Talk slides from Bright Talk webinar

Earlier today I had the pleasure of doing a live webinar for Bright Talk. The talk was titled ‘Separating Myth from Truth in Data Visualisation’ during which I dispelled and acknowledged some of the ‘always and nevers, mostlys and rarelys’ that exist in data visualisation design.

The slides are now available, published on SlideShare. (Due to the amount of detailed images included in this deck, as ever, some have been compromised in their appearance). For those who registered for the webinar you will be receiving a link from Tableau to a recording of the session.

(If you prefer to watch the slides being presented with my audio from today’s session, you can sign up and get free access here).

Talk slides from second Tableau 2016 webinar

Earlier today I had the pleasure of being invited back by Tableau to deliver a second webinar of this year. The talk was titled ‘Bringing Method to the Madness’ during which I discussed the aims of my new book and profiled the design process behind my recent visualisation project called Filmographics.

The slides are now available, published on SlideShare. (Due to the amount of detailed images included in this deck it looks like some have been unfortunately compromised in definition terms). For those who registered for the webinar will be receiving a link from Tableau to a recording of the session.

Andy Kirk's Webinar for Tableau (July 2016) from Andy Kirk

Six questions with… Santiago Ortiz

In order to sprinkle some star dust into the contents of my book I’ve been doing a few interviews with various professionals from data visualisation and related fields. These people span the spectrum of industries, backgrounds, roles and perspectives. I gave each interviewee a selection of questions from which to choose six to respond. This latest interview is with Santiago Ortiz, Head at Moebio Labs. Thank you, Santiago!


Q1 | What was your entry point into the field: From what education/career background did you transition into the world of data visualisation/infographics?

A1 | As a kid (at least since I was 5) I had a deep interest in maps. I tried to create my own maps of imagined places. My parents report I said “I want to be a cartographer” when I was 5. Also as a kid, but later, I started coding. As many, I developed my own simple video games, but also played just with graphs driven by simple algorithms. Later fractals and cellular automata blew my mind, and then genetic algorithms. I studied mathematics while continue using code as creative tool. My math thesis was a model for evolution and genetic algorithms. I have to say that at that time I kind of hated applied maths, so statistics didn’t interested me on the least. That came later.

In 1999 I co-founded a web design company in Colombia, called Moebio. Although websites tended to be very conventional, I continued being interesting in the creative capabilities of the digital medium, specially the hyper connected medium of internet. Soon, I started using data to drive visual outcomes. In 2003, while living in Spain, working in collaboration with an awesome Protein Laboratory in Madrid, ran by Alfonso Valencia that was doing pioneer research on data crawling and data crowdsourcing for molecular biology data, we created Gnom, the first serious (although pretty much experimental) data visualization project I was involved.

In 2005 I co-founded Bestiario, a company devoted to interactive data visualization (I left the company in 2012). Now I lead Moebio Labs, a small data consultancy team. We combine interactive data visualization with data science.

Q2 | What is the single best piece of advice you have been given, have heard or have formed yourself that you would be keen to pass on to someone getting started in a data visualisation/infographics-related discipline?

A2 | You should pursuit a career on data visualization only if you’re more interested in what you visualize than in data visualization itself. As a corollary, for each datavis book you read, you should read other 9 about a variety of other subjects such as psychology, economics, mathematics, genetics, sociology, statistics… (my personal rate is actually 1/30).

Q3 | When you begin working on a visualisation task/project, typically, what is the first thing you do?

A3 | I do two things in parallel: I explore the data focusing on structure, with a domain-agnostic approach; and I also talk with the client a lot: I make lots of questions, I try to understand client’s landscape of pains and opportunities, its expectations towards the data and project outcomes, the client’s general major problems and challenges.

Q4 | At the start of a design process we are often consumed by different ideas and mental concepts about what a project ‘could’ look like. How do you maintain the discipline to recognise when a concept is not fit for purpose (for the data, analysis or subject you are ultimately pursuing)? How should one balance experimentation with the pragmatism of what is a data driven and often statistically influenced process?

