Six questions with… Stephanie Evergreen

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 Stephanie Evergreen, Data Visualisation author, trainer, consultant and the rest. Thank you, Stephanie!


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 was a researcher and evaluator who got really bored and frustrated with how my colleagues and I were talking about our work.

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

A2 | I ask “what’s the point?” because the answers drive everything else I’m going to do. The answers determine audience, copy, graph type, level of interactivity, color use, and so on.

Q3 | With deadlines looming, as you head towards the end of a task/project, how do you determine when something is ‘complete’? What judgment do you make to decide to stop making changes?

A3 | When it feels right in my gut. Before that time, there’s a nagging feeling that sits with me until all the small things are fixed.

Q4 | As somebody who is involved in educating others, what are your observations about what attributes separate the successful delegates from the rest of the pack and/or the organisations most ready to successfully adopting your teaching?

A4 | The most successful are those who have permission to change. Sometimes that permission is internal, within the individual in the seat. Oftentimes that permission is from a supervisor, department head, or executive. I show people how to change and how easy it is to be better, so usually the last obstacle is the permission to do so.

Q5 | 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 new tools etc.)

A5 | Taking a pottery class. Seriously. For two reasons. First, it’s about work-life balance. I find that the more hours I spend at the computer or on the road to give a workshop, the less creative I am. And creativity is necessary for innovation. It’s on that walk around the block to enjoy the fresh air that I solve problems and dream up new ideas to test. Getting away from my data visualizations will actually enhance my data visualizations. Second, ever since I started working in this field, I’ve had a dream of creating some client’s keystone data out of clay, 15 feet tall, to show off in their lobby.

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 | I ask about audience straight away because it does change some of the decisions I’ll make when I’m visualizing. Things like decimal points and error bars are not appropriate for public audiences but perfectly fine and even expected when the audience is made up of scientific peers. But sometimes I think audience differences are overrated. Scientists, reporters, corporate executives, and your boss are all humans and thus all visual beings who want to see the important stuff visualized.


Header image taken Stephanie’s new book ‘Effective Data Visualization’ available via Amazon.

Six questions with… Alan Smith

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 Alan Smith OBE, Data Visualisation Editor at the Financial Times. Thank you, Alan!


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 | My entry point was cartography/Geographic Information Systems (GIS) – but in a very specific way. My thesis for my Masters in GIS, back in 2003, was essentially ‘do you need GIS anymore to put maps on the internet?’ – it was a long look at Scalable Vector Graphics (HTML/SVG, the underlying technology exploited by d3). Even that far back, it was clear that web technology was going to encourage content convergence – maps, charts, images, text, all in one single format . Basically, the toolbox was being opened right up. I think visualisation as a discipline has benefitted massively from that. Now, we’re starting to see visualisation appear in academic curricula, across a variety of disciplines, which can only be a good thing.

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 | Given my background at the Office for National Statistics, I would have to say the statistical principles! Are you picking out and emphasising key statistical relationships in your data in a way that will make sense to users? That doesn’t mean everything has to be a bar chart – but it can be a very strong way of managing the audition process when it comes to choosing the right symbology.

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 | That’s difficult – because there is not one project I have been involved in that I would execute exactly the same way second time around. So I could conceivably pick any of them – and probably the thing they could all benefit most from? More inter-disciplinary expertise…

Q4 | 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?

A4 | Develop personas to represent your users and their needs – this helps you to move away from thinking only ‘what can they understand?’, but also ‘what do they need?’

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 | Don’t under-estimate the importance of domain expertise. At ONS, I was lucky in that I was very often working with the people who created the data – obviously, not everyone will have that luxury. But most credible data producers will now produce something to accompany the data they publish and help users interpret it – make sure you read it, as it will often include key findings as well as notes on reliability and limitations of the data.

Q6 | You will also play a key role in evaluating work that your team creates. What are some of the key components of assessment you are making when determining if a design is at the right level to be published/launch?

A6 | Check off each design against your own maintained content standards…(so make some – and continually improve them!)


Header image taken the FT article ‘Global trade: structural shifts’.

Six questions with… Jen Christiansen

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 Jen Christiansen, graphics editor at Scientific American. Thank you, Jen!


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 came at the field from an illustrative background. I’ve been practicing art ever since I can remember. Formal training started in high school, when I took classes and worked in a painting and illustration studio, cleaning palettes while watching the pros that leased studio space. But I was also a science-fair and science-olympiad kid. In college I managed to keep a foot in both worlds, and completed a double major in geology and studio art. But what about the next step? Was I a scientist or an artist?

