Interviewed for the Mindjet ‘Conspire’ website

I was recently interviewed for Mindjet’s ‘Conspire’ website, a new resource which I’ve admittedly only come across over the past couple of months but seems to have some great content. Anyway, if you are so inclined, just click on the image below to be taken to a page containing my ramblings…

Many thanks to CJ Ciaramella for the conversation!

Best of the visualisation web… May 2012 (part 2)

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. If you follow me on Twitter you will see many of these items shared as soon as I find them.

Here’s part two of the latest collection from May 2012 (see part one):

Perceptual Edge | Data Art vs. Data Visualization: Why Does a Distinction Matter? | Article

Fastco Design | Infographic: Soldier Deaths In Iraq Paint A Tattered American Flag | Infographic

Visual.ly | The Dangers of Scale: Visualizing the Hills of Bay to Breakers | Article

New York Times | The Facebook Offering: How It Compares | Interactive Visualisation

Chartsnthings | Design narrative about the above Facebook visualisation | Design Process

EVO Energy | ‘The Interactive UK Energy Consumption Guide’ (should dislike it but kind of don’t…) | Interactive Infographic

Open Knowledge Foundation Blog | Kick-starting the School of Data! | Article

Forbes | Linked Micromaps for Geographically Referenced Data | Critique/Visualisation Method

Stories Through Data | Updated: visualising Data at the House of Commons | Article/Static Visualisations

Telegraph | Jonathan Ive interview: Apple’s design genius is British to the core | Interview

Guardian Data Store | Climb every mountain: visualising the world’s 50 most prominent peaks | Interactive Visualisation

Big Map Blog | Newly discovered site with some great vintage and innovative mapping content | Site

Adam Crymble | “Shock and Awe” Graphs in Digital Humanities | Article

Code For America | Does the digital divide have a silver lining? | Article

Eager Eyes | Great question from Robert – ‘How Much Data Do You Really Need?’ | Article

Flowing Data | Which nations consume the most water? | Infographic

Wired | Introducing FatFonts – a dedicated typeface for infographics | Typography

BBC News Magazine | Who works the longest hours? | Interactive Visualisation

Flowing Data | Even simple charts can tell a story | Article

Mindjet | Why We Need Creative People to Help Understand Data | Article

HCIL | ‘Motif Simplification: Improving Network Visualization Readability with Fan and Parallel Glyphs’ | Paper

Interactives | Interactive weather map… on TV | Video

Data Remixed | Part one of a three part series… ‘Data Visualization: Clarity or Aesthetics?’ | Article Series

Data Remixed | Part two… ‘Clarity or Aesthetics? Part 2 – A Tale of Four Quadrants’ | Article Series

Data Remixed | Part three… ‘Clarity or Aesthetics? Part 3 – Tips for Achieving Both’ | Article Series

Junk Charts | Analysing a ‘nice use of histograms’ | Critique

Data Driven Journalism | ‘And the winners of the Data Journalism Awards are…’ | Award Announcement

Data Projet | This Animated Bubble Chart shows the 270 most expensive artworks sold in auction since 2008 until end 2011 | Interactive Visualisation

Data Presentation | “I was watching CNN this morning before work, enjoying my breakfast, when all of a sudden they put up a graph of tornado deaths by year” | Bad Visualisation

Places & Spaces | A collection of 134 maps | Map Collection

The Why Axis | The Reuters Macroscope Visualization You Need a Microscope to Read | Critique

Screen Jabber | Interview with Ridley Scott discusses storyboarding | Video/Interview

Amazon | Revised edition of ‘Information Visualization, Third Edition: Perception for Design (Interactive Technologies)’ | New Book

Sculpteo | Featured Sculpteo Stores #1: Nostromo and the DataSculptures | 3D Printing

Green Plum | Videos from the Data Science Summit 2012 | Video Collection


Presenting the top five most popular posts on Visualising Data during May:

The Data Journalism Handbook is now live – April 29th, 2012

Quadrigram: New visual programming environment launches – May 15th, 2012

Best of the visualisation web… April 2012 (part 1) – May 14th, 2012

Best of the visualisation web… April 2012 (part 2) – May 14th, 2012

The fine line between plagiarism and inspiration – May 22nd, 2012

Best of the visualisation web… May 2012 (part 1)

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. If you follow me on Twitter you will see many of these items shared as soon as I find them.

