"Absorb the data. Read it, re-read it, read it backwards and understand the lyrical and human-centred contribution." (Kate McLean) [1]
"Admit that nothing you create on 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 visualisation 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." (Lena Groeger) [1]
"After the data exploration phase you may come to the conclusion that the data does not support the goal of the project. The thing is: data is leading in a data visualization project – you cannot make up some data just to comply with your initial ideas. So, you need to have some kind of an open mind and 'listen to what the data has to say' and learn what its potential is for a visualization. Sometimes this means that a project has to stop if there is too much of a mismatch between the goal of the project and the available data. In other cases this may mean that the goal needs to be adjusted and the project can continue." (Jan Willem Tulp) [1]
"Although all our projects are very much data driven, visualisation is only part of the products and solutions we create. This day and age provides us with amazing opportunities to combine video, animation, visualisation, sound and interactivity. Why not make full use of this? Judging whether to include something or not is all about editing: asking 'is it really necessary?'. There is always an aspect of gut feel or instinct mixed with continuous doubt that drives me in these cases." (Thomas Clever) [1]
"At the beginning, there’s a process of 'interviewing' the data – first evaluating their source and means of collection/aggregation/computation, and then trying to get a sense of what they say – and how well they say it via quick sketches in Excel with pivot tables and charts. Do the data, in various slices, say anything interesting? If I’m coming into this with certain assumptions, do the data confirm them, or refute them?" (Alyson Hurt) [1]
"Context is key. You’ll hear that the most important quality of a visualisation 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 visualisation; what’s important shifts with the constraints of your audience, goals, tools, expertise, and data and time available.’ (Scott Murray) [1]
"Data and data sets are not objective; they are creations of human design. Hidden biases in both the collection and analysis stages present considerable risks [in terms of inference]." (Kate Crawford) [1]
"Data inspires me. I always open the data in its native format and look at the raw data just to get the lay of the land. It’s much like looking at a map to begin a journey." (Kim Rees) [1]
"'Everything must have a reason.' A principle that I learned as a graphic designer that still applies to data visualization. In essence, everything needs to be rationalized and have a logic to why it’s in the design/visualization, or it’s out." (Stefanie Posavec) [1]
"Good design is honest. It does not make a product appear more innovative, powerful or valuable than it really is. It does not attempt to manipulate the consumer with promises that cannot be kept." (Dieter Rams) [1]
"I focus on structural exploration on one side and on the reality and the landscape of opportunities in the other […] I try not to impose any early ideas of what the result will look like because that will emerge from the process. In a nutshell I first activate data curiosity, client curiosity, and then visual imagination in parallel with experimentation." (Santiago Ortiz) [1]
"I kick it over into a rough picture as soon as possible. When I can see something then I am able to ask better questions of it – then the what-about-this iterations begin. I try to look at the same data in as many different dimensions as possible. For example, if I have a spreadsheet of bird sighting locations and times, first I like to see where they happen, previewing it in some mapping software. I’ll also look for patterns in the timing of the phenomenon, usually using a pivot table in a spreadsheet. The real magic happens when a pattern reveals itself only when seen in both dimensions at the same time." (John Nelson) [1]
"I say begin by learning about data visualization’s 'black and whites' , the rules, then start looking for the greys. It really then becomes quite a personal journey of developing your conviction." (Jorge Camoes) [1]
"I suppose one could say our work has a certain signature. Style, to me, has a negative connotation of 'slapped on' = to prettify something without much meaning. We don’t make it our goal to have a recognisable (visual) signature, instead to create work that truly matters and is unique. Pretty much all our projects are bespoke and have a different end result. That is one of the reasons why we are more concerned with working according to values and principles that transcend individual projects and I believe that is what makes our work recognisable." (Thomas Clever) [1]
"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." (Simon Scarr) [1]
"I truly feel that experimentation (even for the sake of experimentation) is important, and I would strongly encourage it. There are infinite possibilities in diagramming and visual communication, so we have much to explore yet. I think a good rule of thumb is to never allow your design or implementation to obscure the reader understanding the central point of your piece. However, I’d even be willing to forsake this, at times, to allow for innovation and experimentation. It ends up moving us all forward, in some way or another." (Kennedy Elliott) [1]
"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? [...] 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." (Jen Christiansen) [1]
"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!' 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'." (Giorgia Lupi) [1]
"It is easy to immerse yourself in a certain idea, but I think it is important to step back regularly and recognize 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." (Jane Pong) [1]
"Look at how other designers solve visual problems (but don’t copy the look of their solutions). Look at art to see how great painters use space, and organise the elements of their pictures. Look back at the history of infographics. It’s all been done before, and usually by hand! Draw something with a pencil (or pen [...] but NOT a computer!). Sketch often: The cat asleep. The view from the bus. The bus. Personally, I listen to music – mostly jazz – a lot." (Nigel Holmes) [1]