I loved the clarity and order inherent to the scientific process; ask questions, set up methodologies, collect data, analyze. No matter the result of the study–don’t even ask about the punch line of my college honors thesis–it gave me the chance to contribute a rigorously-produced bit of knowledge. But I also loved the idea of communicating through visuals rather than words. My studio arts classes encouraged me to question and morph methodologies. I couldn’t stop making images. Nor could I imagine choosing one discipline at the expense of the other. Scientific illustration, however, would allow me to merge those two identities. I was thrilled to find the perfect graduate program for me at the time: Science Communication/Natural Science Illustration at the University of California, Santa Cruz (the program is now located at CSU, Monterey Bay).

I eventually shifted from illustrating objects (like newly described species) towards art directing process and concept diagrams for magazines and textbooks. Instead of contributing new scientific findings to the world, I found a niche helping to make sure that other peoples’ findings were accessible to wider audiences through a visual language. Science research is heavily rooted in data collection and analysis, so data visualization was always a part of the tool box.

Q2 | With deadlines looming, as you head towards the end of a task/project, how do you determine when something is ‘complete’? What judgment do you make to decide to stop making changes?

A2 | Magazine work revolves around hard-deadlines, and we’re dealing with overlapping monthly issue production schedules, so it’s critical to keep things rolling forward efficiently. In order to keep the article team focused on really reviewing sketches carefully, I try to keep change requests limited to 3 rounds: in response to (1) concept sketch(es), (2) tight sketch, and (3) final. The concept sketch phase is the time for experimentation and creativity. At this point, I’m looking for overall setup of the information and narrative flow…the skeleton of the graphic. As soon as that basic plan is established, things really need to dial in. The tight sketch makes content-related adjustments to that skeleton, and critical content details are clarified. A suggestion of ultimate look of things starts to emerge (color palette and style). As far as the final round goes, my utmost concern is with accuracy and legibility. I take aesthetics very seriously, but I’ll generally pull an all-nighter before a press-date only in the event of correcting issues related to accuracy and legibility.

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 | For me, it’s largely about serving the content, and developing a visualization that makes the main points clear. Since I’m most often dealing with graphics that communicate specific research findings (as opposed to visualizing data in the process of analyzing it), there’s generally a pre-existing — and peer-reviewed — punchline. For those graphics, I keep referring to the conclusion as my guiding principle. Does the graphic help make the punchline of the story clear? How can visuals provide the background/context to understand that punchline more efficiently — and completely — than words? The graphic needs to be engaging, for sure (see response #3, below). But hopefully that can develop alongside efforts to clearly communicate the core scientific concept.

Occasionally I work in items that are more fun and exploratory in nature. If the point of the graphic is to simply get folks interested in a scientific topic, and encourage them to spend some exploring a data set or concept…. then I’m more focused on working with freelancers to create an engaging and dynamic visual. In that case, I’ll loosen up a bit, and err on the side of design choices made for purely aesthetic reasons.

Q4 | As Art Director one of your roles will be commissioning and coordinating others to contribute designs to the magazine. As you operate at the junction between designers/developers and domain experts, what would you describe as being the most important attributes of managing people/projects that help make the experience as effective and efficient as possible?

A4 | To keep things moving efficiently, and to manage everyone’s expectations fairly, I try to be as clear as possible in the initial project brief. If there’s a very specific end-point in mind, and most of the background research has already been completed, the freelance designer/illustrator’s role is very different than for a more open-ended project, when I’d like them to explore several possibilities and provide recommendations. By articulating the scope of the project, outlining a clear deadline schedule (and indicating when/if there’s any flexibility with that schedule), and providing the reference material that I already have assembled, I try to set up the freelancer to make an informed decision on whether or not they can — or want to — accept the job. And it helps to make the expectations clear. Sometimes I’m looking for an artist that can breathe life into an already decided-upon solution. In other cases, I’m looking for someone to develop a plan with very little initial direction. The distinction between those two approaches is pretty important, and it behooves everyone to understand the expectations as early as possible.

Q5 | You will also play a key role in evaluating work that you commission. What are some of the key components of assessment you are making when determining if a design is at the right level to be published?