Here’s part one of the latest collection from May 2012 (see part two):

New York Times | Interactive piece depicting ‘One Year of Clouds Covering the Earth’ | Interactive Visualisation

Guardian | Introducing the work of Bryan Christie: blending information design and fine art | Article

OECD | Second generation of the ‘OECD Better Life Index’ | Interactive Visualisation

Well-Formed Data | Moritz Stefaner analyzes which ingredients were ordered together most often in custom muesli mixtures from mymuesli.com customers | Interactive Visualisation

The Functional Art | Interview with renowned information graphics designer, John Grimwade | Interview

Datavisualization.ch | Design narrative for the recent project ‘Ville Vivante – How We Visualized the Vividness of Geneva’ | Design Process

SND | Motion graphics: New weapons of visual journalism | Article

Eager Eyes | A Glimpse Into the New York Times Graphics Department | Article

The Why Axis | Bryan’s analysis of what he believes is a near perfect demonstration of presenting data to the public | Critique

Brain Pickings | Frank Lloyd Wright’s Lesser-Known Contributions to Graphic Design | Article

Jerome Cukier | Review of SEE#7 Conference | TYPE

Clearly and Simply | How to Embed and Open Tableau Workbooks in PowerPoint | Tutorial

Chartsnthings | Sketches: How Mariano Rivera Compares to Baseball’s Best Closers | Design Process

Infographics News | Five Pinterest boards you may follow if you like infographics | Collection

Datavisualization.ch | A great selection of carefully curated data visualisation tools and resources | Collection

The Why Axis | Guest post from Jerome Cukier: The Role of Data Visualization in the 2012 French Presidential Race | Article

O’Reilly Radar | A brief history of data journalism – Key milestones in data journalism’s development | Article

Vimeo | Mike Dewar (Data Scientist, bit.ly), presents a talk on getting started with data driven design in Javascript to the New York Open Statistical Programming Meetup from January 2012 | Video

Flowing Data | Common statistical fallacies | Article

Under the Raedar | Visualising the population of the UK based on how many people live geographically below key cities | Static Visualisation

TED | TED@SXSW talk from JP Rangaswami: Information is food | Video

On Goals Scored | Analysing how much England (football) can rely on Rio Ferdinand and John Terry | Static Visualisation

Guardian | Gay rights in the US, state by state | Interactive Visualisation

Guardian | Process narrative behind the above visualisation | Design Process

The Why Axis | Critique and mature evaluation of the same visualisation | Critique

New York Times | Matrix of reactions from NYT readers to the Obama ‘same sex marriage’ stand | Interactive Visualisation

Vallandingham.me | Assessing the scope of using D3 without SVG, based on a NYT visualisation example | Tutorial

Storytelling With Data | The importance of clarifying ‘what are we trying to say with what we show?’ | Article

Matthew Epler | “‘Grand Old Party’ is a data visualization project. It is also a set of butt plugs.” | Video

Wired | ‘Map of Life’ will track every animal and plant in the world | Article/Interactive Visualisation

USGS | Visualisation of how much water is on earth | Static Visualisation

KQED | Interactive map to ‘Envision California’s Delta As it Was’ | Interactive Map

Washington Post | Analysis of whether the ‘filibuster’ is unconstitutional | Static Visualisation

Chartsnthings | ‘Shan Carter (and an army of others) share some sketches from the NYT electoral map’ | Design Process