A4 | “At the start of a design process we are often consumed by different ideas and mental concepts about what a project ‘could’ look like”… Actually I don’t let that happen. As mentioned before I focus on structural exploration in one side and on the reality and the landscape of opportunities in the other. Then we start playing (it’s usually me, a data scientist and a visualization designer+developer), building fast prototypes (we create our own tools for that). By combining and exploring options, forking, pivoting, trying… we end up with good candidates, that we execute and wrap into something we can send to the client. That’s the result of the first iteration. Then it comes lot of conversations with the client and then the tests… tests by us and the client. We talk again, we take into consideration client’s feedback guided by questions. We find what is useful in the first iteration, what is really starting to give some insights to the client, what helps it to make faster and better decisions, etc… Next iteration will then expand what works, remove what doesn’t, and add more experimental approaches to be tested. Typically in the fourth iteration or so the client has a set of tools, some training and gained knowledge that allows it to take real advantage of the data. So, again, we try not to impose any early ideas of what the result will look like, because that will emerge from the process. In a nutshell we first activate data curiosity, client curiosity, and then visual imagination in parallel with experimentation.

Q5 | Beyond the world of infographics/visualisation what other disciplines/subject areas/hobbies/interests do you feel introduce valuable new ingredients and inspire ongoing refinement of your techniques?

A5 | These are some other fields of knowledge that we consider very important, because they provide ideas and tools for the stuff we build, or because they are typical sources of information we might end up analyzing and visualizing… in most of the cases it’s both! We also have to deal often with experts on those fields.

Of course neither of us has deep knowledge on all those fields. We are dilettantes, but we all spend a big deal of time studying and reading.

Q6 | In your experience, what has proven to be the most valuable approach to evaluating your work (post completion) or what methods have you seen others taken that you felt were especially smart? There will always be a balance between effort and reward but very keen to learn of any specific effective tactics.

A6 | Evaluation of work is key for us, as previously explained. Evaluation means improving, it’s a constructive concept not a passive one. Evaluation is also, in our case, a collaborative process, something with do along with the client. We use concepts and methodologies borrowed from data science. We test against reality, we lean towards real return. Although the perceptual, psychological and usability aspects are certainly important and are also assessed, we don’t share the academic general approach to evaluation, that tend to focus on those reductive aspects. We have a holistic approach in which being able to read or memorize values from a chart is really not so important; instead we aim to sense making, insight, complexity of tasks, capability to inform when it comes to make decisions, capability to provide vision, and, in certain projects that might contain more sophisticated analysis, including prediction, the accuracy and value of specific answers.


Header image taken from Santiago’s portfolio of incredible work.

Six questions with… Valentina D’efilippo

In order to sprinkle some star dust into the contents of my book I’ve been doing a few interviews with various professionals from data visualisation and related fields. These people span the spectrum of industries, backgrounds, roles and perspectives. I gave each interviewee a selection of questions from which to choose six to respond. This latest interview is with Valentina D’Efilippo, Information Designer. Thank you, Valentina!


Q1 | What was your entry point into the field: From what education/career background did you transition into the world of data visualisation/infographics?

A1 | After earning my Industrial Design degree in Italy, I moved to London to study Graphic Design. Then, despite graduating with a predominantly print portfolio, I found work in digital advertising. I worked as an interactive designer for various agencies over the next 4-5 years. In 2011, I set up my own company to work freelance and start focusing more on the visual display of information and data viz. Eventually I published my own infographic book: The Infographic History of the World. I think that data visualisation is the connector between the various skillsets. It’s a blend of illustration, art direction and the rigorous user focus approach of industrial and interaction design.

Q2 | What is the single best piece of advice you have been given, have heard or have formed yourself that you would be keen to pass on to someone getting started in a data visualisation/infographics-related discipline?

A2 | I personally was a bit disillusioned early in my professional career – commercial work can involve briefs with little room for artistic meaning. But luckily, I was encouraged to explore ideas that inspired me and I refocused on self-initiated projects to nurture my own ideas. I would recommend to anyone getting started in any creative field: do not let commercial routine stifle your creativity – keep experimenting, be curious and proactive.

Also, keep learning and embrace the skills you do not yet have. Especially in the world of data viz, we are required to do so many things at once – do not let your current skillset limit your exploration. Plus, the community is vibrant and open. You can work with talents who come from a variety of fields: journalism, design, coding, data science, just to mention a few.

Q3 | When you begin working on a visualisation task/project, typically, what is the first thing you do?

A3 | The first thing I do is making sure I clearly understand the brief. And, if it’s a self-initiated project, it can be even more important to outline primary objectives. For me, the most important questions are What, Why, and Who? What insight does the data provide? Why am I creating a data viz or, in other words, what is the purpose? And, lastly, who is my audience and why would they care? Once these three questions are explored, the answer to how I’m going to tell this story follows more naturally.