A5 | When it comes to data visualizations, I’m obsessed with alignments. Sloppy label placement on final files causes my confidence in the designer to flag. What other details haven’t been given full attention? Has the data been handled sloppily as well? Not to mention, I then have to then spend more time cleaning up the files and preparing them for press, during the busiest time of the deadline cycle — as the full issue is barreling towards transmittal to the printer. On the flip side, clean, layered and logically built final files are a thing of beauty….and my confidence in the designer, and their attention to detail, soars.

Q6 | During your appearance on the recent data stories podcast episode, you discussed a project that used illustrations (Moritz’s bee project) almost as a visual hook to draw people in. Can you just elaborate a little more on the thinking behind that and what role you feel illustrations/photo-imagery have to play alongside visualisation assets?

A6 | I love the idea of Edward Tufte’s assertion that “Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.” But I found that when I developed magazine graphics according to that philosophy, they were most often met with a yawn. The reality is that Scientific American isn’t required reading. We need to engage readers, as well as inform them. I try to do that in an elegant, and refined, and smart manner. To that end, I avoid illustrative details that distort the core concept. But I’m happy to include them if the topic could benefit from a welcoming gesture. As I presented at the Communicating Complexity conference in 2013,

“Before you can even begin to communicate a complex topic, you must first engage an audience. Whereas minimalist and abstract iconography may be the most efficient and elegant way to communicate complex findings within a research community (arguably a captive audience), I suggest that this design approach can actually be off-putting to a non-­specialist audience. If an information graphic does not incorporate immediately-­visible context, a familiar visual vocabulary, or a welcoming gesture for the non-specialist reader, it may simply confirm a preconception that the content itself is abstract and unrelatable — thereby shutting down the opportunity to convey that information to a new audience… I argue that although it’s possible that superfluous texture, detail, and color may distract a bit of attention from communicating the core concept, the trade-­off can be worth it. Beautifully detailed and somewhat fancifully figurative art can engage and inspire a reader. This is particularly true, for example, when trying make counterintuitive and complex concepts in cosmology and quantum physics accessible to a science savvy, but non-­specialist audience.”


Header image taken ‘How Science Evolves’.

All the ‘Six questions with…’

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. The title of the series is therefore ‘six questions with…’. For convenience, here is the full collection of the interview posts so far, which will be completed in time for the release of my book at the end of May.


#1: Kennedy Elliot

6QuestionsKennedy

#2: John Nelson

6QuestionsJohnNelson

#3: Isabel Meirelles

meirelles-design-for-information

#4: Gregor Aisch

6QuestionsGregor

#5: Amanda Hobbs

AmandaHobbs

#6: John Burn-Murdoch

6QuestionsJBMFeatured

#7: Alyson Hurt

AlysonHurtFeatured

#8: Nigel Holmes

Glasses

#9: Katie Peek

Screen Shot 2015-12-01 at 14.34.35

#10: Jan Willem Tulp

6QuestionsJWT

#11: Giorgia Lupi

6QuestionsGiorgia

#12: Paolo Ciuccarelli

Screen Shot 2016-02-13 at 15.14.22

#13: Jane Pong

6QuestionsWithJanePong

#14: Lena Groeger

LenaFeatured

#15: Jen Christiansen

Graphic Science

#16: Alan Smith

AlanSmith6Questions

#17: Stephanie Evergreen

6QuestionsStephanie

Six questions with… Lena Groeger

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 Lena Groeger, science journalist, designer and developer at ProPublica. Thank you, Lena!


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’ve been interested in graphic design since I was pretty young (as a kid I would spend hours fiddling around in Photoshop). But even though I took some design classes in high school and worked a few summers at a local design firm, graphic design was always, in my mind, a hobby. It wasn’t until after college (where I studied philosophy and biology) that I turned my obsession with Photoshop into a full time job and worked as a graphic designer for a university health education department. That got me interested in science and health communication, so I decided to study science journalism at New York University. There I stumbled upon data journalism and information graphics, and after graduating in 2011 I got an internship at ProPublica, where I transitioned from mostly writing words to mostly writing code. I’ve been on the ProPublica news apps team ever since, building interactive graphics and new applications.

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 learn through projects, not tutorials. Pick a project, then learn the tools you need to complete it. A common question I hear about learning to code or get started in data visualization is “What language/tools/software should I learn?” The answer to that question is always “What are you trying to do?” Depending on the specific thing you want to do (analyze a data set? create a bar chart? scrape a website?), the tools and languages and programs will change. So I think it’s super important to remember that the project determines the tools, and it’s also how you learn. One more piece of advice: even if you feel stuck and frustrated, if you struggle for hours and feel like you’re not making progress, don’t worry: YOU ARE LEARNING. Take a look at Make It Stick: The Science of Successful Learning if you want evidence that the best way to learn is through the repeated struggle to solve problems by ourselves.