On Goals Scored | Visual illustration of four iconic European Championships goals from down the years | Static Visualisations

Jerome Cukier | The making of ‘cutting Paris in voting districts’ | Design Process

Forbes | Bad Graph Contest: What Software Produces the Worst Graph? | Article

Forbes | Winner of the Bad Graph Contest Announced | Article

Guardian | The Twitter news map of Britain | Interactive Map

Core77 | Visualising Criminal Networks to Help Police Solve Crime | Article


Presenting the top five most popular posts on Visualising Data during May:

The Data Journalism Handbook is now live – April 29th, 2012

Quadrigram: New visual programming environment launches – May 15th, 2012

Best of the visualisation web… April 2012 (part 1) – May 14th, 2012

Best of the visualisation web… April 2012 (part 2) – May 14th, 2012

The fine line between plagiarism and inspiration – May 22nd, 2012

Metaphor too far? The anatomy of a visualisation designer

As I was writing my previous post about my thinking behind ‘The 8 hats of data visualisation design’ I realised that the theme of body parts was emerging strongly.

So here’s an alternative perspective on this matter, throwing away the hats and switching on the Frankenstein lab…

This is the super-hero visualisation designer I want to be.

Cognitive Scientist = the mind, responsible for thinking, understands how the eye and the brain works…

Designer = the eye for design, for visual solutions, for colour

Journalist = the nose for a story, the analytical angle to pursue

Communicator = the mouth and ears, to talk and to listen

Computer Scientist = the hands, the builder

Data Scientist = the back-breaking hard work of data gathering and preparation

Project Manager = the torso, brings the whole thing together

Initiator = the legs, sets things in motion

I’ve taken it too far haven’t I…

Article: The 8 hats of data visualisation design

Last week I posted a slideshare version of my slides from a recent pair of presentation events in Chicago. The title of this talk was “The 8 hats of data visualisation”. In this article I want to follow up these slides with a written accompaniment to contextualise and explain what I was presenting, as slides alone don’t really manage to achieve this effectively.

Background

Ever since I discovered data visualisation I have been intrigued by the many different subject areas and disciplines that contribute to its unique mix of art and science. This convergence of different ingredients introduces a wonderful richness and variety of concerns but can equally present quite a challenge for people looking to master the subject.

As the field continues to increase in popularity and exposure, penetrating more into the mainstream, and as data resources and technological capabilities continue to enhance at incredible rates, the opportunities and challenges similarly increase. For many, the prospect of trying to acquire and effectively demonstrate sufficient knowledge and skill across the board of requirements is something that can be either intimidating or at least exist as a perceptual barrier. There is a sense that to be successful you need to be a Superman or Wonder Woman?!

During my training courses I have met many people who have expressed a similar concern. More specifically, they don’t know where they fit in to the world of data visualisation. They aren’t trained designers, they aren’t skilled technologists, so how can they contribute to the design process?

Typically I find these people to be extremely bright, sharp individuals with a keen sense of the analytical dimensions that might be most interesting to surface in a visualisation. They might also be great organisers, leaders and be able to pull a team of people together to create a solution. The key point here is that everybody can find a role, even if they are not capable in certain areas because collaboration with others who can plug such gaps is so much more feasible these days. There are plenty of other duties required that don’t have such technical capabilities or experiences.

Furthermore, we should assess more closely the role of technology in data visualisation. I’ve somewhat paraphrased or maybe just echoed Aron Pilhofer (of the New York Times), but doing data visualisation well is ‘less a technology problem, more a people problem’. So, if you don’t have the tech skills but have the people skills – there is a role for you. Similarly, if you do have the tech skills, you need to ensure you also have the people skills.

Why the 8 Hats?

Having spent a number of years assessing and learning about effective visualisation design I was interested to take a specific analytical look at the range of different capabilities required to ensure that any project is undertaken in the most rounded sense. These can be roles fulfilled by a number of people or they can be the different, deliberate mindsets of an individual to ensure that the problem is viewed and tackled from all necessary directions and not from a limited perspective. This is where I came up with the 8 hats of data visualisation design.