Q4 | At the start of a process we are often consumed by different ideas and mental concepts about what this project ‘could’ look like. How do you maintain the discipline to recognise when a concept is not fit for purpose (for the data or analysis you are ultimately pursuing)?

A4 | I love this question! I think the reconciliation happens organically when we adopt a research-based approach to evaluation and design. In my opinion, decisions on the outcome emerge from data analysis as well as research into the subject. In other words, I explore how to best display the data insights, and I parallel I consider the art direction that will be most suitable to the subject. I do not treat these two tasks independently because I believe the visual should provide clarity on the story’s topic and connect with the audience – but at the same time, it must be functional and become the vehicle to deliver and clarify the data insights. I also do not enforce a personal aesthetic preference, but I rather adopt a different style for each outcome, based on the subject represented.

Q5 | Given the popularity and exposure of your recent ‘poppies’ project, what are some of the key lessons you have learnt yourself when you reflect on your experiences with that work?

A5 | Well, there were quite a few key lessons…

Poppy Field reinforced (I hope!) the value of finding a compelling visual approach that accurately represents the data as well as connects with the audience. But the initial outcome, which was printed in the book, was limited by space and the static nature of the medium. In exploring alternatives outcome that could deliver a more comprehensive representation, collaboration was key. I would not have been able to create a worthy interactive experience without working with my talented friend and developer, Nicolas Pigelet. Secondly, it was intimidating to release to the public a self-initiated project on such a delicate subject considering some limitation with content and data source. But I came to appreciate that “it’s ok” to offer a relevant way of looking at the subject, rather than provide beginning-to-end conclusion. And finally, I learnt to appreciate more the power of social media. I must admit that I am not very engaged with social platforms, but Twitter and Facebook were powerful communication channels for both distribution and validation.

Q6 | Aside from freely accessible metrics like hits, retweets, likes etc. what has proven to be the most valuable approach you have found to evaluate your work (post completion)?

A6 | I guess that depends on the project, as they each come with different reward. Tweets and media attention are great, but for Poppy Field I was more interested in user engagement. On average people had a lengthy interactions with the website, meaning they were interested in learning and reading the content. For my book, The Infographic History of the World, for instance, the design awards and the social media attention were certainly rewarding – especially the recognition of others in the design community. But the most gratifying moments are when readers share something about their experience with your work. The most exciting thing I heard was about the book being added to academic curriculum for an English school in Venezuela. It’s so rewarding to think that something I created is helping kids to get closer to history and think about numbers in a visual form.


Header image taken from Valentina’s ‘Poppy Field‘ project.

Six questions with… Stefanie Posavec

In order to sprinkle some star dust into the contents of my book I’ve been doing a few interviews with various professionals from data visualisation and related fields. These people span the spectrum of industries, backgrounds, roles and perspectives. I gave each interviewee a selection of questions from which to choose six to respond. This latest interview is with Stefanie Posavec, Information Designer and soon to be a published co-author. Thank you, Stef!


Q1 | What was your entry point into the field: From what education/career background did you transition into the world of data visualisation/infographics?

A1 | I studied in university to be a graphic designer on my BA, then completed an MA in Communication Design, where I started to be drawn towards working with data. What’s interesting is that on the course I wasn’t really aware that what I was creating was data visualisation until someone described it later; my course emphasised designing information within the scope of book design or wayfinding systems, but data visualisation as practised by a designer was perhaps a pretty new concept then.

Q2 | We are all influenced by different principles, formed through our education, experience and/or exposure to others in the field – if you had to pick one guiding principle that is uppermost in your thoughts as you work on a visualisation or infographic, what would it be?

A2 | ‘Everything must have a reason’… A principle that I learned as a graphic designer that still applies to information design. In essence, everything needs to be rationalised and have a logic to why it’s in the design / visualisation, or it’s out.

Q3 | How do you mitigate the risk of drifting towards content creep (eg. trying to include more dimensions of a story or analysis than is necessary) and/or feature creep (eg. too many functions of interactivity)?