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 | Try to always do something specific and unique to the data you are working with. Ask the question: What is something that could ONLY be done with this information? Let the answer guide you. Many of my favorite and most fulfilling projects have been exploiting the uniqueness of the data to do something no one has done before.

Q4 | What advice would you give to anyone working under pressure of 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 | Admit that nothing you create on a deadline will be perfect. However, it should never be wrong. I try to work by a motto my editor likes to say: No Heroics. Your code may not be beautiful, but if it works, it’s good enough. A visualization may not have every feature you could possibly want, but if it gets the message across and is useful to people, it’s good enough. Being “good enough” is not an insult in journalism – it’s a necessity.

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 | I tend to try to imagine one person – my cousin, a college buddy, a neighbor – and try to design/write/produce something as if I were creating it for him or her. Having one person in mind helps eliminate jargon, reduce complexities, simplify complicated steps, and helps get me focused on emphasizing what is useful about this thing I’m making. It’s often better to imagine one person rather than the completely generic and all-encompassing “users,” whatever that means. Note: it’s important that this person NOT be a fellow journalist or data/tech expert, but if they are curious and open, the thought experiment should work.

Q6 | What advantages do you think working in a journalistic setting has in terms of ongoing development of your data visualisation/infographic capabilities?

A6 | The key difference I think in producing data visualisation/infographics in the service of journalism versus other contexts (like art) is that there is always an underlying, ultimate goal: to be useful. Not just beautiful or efficient – although something can (and should!) be all of those things. But journalism presents a certain set of constraints. A journalist has to always ask the question: How can I make this more useful? How can what I am creating help someone, teach someone, show someone something new? Those questions help focus a piece of journalistic work and serve as a metric on which to judge it.


Header image taken from Lena’s work for ProPublica ‘Murdoch’s Circle: The News International Scandal’.

Summary of outputs from Seeing Data research

For the purpose of convenience, this is a collection of all the articles, posts and other outputs from the ‘Seeing Data‘ research work.

ARTICLES IN ACADEMIC JOURNALS

BOOKS AND BOOK CHAPTERS

BLOGPOSTS

PODCASTS, WEBINARS & OTHER PUBLICATIONS

Six questions with… Jane Pong

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 Jane Pong, formerly of the South China Morning Post and Reuters and currently freelancing. Thank you, Jane!


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 started with bachelor degrees in the somewhat strange (unique) combination of chemistry, psychology and linguistics. Data visualisation turned out to be the perfect blend of science and arts that I didn’t know I was looking for.

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 | The work is not about me (the designer), it’s about everyone else (the audience), and it’s about establishing a connection. The connection could be aesthetic, an appreciation in form; or semantic, making people understand and care about the chosen topic. Some might argue that understanding comes first and foremost, but I believe creating a thing people find pleasing without understanding it straight away has its power too. It comes as no surprise that it all depends on context.

Though I must admit that I’m not always good at following that myself – there are times when I fall into the trap of designing a certain way just because I like it. It’s a tough one!

Q3 | 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)?

A3 | It is easy to immerse yourself in a certain idea, but I think it is important to step back regularly and recognise that other people have different ways of interpreting things. I am very fortunate to work with people whom I greatly admire and who also see things from a different perspective. Their feedback is invaluable in the process.

Sometimes I find it helpful as well to conduct mini thought experiments and work out how someone who is diametrically opposed to me in terms of background might interpret a visualisation. Would a concept still work for someone who embodies completely different knowledge, assumptions and expectations? Instead of rushing to settle on a single concept and start to develop it right away, it’s worth it to take a pause, and spend some time to really think through how the concept might or might not work in different contexts.

Q4 | 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 new tools etc.)

A4 | Reading, definitely. But not just the obvious non-fiction books, I’d love to read a lot more fiction as well to stretch my brain a bit. I feel like reading fiction allows me to find fresh perspectives on all manner of things and build empathy, which would help me as a designer in the long run (besides, reading fiction is fun!).

I’d also like to try making things that are away from the computer screen. I’ve had an Arduino starter kit sitting on my desk for months now. Another fun thing to do would be to learn geometry through drawing.