A couple of things that motivated the concept of the 8 hats.

Firstly, and obviously, was Edward de Bono’s 6 thinking hats, which essentially relates to the different thinking perspectives we should try to occupy when trying to reason and solve with complex problems.

Secondly, and far less obviously, I remebered a cartoon I used to watch as a kid (and probably only UK people will recognise) called Mr Benn.

The basic narrative of the story was that, in each episode, Mr Benn would go into a fancy-dress shop, try on a particular outfit and then would enter through a secret door in the dressing room into a magical world and live out an adventure appropriate to the costume.

So, this idea of taking on different characters or different characteristics resonated with my intentions for these 8 hats. It is not meant to be scientific, it is based on an instinctive sense of what is important. Furthermore, it is not presented in a way which gives any weight or hierarchy, rather a collection of the issues and duties that need covering off.

The 8 Hats

The Initiator is the leader, the person who is seeking a solution to a given problem, curiosity or opportunity. The hat is that of an explorer, they want to explore data and different design avenues to find answers to problems or evidence to their researcher mindset. They may have been commissioned with the project or might have conceived it themselves, fulfilling their nature as a thinker.The initiator will establish the analytical direction of the project, identifying the fundamental purpose and motive, which in itself will dictate the tone and style of the potential solution. Is it about explaining or exploring or expression? Is it something that is motivated by a need to facilitate maximum interpretation accuracy and efficiency or more about creating an emotional engagement with the subject matter?

The initiator will also identify and set out some of the key parameters surrounding the project such as the clarity and definition of the brief, the intended format/platform of the solution, the nature of the audience (size, type) and an initial view on the proposed resolution of the data solution (headlines, full details).

The Data Scientist is characterised as the data miner, wearing the miner’s hat. They are responsible for sourcing, acquiring, handling and preparing the data. This means demonstrating the technical skills to work with data sets large and small and of many different types. Some might come from corporate systems, others from web scrapes or via an API, some of it may also come from tricky pdfs.Once acquired the data scientist is responsible for examining and preparing the data. This means identifing and addressing data quality issues and generally preparing it for its analytical purpose (eg. parsing, merging, freetext > keyword converting). It will also be necessary to consider and source additional sets of data to mashup and enhance or consolidate the potential data stories.

The data scientist will also hold the key statistical knowledge to understand the most appropriate techniques and mathematical methods. They will apply this to undertake the initial descriptive analysis of the data, to commence the familiarisation process of this raw material. They will also begin to undertake exploratory visual analysis to learn about the patterns, relationships and physical properties of the data.

The Journalist is the storyteller, the person who establishes the narrative approach to the visualisation’s problem context. Working with the Data Scientist and the Initiator, they have the nose for the key stories and angles with which to slice the analysis and present the stories.They work on formulating the data questions that help keep the project’s focus on its intended editorial path. Building on the Initiator’s initial steer the Journalist will develop a deeper researcher mindset to really explore the analytical opportunities.

As with any research process, the approach may be inductive or deductive, but either way, the journalist is at the heart of the action, seeking to find the answers to move the project on from the preparatory/groundwork activity and on to its design stage.

As Edward Tufte says, ‘Good content reasoners and presenters are rare, designers are not’. That is the responsibility of the Journalist.

The Computer Scientist is the executor, but not in the sense of destruction, rather this is the person who brings the project alive. With their critical capability they are ultimately the ones who will construct the key solutions at the design stage and also bolster the Data Scientistwith technical know-how to most effectively and efficiently handle the data gathering, manipulation and pre-production visualisation activities.The breadth of software and programming literacy will have great bearing on the potential speed and sophistication of the data visualisation solution. It may be restricted to some basic Excel, Tableau and web publishing skills or may involve strong programming abilities with powerful environments such as Processing and D3.