A3 | In my mind, I see a strong concept as being a single unified thread, where the data, the aesthetic, the visual metaphor, the editorial focus, and so on all work to communicate this grand overarching concept. This sounds strange, but I spend a lot of my time trying to mentally link this concept thread in a complete circle, tying the entire concept into a neat package. If something doesn’t help create this ‘neatly-packaged’ feeling in my mind, I cut it. (harder than it sounds, of course!)

Q4 | At the start of a design process we are often consumed by different ideas and mental concepts about what a project ‘could’ look like. How do you maintain the discipline to recognise when a concept is not fit for purpose (for the data, analysis or subject you are ultimately pursuing)?

A4 | I tend to keep referring back to the original brief (even if it’s a brief I’ve made myself) to keep checking that the concepts I’m creating tick all the right boxes. Or, sometimes I get excited about an idea but if I talk about it to friends and it’s hard to describe effectively then I know that the concept isn’t clear enough. Sometimes just sleeping on it is all it takes to separate the good from the bad!

Q5 | How important to you is the idea of establishing a workflow/process that you can adopt on any new task you work on? Alternatively, does your experience give you the confidence to be able approach tasks with a greater sense of freestyling, not being constrained by a sequenced approach to thinking?

A5 | Having an established workflow is important to me, as it helps me cover all the bases of a project, and feel confident that my concept has a sound logic. I wish I could freestyle more often, but unfortunately I think it goes against my nature! But having said that, spending much of my time working on a drawing project this year where you can’t ‘undo’ mistakes like you can on the computer has helped me become more free-form as I am less afraid of making mistakes, so I think this can be learned (after learning a basic process first, that is)

Q6 | Beyond the world of infographics/visualisation what other disciplines/subject areas/hobbies/interests do you feel introduce valuable new ingredients and inspire ongoing refinement of your techniques?

A6 | Recently taking up drawing has helped me better articulate the images I see in my mind, otherwise I still follow up on all different types of design and art outside information design / data visualisation. I try to look at things outside my field as often as I can to keep my mind fresh as opposed to only looking at projects from my field for inspiration.


Header image taken from Stefanie’s work on the project ‘(En)tangled Word Bank‘.

Talk slides from Information+ conference

This week I have had the real privilege of visiting Vancouver to run a workshop, speak at a meetup event and, primarily, to attend and speak at the inaugural Information+ conference. I gave my talk yesterday titled “Developing Visualisation Literacy: Experiences from the Front Line” which was about sharing, describing and reflecting on my experiences of commercial training and academic teaching over the past 5 years.

Andy Kirk's Talk at the Information+ Conference 2016 from Andy Kirk

Six questions with… Simon Scarr

In order to sprinkle some star dust into the contents of my book I’ve been doing a few interviews with various professionals from data visualisation and related fields. These people span the spectrum of industries, backgrounds, roles and perspectives. I gave each interviewee a selection of questions from which to choose six to respond. This latest interview is with Simon Scarr, Deputy Head of Graphics at ThomsonReuters in Singapore. Thank you, Simon!


Q1 | What was your entry point into the field: From what education/career background did you transition into the world of data visualisation/infographics?

A1 | After college I furthered my studies with a diploma in “Information graphics and newspaper design”. This led me straight into the field and straight into the newsroom. That was around 15 years ago now.

Q2 | What is the single best piece of advice you have been given, have heard or have formed yourself that you would be keen to pass on to someone getting started in a data visualisation/infographics-related discipline?

A2 | I think this is something I’ve learned from experience rather than advice that was passed on. Less can often be more. In other words, don’t get carried away and try to tell the reader everything there is to know on a subject. Know what it is that you want to show the reader and don’t stray from that. I often find myself asking others “do we need to show this?” or “is this really necessary?”. Let’s take it out.

Q3 | When you begin working on a visualisation task/project, typically, what is the first thing you do?

A3 | Read. It’s vital that you have a good understanding of your subject matter before even thinking about what a graphic will look like or focus on. The content of a graphic is the most important element.

Q4 | How do you mitigate the risk of drifting towards content creep (eg. trying to include more dimensions of a story or analysis than is necessary) and/or feature creep (eg. too many functions of interactivity)?

A4 | It’s important to manage this before it actually starts. Make sure you do all of your research before building anything. I like to map out what it is you’ll be focusing on and how you want to show it. As a project or graphic takes shape you’ll be less likely to be surprised by interesting info you find and less tempted to alter your train of thought.