And of course, I have a list of personal projects just waiting for me to delve into! Nothing pushes you to learn more than working on something you care about a lot. I would love to build some fun interactive visualisations and in the process level up my analytic and programming skills.

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 | Expect failure. Working with data is rarely a smooth process, it often involves twists and turns and tonnes of frustration. Don’t be discouraged – keep asking questions about the data and it may surprise you. There have been times when I had to pare down the visualisation, or even discard it altogether, but it happens. (To everyone. All the time. We just don’t hear about these failures.) The quality of visualisations is proportional to the integrity of the data.

Q6 | From your experience of publishing for print, what are some of the key tips you would offer to people creating visualisation work designed for print output?

A6 | I love, love, love print. I feel there is something so special about having the texture and weight of paper be the canvas of the visualisation. It’s a privilege to be able to design for print these days, so take advantage of the strengths that paper offers – mainly, resolution and texture. Print has a lot more real estate than screen, allowing for very dense, information packed visualisations. I love to take this opportunity to build in multiple story strands, and let the reader explore on their own. Print can be interactive too (sort of). The texture of paper can also play a role in enhancing the visualisation; consider how a design and colour choices might be different on a glossy magazine page versus the rougher surface of a newspaper.


Header image taken from Jane’s work for SCMP titled ‘Rain Patterns’.

Six questions with… Paolo Ciuccarelli

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 Paolo Ciuccarelli, Scientific Director at DensityDesign Research Lab – Politecnico di Milano. Thank you, Paolo!


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 | Meaning is built (designed), not extracted. Meaning and sense are not in the data: they will – or will not – exist in a kind of “space” between the visualization (and behind it the data) and the mind of its users/readers, as a combination of what they see and what they think. That’s why I don’t like that much the emphasis on ‘Data Mining’: it’s just one step in a much broader process; and that’s way I love the term “sense-making”: we have to “make” it, and – before that – “design” it.

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

A2 | If it’s a (big) project I immediately ask the client how much time do they have to dedicate to the project. Often they didn’t even think to that, and especially for exploratory projects (i.e. exploring the data in search for meanings) it’s fundamental.

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 | A visualization is always a model (authored), never a mould (replica) of the real. That’s a huge responsibility.

Q4 | 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’?

A4 | Curiosity, first. Then the will and the capabilities to cope with the technological side/components. Coding (more as a logic than a technical task) is becoming a very important component for designers working in the field. It doesn’t necessarily mean that you need to code to work in the field, but it helps a lot. I think the profile in the future will be hybrid, mixing capabilities now separated into disciplinary silos.

Q5 | What do you feel is still the big unknown in data visualisation? If you could undertake one research project (assume any funding needed, plenty of time, good collaborators, justification are all in place) what do you feel would make the biggest difference to the field at large?

A5 | The research project would be how to make visible the metadata of data: how can we visualize what is behind the data: how this data has been extracted or precessed, what is the level of uncertainty of these processes and of the data itself; where the data come from (source) … and some of them could have different values at once: a data could be uncertain for different reasons (time – e.g. exact date of a know connection between two people – and source…) these are all aspects of the data that certainly would contribute to make sense of it but we don’t usually show.

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 new tools etc.)

A6 | Improving coding capabilities and do (more) things (hands-on): given my position at the university and within the research lab (DensityDesign) I don’t have the time I would like to have to go deep into all the projects. I was used to code in the past, so I know how it works, but between knowing and doing in this case there is a difference, given also the importance of prototyping in designing data interfaces. As I said once “if you don’t code someone else is doing it for you”, meaning that in most (if not all ) the projects we’re involved in there is always a coding component, that someone should take care of, and I think this is a clear trend for the future.


Header image taken from Density Design’s Research page.

Views from ‘Seeing Data’ research (Part 3)

This is the third in a series of three blogposts about the Seeing Data project. The first post was written by Professor Helen Kennedy, director of Seeing Data, and discussed some of the findings and what they meant for how we think about ‘effective’ visualisations. The second post reflected on one of the research methods that we used, called ‘Talking Mats’, and its potential as a means for measuring the effectiveness of data visualisations. This is the third in a series of three blogposts about the Seeing Data project. In this final part I will be reflecting on our findings and considering some implications for visualisation designers. This summarises some of the ideas I discussed in a talk I gave during a Tableau webinar in September.


Part 3: What are the implications of this study for visualisation practitioners?

