

Journalism | ‘BBC to launch daily infographics shared on social media’

Sundries

Any other items that may or may not be directly linked to data visualisation but might have a data/technology focus or just seem worthy of sharing

Guardian | ‘Second world war in Google Street View’ – overlaying photos from the second world war

Twitter | Useful little explainer for the difference between Type I and Type II errors.

Collossal | ’271 Years Before Pantone, an Artist Mixed and Described Every Color Imaginable in an 800-Page Book’

The Creators Project | ‘This Is What The Internet Sounds Like’ – audio of different big data centres

FastCo Create | R.I.P HR Giger

FastCo Design | R.I.P. Massimo Vignelli

Wired | ’400 Years of Beautiful, Historical, and Powerful Globes’

NPR | ‘The Best Commencement Speeches, Ever’ – Over 300 searchable addresses going back to 1774

Slash Film | ‘Every Word In Star Wars Sorted Alphabetically’

Guardian | ‘World Cup kits through the ages – interactive guide’

xkcd | “Someone is wrong on the internet.”

Business Insider | ‘Inside The 45-Day Planning Process That Goes Into Creating A Single Corporate Tweet’

Twitter | “We are becoming rational, analytical, and data-driven in a far wider range of activity than ever before”

Buzzfeed | ‘The 21 Worst Police Sketches Of All Time’

LinkedIn | ‘Error messages are evil’

Twitter | ‘Save Paper – Save The Planet ‘

New York Times | ‘What are you drinking?’ – Interactive and customised cocktail builder

8 Articles Discussing Visual and Visualisation Literacy

For cross-posting purposes: Over on the Seeing Data research project blog, I have posted a collection of 8 articles concerning visual and visualisation literacy.

Screen Shot 2014-07-11 at 08.29.24

Why visualisation is a pursuit of optimisation

I’ve had this short post sat in my draft folder for weeks now, awaiting the right context before publishing. I’m finally motivated to post it having seen a few discussions on Twitter last week whilst on holiday (when the hotel pool has wifi, what can you do but look now and again…).

The Twitter discussions involved comments along the lines of “good, but would have been nice if…”. This is something I’ve uttered and written hundreds of times before: it is an inevitable reaction of somebody assessing what is in front of them. (Whisper it, sometimes it will also be a comment shared with the wider world to help others understand just how super astute you are!)

I didn’t bookmark the conversations nor is it about pinpointing individuals, indeed I can’t even remember who was involved. Furthermore, this isn’t another criticism-soapbox piece but a simple reminder that data visualisation – and frankly any creative endeavour – is a pursuit of optimisation.

Firstly, it is important to remember that the “it would have been nice if…” observation (usually in relation to absence of a certain design feature) is more than likely a view also shared by the creator. Just because a piece of work doesn’t include something that would have added value doesn’t necessarily mean that it wasn’t both considered and desired by the designer him/herself.

This short exchange between Elijah Meeks and Hannah Fairfield in relation to a New York Times graphic about the Affordable Care Act demonstrates the reality of the circumstances in which projects are created. I’m not picking on Elijah’s query – the hover/click feature was something I remember also instinctively wanting – because it was an entirely valid point, rather I’m struck by Hannah’s quick reply ‘ran outta time for tooltips’.

Screen Shot 2014-07-01 at 10.56.18

Secondly – and mainly – we rarely, if ever, have perfect conditions for creating visualisation work. It is a game of compromise shaped by factors like resource limitations, time constraints, client interference, format restrictions, market pressures etc. It is sometimes about the skill of judging when ‘good enough’ has been achieved. Indeed, on some occasions it is not even about settling for ‘second best’ but realising there is a viable path represented by a least worst solution.

So, don’t stop critiquing work and querying whether something had been considered. Don’t stop commenting on what you think would be good to make something even better. But do remember that there is likely a good reason why certain things couldn’t be achieved in the context of its creation.

Seeing Data: Researching visualisation literacy

I want to share some information about a really interesting research project I’m fortunate to be working on with a small research team from the Institute of Communication Studies at the University of Leeds and The Migration Observatory. The study is titled ‘Seeing Data’ and is funded by the Arts & Humanities Research Council (AHRC). Having commenced in January of this year the project runs through to March 2015.

I’ve briefly mentioned it over the past few weeks but with the project’s website seeingdata.org and blog having been launched in the past couple of days it is a good time to profile it on here because the focus of the study should be of interest to anyone visiting this site.

seeing-data-logo

So much of the discussion about data visualisation is dominated by new projects, new techniques and tools – and understandably so, in many ways we are still in the golden period of experimentation and discovery.