Q5 | As you know there is a lot of science underpinning the use of colour in data visualisations. There is also, however, a lot that can be achieved through applying common sense. What is the most practical advice you’ve read, heard or have for relative beginners in respect of their application of colour?

A5 | If using colour to identify certain data, be careful to not accidentally applying the same identity to a nearby part of the graphic. Don’t allow colour to confuse just for the sake of aesthetics.
I also like to use colour to highlight. A single colour highlight on a palette of muted colours can be a strong way to draw attention to key information.

Q6 | We often hear how important ‘designing for an audience’ is but this is often easier said than done. How do you integrate this perspective of thinking into your own workflow? Do you have advice on any effective approach(es) you use for this?

A6 | Remember that you’re designing for the general reader (most of the time) and not people in our field. Using a very elaborate visualization technique may catch the eye of some of your peers but it’s no good if a general audience can’t understand it. When nearing a finished draft I try to show the piece to someone with no prior knowledge of the project or subject. Don’t talk them through it. Just see if they understand it and are able to pick up the key takeaways.


Header image taken from Simon’s portfolio page.

Six questions with… Sarah Slobin

In order to sprinkle some star dust into the contents of my book I’ve been doing a few interviews with various professionals from data visualisation and related fields. These people span the spectrum of industries, backgrounds, roles and perspectives. I gave each interviewee a selection of questions from which to choose six to respond. This latest interview is with Sarah Slobin, visual journalist & Things editor at Quartz. Thank you, Sarah!


Q1 | What is the single best piece of advice you have been given, have heard or have formed yourself that you would be keen to pass on to someone getting started in a data visualisation/infographics-related discipline?

A1 | Beware the asterisks. If you get all the way to the end of a project and you haven’t read it through thoroughly you may find yourself having to compensate for stray details that seems tiny but were in fact, major. (Read more)

Q2 | How do you mitigate the risk of drifting towards content creep (eg. trying to include more dimensions of a story or analysis than is necessary) and/or feature creep (eg. too many functions of interactivity)?

A2 | The best method for mitigating content creep has been to start with a clear list of requirements at the front-end of a project. This forces all parties to think through what the work the interactive is trying to do, create a list of priorities and, agree on them. The list is often more ambitious than we can accomplish, so end up with a clear sense of what can be cut from the bottom. This understanding – we can likely do X but not promise Y is very helpful at the 11th hour when the interactive takes shape and folks start to ask if we can add features. With the list we can look at what is possible and what has to be sacrificed. Something else that has been very useful is using this code-as-architect metaphor at the beginning of a project: ‘We need to think about the architecture at the front end. Imagine if you built a 3-storey Victorian House and then decided you’d like a modern, ranch house with huge glass windows. We’d to have to do an entire tear-down to reshape the infrastructure”

Q3 | If you had the time and resources (perhaps more skills, new tools) to revisit one project from your past and make improvements to certain features, which project would it be and what would you change?

A3 | We did this immersive last year Syria Shattered, with photos and reported and user-generated video. We were working super hard to make a very heavy experience lightweight (so many videos and photos) but in the process didn’t work through our navigation structure well enough. Getting the technology right was super difficult. I was so bogged down with the story and the assets and building out the modules that I didn’t have bandwidth. My fear is enough folks didn’t stay for the entire narrative.

Q4 | What advice would you give to anyone working under the pressure of tight timescales: What are the compromises you are willing to make vs. those you are not? How do you juggle an ambition to innovate within the constraints you face?

A4 | I’m always the fool looking at the sky who falls off the cliff. In other words, i tend to seize on ideas because they’re exciting or innovating without thinking through the consequences of the amount of work they will entail. I find tight deadlines energizing. Answering the question of ‘what is the work the graphic/visualization trying to do’ is always helpful. At minimum the work needs to speak to this. Innovation doesn’t have to be a wholesale out-of-the box approach. Iterating on a previous idea, moving it forward is innovation. The Billion Dollar Start-Up Club is pretty straightforward. By adding an interesting visualization at the top it becomes innovation.

Q5 | We often hear how important ‘designing for an audience’ is but this is often easier said than done. How do you integrate this perspective of thinking into your own workflow? Do you have advice on any effective approach(es) you use for this?

A5 | The hardest thing to do is to listen to feedback when you’ve been crunching on a project for a long time. It’s super-important to show several people what you’re working on and get reactions. If you have more than one person saying ‘I missed that’ you have clear guidance that there is something you need to address. You can fool yourself into thinking you’ve found a solution for something if you’re working in a bubble.