In part one, Helen outlined some of the socio-cultural factors that, through our study, we found had an affect on the engagement of readers. The term ‘engagement’ in this context was deliberately broad to cover all components of a reader (which is the term I’ll stick with for consistency) experiencing a data visualisation: from the seduction or motivation to simply look at it, through using and reading the visualisation and on to the understanding that forms as a consequence of the experience.

This post builds on the framework of factors discussed in part one presenting a set of practical implications we feel are of relevance to those involved in creating data visualisations – whether as full-time professionals or part-time enthusiasts – based on the findings to have emerged from this study. That last point is important because I could speculate on many other aspects about this subject but this discussion must be rooted in what has actually been observed.

I’m sure many of the suggestions presented are quite familiar to experienced designers and developers, in which case hopefully this reinforces what you always suspected. For others, this will hopefully provide a useful framework of prompts to substantiate your appreciation about the influence these human factors might have within and across your potential audiences.

SUBJECT MATTER

This concerns the role of the subject matter and the relevance/interest this has amongst your target audience and/or recipients. ‘Design for your audience’ is always a common piece of advice but it is actually a much harder and elusive consideration in practice: it is far easier said than done but often only said and not done.

SUBJECT KNOWLEDGE: What will your intended recipients likely know and not know about this subject? What pre-requisite knowledge can be reasonably assumed? What content will need to be explained (terminology, acronyms, translation of key findings)?

TOPIC INTEREST: Will the readers likely be already interested in this topic or will they need some degree of persuasion/seduction? Marketing is a dirty word for some in this field but in certain situations there has to be an element of design thinking concerned with creating appeal towards engaging with a visualisation that might not already exist amongst cohorts of an audience.

CURIOSITIES, WANTS AND NEEDS: What do they need to know and not need to know? What curiosities are likely to be most necessary to satisfy? What are the angles of analysis you think might be most relevant to them?

FOCUS: You can’t satisfy the needs of everyone. How much is enough and how much is too much: where is the line at which you can determine that a sufficient range of content has been offered to cover the needs of enough people? Even in apparently simple and diminutive datasets there will always be multiple permutations of different angles of analysis, different filters and data treatments that you must determine NOT to include.

1. Subject

TRUST

This concerns the influence of the source/location of the published visualisation work and the potential beliefs and opinions held by the readers.

BE CLEAR: Tell people what you’ve done: where has the data come from, what have you done to treat it, what assumptions you have made, what counting rules apply, what has been excluded etc. Also, manage expectations about what does the visualisation offers and also what it does not.

BE REALISTIC: Some topics are automatically going to be invoke strong passions and entrenched opinions. You can’t convince everyone, indeed you might not need to or wish to, so be realistic about your ambitions.

QUALITY: Should go without saying but worth reinforcing: there is paramount importance in the accuracy and perceived integrity of your work. Some people inherently trust data visualisations – often when they should not necessarily do so – other people are immediately suspicious of data visualisations – often when they should not necessarily need be. You can’t compensate for all human traits but you can control the quality of your work so don’t cut corners, don’t forget to check your work, don’t be complacent.

ABIDE BY THE DESIGN PRINCIPLES: Don’t abuse visual attributes such as including unnecessary 3D decoration, distorting axis truncation, flaws in your geometric calculations, obstructive and ineffective interaction features.

2. Trust

TIME

This concerns the characteristics of the situation or setting in which the reader will be consuming the visualisation, specifically how the design aligns with the demands of time and pressure being faced in that moment of engagement by the reader.

IMMEDIACY: The setting of how a visualisation will be consumed is a significant factor in determining the effectiveness of the design you create. Serve the setting as well as the audience. Some situations will require immediate, at-a-glance insights in less than 10 seconds, others will be compatible with a more prolonged and multi-faceted engagement.

CONSUMPTION EXPERIENCE: Some situations will require a visualisation that offers explanatory assistance to bring to the surface the key insights you think the audience need directing towards, others will fit better with an exploratory experience allowing them to make discover themselves. Sometimes you might need a blend of the two, creating a journey to offer both experiences.

SHOW COURAGE AND CONVICTION: Echoing the point raised above against ‘focus’, don’t overwhelm your audience with too much. A deluge of content and a plethora of functionality can create paralysis: “Too much to take in, lost interest” (also known by the cool kids as “TL;DR”). Again, if the setting requires more immediacy, deliver it. Have the conviction and discipline to leave things out.

3. Time

CONFIDENCE/SKILL

This concerns the variety of capabilities needed to be an effective reader of a visualisation and what you can do to appreciate and accommodate any deficit amongst your audience.