The aim of ‘Seeing Data’ is to understand how people make sense of data visualisations, specifically ‘big data’ visualisations relating to subjects of great depth and rich breadth. Through learning about the ways in which people engage with data visualisations we intend to provide some key resources for the general public, to help them develop the skills they need to interact with visualisations, and also for visualisation designers/producers, to help them understand what matters to the people who view and engage with their visualisations.

One of the key strands of our research activity will be the running of focus groups where we will be conducting assessments about people’s experiences with an array of different visualisation work: different in format, function, tone and subject matter. We are thrilled to be collaborating with our partner studio – Clever Franke – who are helping us to create new visualisation assets for use in this process and beyond.

It is not a long-running, big-team, multi-million pound programme of work but we feel it will be an important stepping stone to learning more about this fascinating subject area. You can find more details about the project via our new website, which includes more information about the aims, intended outputs and how you can get involved in our research. You can follow updates about the project via Twitter (@seeing_data), Facebook and our blog where we aim to publish weekly articles about the study and the subject of visualisation literacy.

If you have any questions or contributions to make to the discussion about visualisation literacy, feel free to get in touch!

Data Stories podcast: Episode 37, teaching visualisation

As ever it was a privilege to be invited to take part in the latest episode 37 of the Data Stories podcast. I joined Enrico and Moritz alongside Scott Murray to discuss the challenges of learning and teaching data visualisation.

Datastories

Many thanks again to Enrico and Moritz for inviting me on the show for a fifth time!

Tasty visualisations from the Barcelona Data Cuisine

Data Cuisine is an experimental workshop investigating the creative possibilities at the intersection between food and data: “exploring food as a medium for data expression”. Between 10th and 13th of June, Moritz Stefaner, a man who needs no introduction, along with Dr Susanne Jaschko and chef Sebastian Velilla ran the second edition of the workshop in Barcelona (the first was in Helsinki in 2012) part of the Big Bang Data exhibition at CCCB, and in coordination with Sónar.

DataCuisine

The focus of the experiment is to research creative ways to represent local open data in through the inherent qualities of food like color, form, texture, smell, taste, nutrition, origin etc. It is a truly multi-sensory approach to encoding data, something that I’ve highlighted previously as been a really interesting branch of the visualisation field.

The workshop is a collaborative research experience, blurring the boundaries between teachers and participants, data and food. At its end, an local data menu is created and publicly tasted.

Noodles

Salt

InOut

Moritz and Susanne have just finished writing up details and publishing photos of the dishes made during this Barcelona workshop. Probably a good idea to not visit the site with an empty stomach.

Visits: A visualisation tool for location histories and photos

Visits is a new visualisation tool by Alice Thudt, Sheelagh Carpendale and Dominikus Baur that lets you browse your location histories and explore your trips and travels. The tool is based on a research project from the University of Calgary. You can find the corresponding publication here: A. Thudt, D. Baur, S. Carpendale – Visits: A Spatiotemporal Visualization of Location Histories, EuroVis 2013.

Visits

Based on an innovative interactive map-timeline the visualisation elegantly comprises a main map element that shows the bigger-picture view of the places you have visited with a series of sequenced circular map snippets that encode when and how long you have stayed in each location. You also then have the option to upload photos from Flickr to supplement the map-timeline with a visual slideshow story of your journey that can be shared with friends and family – and even complete strangers, should you wish.

You can learn more about the project here and, of course, the authors are keen to invite anyone to create their own ‘visit’ story.

Guest post: Using Mode to re-engineer data visualisations

Occasionally I invite folks to contribute guest posts to profile their work, ideas or knowledge. This guest post comes from Benn Stancil from a startup called Mode who have created a really interesting tool that allows you to reverse engineer analysis/visualisations in order to potentially take them in new directions. The product was opened to the public yesterday, so you can check it out and a few examples of the visualisations that people have built with it.

 


 

Can we learn from and build on each other’s visualizations?

Like so many others, I’ve long been fascinated by learning from data–and as a result, been an avid consumer of data visualizations. The explosion of data in recent years has fueled a similar explosion of beautiful and insightful visualizations, created by everyone from industry leaders like the New York Times and Guardian to undiscovered brilliance hidden in obscure corners of the internet.

Even the best visualizations, however, rarely answer all of a viewer’s questions. We often want to understand how the data was collected, how it would look if considered from a different angle, what story it would tell if combined with other data, or how the visualization was built. In other words, great visualizations not only answer questions, but inspire more.