Q6 | For a potentially multi-faceted story/subject, how do you arrive at a judgment of what will be the most interesting and relevant slice of analysis to focus on for a visualisation/infographic? What specific attribute of journalistic experience and skill do you think helps you to achieve this?

A6 | The interesting data usually floats to the top. You have to be able to look at superlatives and be ready to start over if you come up with a flat line. It’s important though, to be clear on which questions you want to ask from the data from the outset. This means you have to do some homework, know what has already been done and know enough about the data to interview it. It requires the discipline to do your homework, the ability to quiet down your brain and be honest about what is interesting and also a certain amount dogged persistence.


Header image taken from Sarah’s portfolio of work for the New York Times, Fortune and WSJ.

Six questions with… Scott Murray

In order to sprinkle some star dust into the contents of my book I’ve been doing a few interviews with various professionals from data visualisation and related fields. These people span the spectrum of industries, backgrounds, roles and perspectives. I gave each interviewee a selection of questions from which to choose six to respond. This latest interview is with Scott Murray, a designer, author and educator working in the learning group at O’Reilly media. Thank you, Scott!


Q1 | What was your entry point into the field: From what education/career background did you transition into the world of data visualisation/infographics?

A1 | As an undergrad, I majored in environmental studies, or, actually, “environmental theory,” which was a self-designed major I invented because my college didn’t yet have environmental studies. The idea was to study environments and how individuals and groups of people situated themselves within those spaces. It sounds far away from visualization, but to me they are both about considering context, expectations, values systems, and perception. Professionally, I worked as a self-taught web designer for several years until I took Tufte’s day-long course and decided I needed to quit and do something more visually creative. (The web wasn’t a super visual place back then!) I went to grad school at MassArt’s Dynamic Media Institute, where my advisor Jan Kubasiewicz suggested I check out this new tool called Processing out of MIT. I spent my first winter break learning how to create interactive things with Processing, and that January I exhibited my first project: the ASCII Photo Booth, still one of my favorites. Through Processing I learned about Ben Fry’s work, and Stamen and a handful of other firms that were just starting to do mapping and visualization projects. It was exciting stuff, and, combined with the open data movement, it seemed the world of data vis was just about to burst open. Happily, it did!

Q2 | What is the single best piece of advice you have been given, have heard or have formed yourself that you would be keen to pass on to someone getting started in a data visualisation/infographics-related discipline?

A2 | Create something today, and publish it online today. Then repeat that process every day. You are bound to push yourself, learn a great deal, and make connections with the people whose work you admire. Invariably, people who are new to visualization want to know where to begin, and, frankly, it’s understandably overwhelming. There is so much powerful work now being done at such a high level of quality, that it can be quite intimidating! But you have to start somewhere, and I don’t think it matters where you start. In fact, it’s best to start wherever you are now. Start from your own experience, and move forward. One reason I love this field is that everyone comes from a different background — I get to meet architects, designers, artists, coders, statisticians, journalists, data scientists… Data vis is an inherently interdisciplinary practice: that’s an opportunity to learn something about everything! The people who are most successful in this field are curious and motivated. Don’t worry if you feel you don’t have skills yet; just start from where you are, share your work, and engage with others.

Q3 | We are all influenced by different principles, formed through our education, experience and/or exposure to others in the field – if you had to pick one guiding principle that is uppermost in your thoughts as you work on a visualisation or infographic, what would it be?

A3 | Context is key. You’ll hear that the most important quality of a visualization is graphical honesty, or storytelling value, or facilitation of “insights”. The truth is, all of these things (and others) are the most important quality, but in different times and places. There is no singular function of visualization; what’s important shifts with the constraints of your audience, goals, tools, expertise, and data and time available.

Q4 | Following the research you did last year, what are your reflections on the perceived importance of following a working process: Do the people you interviewed genuinely place an importance on observing some sort of workflow in their work OR were there more people who felt having an open/freestyle approach suited them better? Was there a sense of a process being like bicycle stabilisers: You need one when you start out but as you advance you become more adept without? Or is it as you grow it just becomes second nature?