WHAT SKILLS?: There are many ingredients in the recipe of data visualisation literacy: numeracy, graphical literacy, visual literacy, computer skills, language skills, critical thinking. Beyond the specific knowledge/confidence with the subject matter you a portraying, as you consider profiling the traits of your intended recipients, consider what levels across these categories your work requires and what levels your audience will likely be comfortable with?

OFFER THE RIGHT LEVEL OF HELP: Beware the curse of knowledge – don’t assume! More than just including scales and legends – provide clear introductions, useful guides for how to use interactive functions and how to read the charts presented. Offer as much assistance as the least capable/confident member of your audience might need.

DON’T BE UNNECESSARILY SELF-RESTRICTED: Don’t avoid using a seemingly uncommon or complex chart type if it is the best way to show your data – respect people’s capacity to learn but make sure you provide the necessary help. Explain where the big and the small is, point out what is good and bad or where is expected or unexpected. There is evidence that when people get over the hurdles of an unfamiliar form, insights can be unlocked that might have appeared inaccessible at the outset.

4. Confidence

EMOTION

This concerns the elusive influence that emotion plays in the engagement or otherwise of a reader with a visualisation, as well as the inherent qualities of a subject, its data and how it is presented

PLEASURE: Fun can be an important attribute of appeal. So long as it is not gratuitous, impeding the process of understanding, or incongruent with the subject matter, the appeal of certain colours, forms and functionality might help attract to and sustain readers with your work.

SUITABILITY: Respect the subject matter’s emotive quality, sometimes you may wish to exploit (in the best possible way) a subject’s inherent emotive characteristics, on other occasions you will seek to avoid it.

BASIC PRESENTATION CHOICES: It was noticeable the number of comments raised about basic lack of readability of text (through type and font properties typically being too small). This is an especially challenging task for designers faced with creating work that has to be potentially compatible across print, large screen and small screen but should be a fundamental concern about accessibility. Colours too are generally the first design properties noticed so use this powerful visual cue sensitively and astutely.

5. Emotions

The closing comment is quite simple: YOU CAN’T PLEASE EVERYONE! People are unique and bring many personal and emotional characteristics that will influence engagement without any rational anticipation. We are not always in the right frame of mind, in a bad mood or just bored. Today we like purple, yesterday we preferred blue. One day we can be “oh cool, some analysis about the US elections”, the next “oh not another piece of analysis about the US Elections”. Perfection is impossible, 100% of engagement is impossible. While ever humans are involved, visualisation has to be and can only be a pursuit towards optimisation.

Six questions with… Giorgia Lupi

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 Giorgia Lupi, co-founder of and Design Director at Accurat. Thank you, Giorgia!


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 architecture at the university, but I have never built or designed any houses.
During my M.Arch studies I’ve always been more interested in aspects concerning the representation of information, and I tried to push all my architectural and urban projects towards working with information and mapping systems; even my M.Arch thesis (in 2006) was an urban mapping project.
For the following 4 years I’ve been collaborating with different interaction design firms in Italy, focusing my contributions on visual documentation and representation, mapping, and information architecture.

It wasn’t until lately that I started working specifically with data visualization. It came natural to me to progressively focus more on the quantitative side within the information design field, and when I got to understand the true potential of working visually with structured data to convey information about phenomena or contexts, I simply felt in love with this world and the realm of possibility it opens. Then, in 2011 I both co-founded my on information design company (Accurat), and started a PhD in communication design at DensityDesign Lab at Milan Politecnico.

As for the job that I am doing today: at Accurat we rely on building multidisciplinary teams to work on our projects. Our team is made of designers, developers, data analysts, interaction designers, and also interestingly one of my partners, Simone, is a sociologist. I am coordinating the design teams for the representation part.

I believe my background in architecture has influenced my production considerably. The very fact that I spent almost 5 years of my life designing, “composing” and manually drawing architectural and urban plans shaped my mind and my visual aesthetics a lot. Moreover, I have played the piano for a long time, and I’ve been always very fascinated by the “repetitive” aesthetic of musical scores and intrigued by the contemporary music notation style; I believe this fascination of mine is reflected in my work as well.

Lastly, as a human being, I have a very visual mind, and I need to draw and sketch to understand my surroundings. In fact, I’m not usually able to perfectly get and define what I’m thinking, or what pops up in my mind about a design problem, I usually say that I cannot think about a project without a pen and some paper. I know drawing is my way to understand I had an idea in the first place.