Unfortunately, it’s often difficult to document and share enough information to answer these follow-up questions. Creators carry the burden of sharing their data sources, their analysis that aggregated and combined data, their visualization code, and many other details. And piecing this information together after the fact is equally burdensome for consumers. The bit of knowledge someone new could add by remixing the analysis–or the bit they could learn by better understanding the original–often hits a dead-end, no matter how inspiring the visualization.

 
Introducing Mode

In part because of my own personal frustration, I recently cofounded a company, called Mode, aimed at providing solutions to these challenges. Mode’s mission is to connect data and the people who analyze and visualize it. We’ve built a web-based tool that executes analysis, displays results, and renders fully custom visualizations all in one place. By saving, versioning, and packaging the entire workflow together, anyone who discovers the analysis can immediately click through the results to see the underlying data, the analysis, and how the visualization was created. Right now, we’re focused on supporting SQL for analysis and web languages (HTML, CSS, and Javascript) for visualizations, though we’re planning to adding R- and Python-based tools soon.

Screenshot

The above is a screenshot of a finished visualization. You can see the query, visualization code, and previous versions by clicking on the Query, Presentation, and Run History tabs above the graphic.

By organizing all of this information together in a simple package, people can immediately understand and add to visualizations without having to rebuild the work themselves. We’ve made this possible in one click–simply click clone on the screen above, and you’ll be working with with same visualization published by the original author, exactly where they left off.

When a piece of work is cloned, the original author not only maintains credit, but also sees who cloned their work and what they’re doing with it. This allows the community to push an analysis forward, without ever losing sight of the creator and without the creator losing sight of how their work is evolving.

Others can then working with the analysis and visualization in their own workspaces. They can even add their own data–Mode allows multiple creators’ data to be combined in a single visualization. Because all of this work happens in the browser, Mode doesn’t require setting up a development environment or finding a place to host the visualization.

Here is a screenshot of the presentation editor, where you can add custom visualization code and preview it.

PresentationEditor

Finally, we want people to be able to easily share their work. All visualizations in Mode can be shared via URL, or can be embedded anywhere on the internet, just like a YouTube video. The embedded visualizations, like the one below, can be fully interactive, and link back to all of the data and work.

 
We Want Your Advice

Our approach to making data visualizations more accessible is largely influenced by our own experiences as data analysts. Surely others, who have had different experiences and objectives, face other challenges or have other ideas for solutions.

We’d love to hear what you think of our direction and how we can tailor it to your needs. What problems have you had when collaborating on data visualizations? What are your biggest struggles, and how would you solve them? If you’d like to check out our approach, Mode is free to use and you can sign up here.

We’re looking forward to see what great work people can build with Mode – and perhaps more importantly, what we can learn from each other. The world is producing fascinating data at an unprecedented pace, on subjects ranging from air quality in Chicago, to taxi traffic in Seattle, to the tattoo trends in the NBA. Great technologies for producing visualizations, like D3, Raphaël, and R, are constantly improving. And we have many giants in the data visualization community to look up to. At Mode, our hope is to help all of us stand on their shoulders.

Beginning the journey towards book number two

A quick announcement to the broader visitorship out there, having briefly tweeted about it last week I am thrilled to have received approval to start work on my second book, which will be published by SAGE (one of the “world’s leading independent academic and professional publisher”, I’ll have you know).

I’m not going to share any details on the title or contents just yet but, as with all my endeavours, it will be aimed at covering in detail the practical craft of data visualisation (it won’t be a glossy coffee-table gallery of different works, for example) with a realistic target completion date being the latter part of 2015.

One of the main things that excites me about this project is that the publishers have stated their commitment to explore some great innovations in the relationship between print and digital form: not just in replicating a text digitally but about creating a digital companion to the printed content. I think that is needed in discussing this subject.

The second main thing that excites me is that the book WILL be printed in colour. Obvious, right? Well, not always, sadly…

My experiences from writing the first book were that it is a painful slog, fraught with mental blocks, anxieties about added-value, fears of mis-quoting or mis-referencing ideas, frustrations at trying to secure permissions for image usage etc. I think this quote astutely sums up the prospect:

Orwell

Whilst I was satisfied with the content of my first book (not so much it’s form), I feel I have moved on considerably with so much more to say than I had the chance to share back then. I’m confident that, with the professional support SAGE will unquestionably provide me, this second title will truly be the book I have wanted to produce. I’ll keep you posted on progress…

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