Alternatively, the final technical solution may not be an innovative interactive online work but instead an infographic or static poster display, in which case technical skills with illustration packages like Adobe Illustrator will be all-important.

The designer is the creative, the one who, in harmony with the Computer Scientist, will deliver the solution. They have the eye for visual detail, a flair for innovation and style and are fully appreciative of the potential possibilities that exist.However, they have the necessary discipline too to follow the message established by the Initiator and taken on by the Journalist. They respect the capabilities of the Computer Scientist in terms of what solutions could be feasible but themselves have the helicopter-like vision to rationalise and reason what things will work and will not work, and why.

Their key responsibility is also to be capable of ensuring the harmony of the solution between its form and its function, ensuring it is aesthetically appealing to draw in the reader whilst fundamentally delivering the intended, communicated message.

Acting almost like a film director, they have many competing decisions to make, particularly around managing the five key layers of any visualisation’s anatomy: data representation, colour and background, layout and arrangement, animation or interaction options and the annotation layer.

The Cognitive Scientist is the thinker in terms of appreciating the science behind the effectiveness of the technical and designed solutions.They have the visual perception understanding to inform how the eye and the brain work most effectively and efficiently. They also have clear know-how about principles or theories like the ‘Gestalt Laws’, are familiar with colour theories, well versed in Human Computer Interaction issues etc.

They also can inform the design process in relation to the complexities of how the mind works in terms of memory, attention, decision-making and behavioural change.

The Communicator is the negotiator. With their hard hat they act as the client-customer-designer gateway informing all parties of the respective needs, feedback loops and progress updates.They need to be able to articulate and explain matters to different types of people, technical and non-technical, and be capable of managing expectations and relationships.

They need to be close to all stages of the process, understanding requirements, appreciating restrictions, recognising possibilities and then ultimately launching, publicising and showcasing the final work.

This role is simply the manager, the person who does much to pick up many of the unpopular duties to bring the whole project together. They manage the process and look after the project’s progress, ensuring it is cohesive, on time and on message.They understand the brief, recognise the parameters of the project as identified by the Initiator but also identify others of their own such as the inherent pressures (time, editorial), the rules surrounding the work (visual identity, layout restrictions), the capabilities of the available technical resources and, critically, the people management side.

Ultimately, this role or mindset is required to ensure things get finished, they need an eye for detail, the commitment and patience to check everything and should also be concerned with integrity matters like visualisation/statistical ethics.

Summary

If we take a look at how the relevance of these mindsets and duties surfaces at different points of a typical visualisation design process, we can see the importance of being able to manage your focus and perspective according to the stage of your progress.

Too often we see examples of work where there has been an immediate rush to produce a pre-conceived design or an excitable technical solution without all the preparatory work undertaken beforehand and the discipline to treat the project with the thoroughness of thought required.

Similarly, we see plenty of works that look like they could have been capable of providing really fascinating insights. They ask the right questions and seemingly tell the right stories but the technical execution, whether through an interactive design or illustration, is ultimately flawed and undermines the whole piece.

You could easily argue about some of the labels and descriptions of how the mindsets and duties have been carved up and allocated but hopefully you will be able to appreciate the many varied responsibilities that anyone delivering a data visualisation solution needs to demonstrate, regardless of whether this is an individual or collaborative design process.

Finally, it will help you recognise where you fit it in to the spectrum of duties and responsibilities, helping you identify your strengths and your weaknesses accordingly. You may then choose to address these weaknesses personally or plug the gaps with support from others.

Interviewed by Ben Jones of DataRemixed.com

Last Thursday I had an enjoyable half hour or so chatting with Ben Jones of DataRemixed.com. Ben recorded the conversation and has now published both the audio and some narrative of this chat on his site.

Thanks again Ben, pleasure speaking with you!