Besides, I take an incredible pleasure in drawing, in tracing lines on paper and seeing abstract shapes come alive and I’ve came to realize this practice gives shape to my inner thoughts, and influenced my visual design production consistently over years.

Q2 | With deadlines looming, as you head towards the end of a task/project, how do you determine when something is ‘complete’? What judgment do you make to decide to stop making changes?

A2 | The short answer is: it is something you feel, it is completed when it feels “just right”.
The long answer considers of course many other aspects. I believe it’s a matter of setting the right priorities every time. We all wish we could have unlimited time to refine our projects, but we all need to deal with deadlines. The questions I usually ask myself when a deadline is hanging over my head are very practical: does it miss anything absolutely necessary for its comprehension? Is it polished and refined enough that the hierarchies of information stand out?

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 | I would say the pursue for beauty. I’ve come to believe that pure beautiful visual works are somehow relevant in everyday life, because they can become a trigger to get people curious to explore the contents these visuals convey. I like the idea of making people say “oh that’s beautiful! I want to know what this is about!”

And also, not being a data scientist or a statistician my self, I see the focus of my persona work with Accurat on designing pleasant aesthetics that tell data-stories; I like, thus, to describe my approach and our work as an attempt to “compose” aesthetically beautiful and multilayered images with data. Of course, the accuracy of information representation principles should be followed, and we try to do it while always pushing a little bit farther the boundaries of what we can produce, visually speaking.

I think that probably (or, at least, lots of people pointed that out to us) being Italians plays its role on this idea of “making things not only functional but beautiful”. I also believe that well balanced and harmonious aesthetics can add a human touch to the world of data, and thus potentially interest and attract a wider audience.

Q4 | 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?

A4 | Building an approach, a recognized method and a workflow is especially useful when you don’t work on your own but with a team of people. At Accurat, for example, we now are 20 people, and we spent a good bit to time during the last couple of years in establishing our workflow, and our principles for designing and developing our projects. A method that can be taught serves as the foundation for the collaborations among designers, and designers and developers; and it also helps new comers to embrace our design philosophy and our style.

When I work on my personal projects, or on projects on my own at Accurat, I definitely leave my self a lot more freedom. As I already mentioned, my approach consists of a lot of sketching. I draw to freely explore possibilities, I draw to visually understand what I am thinking.
I draw to evaluate my ideas and intuitions by seeing them coming to life on paper, I draw to help my mind thinking without limitations, without boundaries.

Q5 | The judgment of how to elegantly compose and layout a piece is possibly one of the least (publicly) discussed aspects of visualisation and infographic design thinking. Do you have any tips or tactics you can pass on to others about how you approach this?

A5 | I would say, first of all, every designer should learn how to “see”, to understand and be aware of what are the aesthetic qualities that attract us in all kind of visuals we like. Learning to see means observing which details make the difference in the visual aesthetics even by starting with replicating those images (and not necessarily data visualizations) that your eyes are fascinated from.

Then, play a lot with visual hierarchies, try to cut and remove all the visual clutter, make only important things stand out and leave the rest for the background.
Choose a color palette that feels beautiful (and appropriate) beforehand rather than picking random colors one after the other while designing.

Also, consider white space as a design space, and don’t necessarily try to fill the whole piece with details and elements: white space and general “air” of the compositions are key elements to its perceived elegance.

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 | Personally I think that (again!) drawing by hand and playing an instrument helps my mind to stay prolific. But more generally speaking, I believe that engaging in (i.e. making time for) personal projects is necessary.

With Dear Data for example, (a year long collaborative laborious analog data drawing effort) I realized the importance of experimenting on making things when no client is judging you and when there’s none looking over your shoulder. You can try things, you can take risks and explore hunches, you ultimately get to do the kind do work that you want to.

We are all busy (I personally don’t like the word busy), but I would encourage anyone to make a little of spare time for projects that are outside our day job. We all have a passion for what we do, we’re lucky we are in a very interesting industry, but we easily end up only making the work that helps to pay the rent, procrastinating personal ideas and projects to nobody-knows-when. I guess the most of us has a resolution list of things we want to do for ourselves but we just have a hard time making the time for that. I believe it’s just a matter of starting, and starting can be as simple as “I will go to a cafe and sit with my notebooks for just an hour every Tuesday after work”. With Dear Data we’ve created a habit for our non-demand work, it helped us staying prolific, producing more consistently and it opened up unexpected new and exciting directions.