‘My design approach requires that I immerse myself deeply in the problem domain and available data very early in the project, to get a feel for the unique characteristics of the data, its 'texture' and the affordances it brings. It is very important that the results from these explorations, which I also discuss in detail with my clients, can influence the basic concept and main direction of the project. To put it in Hans Rosling’s words, you need to “let the data set change your mind set”. (Moritz Stefaner) [1]
"My main advice is not to be disheartened. Sometimes the data don’t show what you
thought they would, or they aren’t available in a usable or comparable form. But [in my world] sometimes that research still turns up threads a reporter could pursue and turn into a really interesting story – there just might not be a viz in it. Or maybe there’s no story at all. And that’s all okay. At minimum, you’ve still hopefully learned something new in the process about a topic, or a data source (person or database), or a 'gotcha' in a particular dataset – lessons that can be applied to another project down the line." (Alyson Hurt) [1]
"Research is key. Data, without interpretation, is just a jumble of words and numbers – out of context and devoid of meaning. If done well, research not only provides a solid foundation upon which to build your graphic/visualisation, but also acts as a source of inspiration and a guidebook for creativity. A good researcher must be a team player with the ability to think critically, analytically, and creatively. They should be a proactive problem solver, identifying potential pitfalls and providing various roadmaps for overcoming them. In short, their inclusion should amplify, not restrain, the talents of others." (Amanda Hobbs) [1]
"The capability to cope with the technological dimension is a key attribute of successful students: coding – more as a logic and a mindset than a technical task – is becoming a very important asset for designers who want to work in Data Visualization. It doesn’t necessarily mean that you need to be able to code to find a job, but it helps a lot in the design process. The profile in the (near) future will be a hybrid one, mixing competences, skills and approaches currently separated into disciplinary silos." (Paolo Ciuccarelli) [1]
"The experience offered by a visualisation influences the interpreting phase of understanding. Whereas tone embodies a continuum, the judgement of the most suitable experience is more distinct and concerns different methods of enabling interpretation: explanatory, exhibitory or exploratory you degrade its existence and malign its importance. Words are not your enemy. Complex thoughts are not your enemy. Confusion is. Don’t confuse your audience. Don’t talk down to them, don’t mislead them, and certainly don’t lie to them." (Amanda Hobbs) [1]
"The key difference I think in producing data visualization/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?" (Lena Groeger) [1]
"There's a strand of the data viz world that argues that everything could be a bar chart. That’s possibly true but also possibly a world without joy." (Amanda Cox, [interview in ( Scott Berinato"The Power of Visualization’s 'Aha!' Moments, Harvard Business Review] 2013) (link) [1]
"Think of the reader – a specific reader, like a friend who’s curious but a novice to the subject and to data-viz – when designing the graphic. That helps. And I rely pretty heavily on that introductory text that runs with each graphic – about 100 words, usually, that should give the new-to-the-subject reader enough background to understand why this graphic is worth engaging with and sets them up to understand and contextualize the takeaway. And annotate the graphic itself. If there’s a particular point you want the reader to understand, make it! Explicitly!" (Katie Peek) [1]
"Using our eyes to switch between different views that are visible simultaneously has much
lower cognitive load than consulting our memory to compare a current view with what was seen before." (Tamara Munzner) [1]
"We should pay as much attention to understanding the project’s goal in relation to its audience. This involves understanding principles of perception and cognition in addition to other relevant factors, such as culture and education levels, for example. More importantly, it means carefully matching the tasks in the representation to our audience’s needs, expectations, expertise, etc. Visualizations are human-centred projects, in that they are not universal and will not be effective for all humans uniformly. As producers of visualizations, whether devised for data exploration or communication of information, we need to take into careful consideration those on the other side of the equation, and who will face the challenges of decoding our representations." (Isabel Meirelles) [1]
"What is the least this can be? What is the minimum result that will 1) be factually accurate, 2) present the core concepts of this story in a way that a general audience will understand, and 3) be readable on a variety of screen sizes
(desktop, mobile, etc.)? And then I judge what else can be done based on the time I have.
Certainly, when we’re down to the wire it’s no time to introduce complex new features that require lots of testing and could potentially break other, working features." (Alyson Hurt) [1]
"When I first started learning about visualisation, I naively assumed that datasets arrived at your doorstep ready to roll. Begrudgingly I accepted that before you can plot or graph anything, you have to find the data, understand it, evaluate it, clean it, and perhaps restructure it." (Marcia Gray) [1]
"When something is not harmonious, it’s either boring or chaotic. At one extreme is a visual experience that is so bland that the viewer is not engaged. The human brain will reject understimulating information. At the other extreme is a visual experience that is so overdone, so chaotic, that the viewer can’t stand to look at it. The human brain rejects what it cannot organize, what it cannot understand." (Jill Morton) [1]
"When the data has been explored sufficiently, it is time to sit down and reflect – what were the most interesting insights? What surprised me? What were the recurring themes and facts throughout all views on the data? In the end, what do we find most important and most interesting? These are the things that will govern which angles and perspectives we want to emphasize in the subsequent project phases." (Moritz Stefaner) [1]
"You don’t get there [beauty] with cosmetics, you get there by taking care of the details, by polishing and refining what you have. This is ultimately a matter of trained taste, or what German speakers call fingerspitzengefühl ('finger-tip-feeling')." (Oliver Reichenstein) [1]
References:
[1] Andy Kirk, "Data Visualisation: A Handbook for Data Driven Design" 2nd Ed., 2019
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