Energy technologies visualisation for the IEA

We’ve had a number of interesting new project releases of late (see this, this and that) and today continues that pattern with another super visualisation development produced for the International Energy Agency (IEA) on energy technologies. This work has been designed through a collaboration between Raureif (who recently worked with Moritz Stefaner on the OECD Better Life Index) and Christian Behrens.

This three parted interactive visualization is about projections for emission reductions, energy flows and transport indicators up to 2050 and it relies on the data and scenarios behind “Energy Technology Perspectives 2012” (ETP2012), IEA’s flagship publication on energy technologies.

The centrepiece visualisation is that of the energy flows, as shown in the two images above, presented as interactive Sankey-style flow diagrams. These illustrate how the overall energy system and three of its sectors (transport, industry and buildings) will have to evolve from now to 2050 according to the scenarios outlined in the ETP 2012 publication in order to reduce emissions and limit average global temperature increase to 2°C. You can click on each part of the Sankey to see the individual ‘data pathways’ and also choose an autoplay function to animate the flow across 5-year periods towards 2050.

For the emission reductions and the transport indicators (shown above and below respectively) the user is able to explore different scenarios and regions to learn more about the data and find the stories that resonate with you.

Further features include an option to download the data and also take snapshot graphic images of your scenarios. You can explore the energy technologies visualisation here.

Talk slides: The 8 hats of data visualisation

Below you will find an embedded slideshare version of the slides used in last week’s pair of talks at Orbitz HQ and the inaugural Chicago Data Viz meetup.

As I’ve said a few times before, I’m a reluctant sharer of slides, not because I’m protective of my material, but because they serve as purely visual prompts for the talk so when read out of context they are hard to fully understand and appreciate some of the details. For that reason I’m shortly going to follow up with an article specifically on the subject of the ’8 hats’, a subject I think is important for any visualisation or infographic designer.

The 8 Hats of Data Visualisation

View more presentations from Andy Kirk

Visualisation in the mainstream: Jimmy Carr tax infographic

One of the matters that I cover at the start of my data visualisation training courses is a brief reflection on visualisation’s popularity in a mainstream sense and how it has now penetrated (and continues) parts of culture and society that it would never really have managed to do even 5 years ago.

I’ve just been reading my Twitter timeline and noticed a retweeted post from a writer, columnist etc. called Emma Kennedy.

This tweet linked to an infographic (shown below) which tried to contextualise the recent troubles being experienced by UK comedian Jimmy Carr.

Now, I’m unsure whether Emma Kennedy actually designed this piece herself but, regardless, the original tweet has been immediately retweeted by many people including celebrities and comedians who have hundreds of thousands of followers.

It just shows you how deeply visualisation and infographics are embedded into the way we portray and digest information these days and how quickly these things can reach broad audiences. This graphic neatly captures much of the contextualising reaction that many have been tweeting about in their considered reaction to this story.

Click on the graphic above to see the full resolution version.

Stamen’s travel planner includes weather forecast

The smart folks over at Stamen Design have come up with some more of their mapping goodness with a great tool that I’m pretty sure everybody will appreciate: a travel planner that includes a layer of weather forecast data for your journey letting you know what it will be like along the route based on when you’re likely to get there.

This new project, created for the Weather Channel, not only forecasts the weather along the route of your planned journey but also allows you to drag your route around to avoid certain weather systems. In an extra layer of data, they also include a feed from the Yelp API to give you extra information about what to see along your way.

You can read more about the project in their launch post. Intriguingly, perhaps, the last part refers back to some work they did on a visualisation of how long it takes to get anywhere in London. Here they discuss some interesting potential future ideas…

I start thinking of weather maps that flow and ebb across the country, where different sliders open and ebb various kinds of other axes: time for sure, but maybe population density, maybe altitude, maybe temperature, maybe how many farms there are, maybe distance from a weather station or a McDonald’s—all the different kinds of things that affect people’s sense of place and space and time, organized by what’s above our heads.