A4 | My sense so far is that a clearly defined process is much more important for teams (like design firms) than individuals (like freelancers). This is a generalization, but in a team, expectations and responsibilities need to be clear. For some teams, the process is documented and made explicit, while for others it evolves organically in response to the demands of a given project and the skills of each team member. Individuals certainly benefit from clarifying their own processes, if only because it helps them identify what works well (or not) for them. But individuals also have the luxury of being more reactive, and taking action without running decisions by collaborators, so, in a sense, their “process” may be implicit, just the way in which their internal decision-making abilities express themselves.

Q5 | As somebody who is involved in educating others, what are your observations about what attributes separate the successful students from the rest of the pack? What capabilities are you most eagerly looking for as they enter the programme – or during – to decide if that person has got ‘it’?

A5 | Successful students have four legs, hooves, and a single horn protruding from their forehead! No, I disagree with the “unicorn” ideal that says to be great you need to be able to understand everything and do everything. Successful students are curious and highly motivated. Without curiosity, you won’t care about the project, and you won’t ask all the questions that need to be asked. (If you are not curious, this is not the right field for you!) Without motivation, you won’t keep pushing yourself to learn new things, to try yet another approach, to ask for help from others when you need it. You don’t have to be a math genius or design whiz to be great at visualization, just curious and motivated.

Q6 | If you could somehow secure 3 months to do anything you wanted, what would you love to be able to spend your time doing to enhance your data visualisation capabilities further? (Eg. Reading, making, learning code etc.)

A6 | Learning basic statistics; learning proper mathematics; catching up on reading; pursuing that backlog of personal projects; and traveling to visit people whose work I admire, interview them, and observe them at work in their studios.


Header image taken from Scott’s extensive and varied collection of previous work.

Six questions with… Kim Rees

In order to sprinkle some star dust into the contents of my book I’ve been doing a few interviews with various professionals from data visualisation and related fields. These people span the spectrum of industries, backgrounds, roles and perspectives. I gave each interviewee a selection of questions from which to choose six to respond. This latest interview is with Kim Rees, co-founder of Periscopic, a studio doing good with data based in Portland, OR. Thank you, Kim!


Q1 | What was your entry point into the field: From what education/career background did you transition into the world of data visualisation/infographics?

A1 | I have a Computer Science degree and had a strong focus on math and data. I was doing backend internet programming when I stumbled across data visualization and immediately fell in love.

Q2 | When you begin working on a visualisation task/project, typically, what is the first thing you do?

A2 | Data inspires me. I always open the data in its native format (e.g., Excel, RDBMS, etc.) and look at the raw data just to get a lay of the land. It’s much like looking at a map to begin a journey.

Q3 | How do you mitigate the risk of drifting towards content creep (eg. trying to include more dimensions of a story or analysis than is necessary) and/or feature creep (eg. too many functions of interactivity)?

A3 | We are extremely diligent about documenting everything at the start: features, interactivity, level of detail, etc. We’re in constant communication with the client to make sure they understand exactly what they’re getting. If we’re all in agreement, we have a very clear line that we can guard against creep.

Q4 | If you had the time and resources (perhaps more skills, new tools) to revisit one project from your past and make improvements to certain features, which project would it be and what would you change?

A4 | Our very first project was an internal one that dealt with sexual assault. We were extremely unskilled at that time. I would love to go back and do that issue justice; it’s a hidden tragedy that I would love to bring to light.

Q5 | As you will fully appreciate, the process of gathering, familiarising with, and preparing data in any visualisation/infographic design task is often a sizeable but somewhat hidden burden – a task that can occupy so much time and effort but is perhaps ultimately invisible to the ultimate viewer. Obviously, pressures during this stage can come in the shape of limited timescales, data that doesn’t quite reveal what you expected and/or substantial data that offers almost too many possibilities. Have you got any stand out pieces of practical advice to share about your practices at this stage?

A5 | Adopt as many tools as possible and become an EXPERT in them! I can’t emphasise this enough. There are many tools that will do a great deal of work for you. You just have to find them and exploit them. Yes, even Excel.

Q6 | As somebody who works with and coordinates a team of people who are likely to be juggling multiple projects at anyone time, it probably goes without saying that Project Management will be an important activity. Can you share some practical advice about how you integrate project management thinking across what is (in a large part) a creative discipline?

A6 | Great management means clearing a path. The goal of the PM is to create the optimal stage for people to do their work. This usually means keeping clients at bay, limiting meetings, distilling only the relevant information for each person.


Header image taken from Periscopic’s extensive gallery of previous work.