AI is the new sensation. Will it be helpful in creating infographics? What are the dos and don’ts?

I think that AI as an aid to design is very useful to save time in tedious processes. But something very different is to expect a totally original result or to achieve something that accurately emulates what we have in mind.

Infographics is an informative need that is built on existing information, data processing, and representation of elements. Infographics must be understood by different audiences, with different levels of complexity and meeting different needs.

Infographics must be a user-centered design that reflect a creative process. Visual explanations must “understand” the audience, that is, they must efficiently show what the user is willing and interested in exploring in less than 20 seconds.

When an infographic department evolves in the ways of creating visual explanations, it is much more difficult to standardize the working methods. Artificial intelligence would need many references to achieve a fresh result, with a stamp of originality.

AI can be expected to cooperate in refining certain contents or to support us in specific processes. What cannot be expected, at least these days, is to achieve a brilliant, original, functional and instantaneous result. Besides, human information design still has an irreplaceable emotional richness, it is generated from experience and comes close to what the reader expects to see.

“What cannot be expected [ from AI], at least these days, is to achieve a brilliant, original, functional and instantaneous result…Human information design still has an irreplaceable emotional richness, it is generated from experience and comes close to what the reader expects to see.

There is another aspect that I would like to mention. The authors of infographics have the intention of expressing and sharing their own ideas when creating a visual piece. And the result can be stimulating when we notice a good reception from the audience and our peers, or it can be frustrating when it is not. It’s all about the ego of the creator. When finishing a graphic, the expectation is to achieve something as close as possible to what we have conceived in our mind. Automating that journey through AI doesn’t seem to be an option that many of us seriously consider. 

South China Morning Post is one of those publications that promotes infographics. Can you explain how the print readers and web viewers have responded to them?

Our printed infographics have a good reputation among our audience. Our newsroom is always open to give us the space to publish our material, and that is a privilege. There is also something we have noticed, on the day of the publishing of a printed infographic, we always post our printed page on social media (Twitter or Instagram), which gives us good traffic and great feedback. That tells us that people still appreciate seeing all the information in one static frame. This encourages us to continue publishing full page infographics and to continue exploring the many possibilities that paper offers.

For our online pieces, we have a very solid post-production system connected to multiple areas of the newsroom, which allows our work to be promoted on the web. Obviously the exposure time [to infographics] is limited, since the publication’s offerings are massive and there are many other articles to highlight on our front page, but when the numbers (visits) are good, and they often are, the permanence of our work extends for a few days.

It is a way to understand the audience as well, by reviewing the number of page views and the behaviour of a visual story over time.

There are stories, which are the result of a long working process, involving resources, time, discussions and planning, finally receiving satisfactory results.

On other occasions, we create very simple stories that have required little effort and production time, which achieve surprising numbers and which maintain a very acceptable level of visits over time.

Which work thrills you more—print or web? And how different are they?

I have a strong background in print, however, I think the online platform offers many more possibilities and obviously has a wider reach. That said, I can’t lean towards one in particular. Making infographics for print has a charm from start to finish (because obviously there is an end point to the process of infographics for print, not so for online), and it always connects me to the beginnings of my career in visual information.

The exciting thing about print is that time, space, and resources are limited so it demands more creativity and practical thinking.

Online infographics, on the other hand, allow the development of topics in different dimensions, it imposes a wide range of skills as in content, form and functionality, but it does not limit the expressions and creativity, on the contrary, it expands them.

Online pieces require a permanent tracking and solid testing processes to ensure the good performance of the information for all users, all the time.

Even though print infographics are more permanent and tangible than online infographics, I like the immediacy and the capacity for permanent editing and expansion that online work allows when it comes to sharing my work with the audience.

Can you explain how you or your team visualised the project “Fly at your own risk: Nepal’s poor air safety record”?

After the plane crash in Pokhara, multiple videos and images of the catastrophe emerged, our idea at first was to explain the accident in a breaking news format, but after doing some research, we realized that it was more important to explain the reasons for the increasing number of accidents in the skies of Nepal. The infographic was published three weeks after the accident. And it includes mainly general statistics on Nepalese civil aviation, the existing standards, and the complexity of the conditions imposed by the geography on the most experienced pilots.

We started the project by understanding how the accident happened and explaining the characteristics of the crash site.

We include a detail of the ATR72-500 model, in those days a theory of the cause of the accident arose, based on the observation of some videos made from the cockpit, where you can see that the flaps were not properly deployed at the time of the approach, causing the speed of the aircraft to not decrease. This point is explained in the diagram.

 An interior layout of the aircraft and dimensional references were also included.

In civil aeronautics there is fortunately a lot of information available, which helped us to define a series of visualizations, we only included in the project the most relevant ones.

An example is a graph that shows which are the most critical phases during a flight in Nepal, we realized that accidents occur towards the end of the trip, practically in 50% of the occurrences, as shown in the following diagram:

In all our projects, the usual thing is to create an image that opens the piece, this image is also used for the promotion of the infographics in social networks. It is part of our process, and I can affirm that it is one of the tasks we enjoy the most.

Do you work on a template or approach every graphic independently?

That depends on the type of graph we are working on. For the simplest and daily coverage we use templates, for those projects in which we can invest more time and resources, we always look for an original and different approach. Each topic represents an expectation to accomplish, as well as each artist has a particular vision of how to tell a story and we respect that before anything else.

What are the most important considerations for infographic designers?

Nowadays the word “infographics” is not enough to describe what we information designers or visual journalists are currently developing. Visual storytelling is too broad, and stories can be told in multiple ways. In that sense, infographics departments have evolved towards more dynamic results, but essentially connected to a creative way of captivating the audience using unique visual narratives, and originating from direct experience (field reporting, first-person research) rather than relying on more common formulas such as isometric representation of a space, or the use of a set of graphs and diagrams. It has been a long time since it required some expertise to create this type of element, now there are many tools available that deliver quite acceptable results.

You also have to consider what the audience is willing to explore. My suspicion is that more than some readers when seeing an isometric drawing (just as an example of a widely used method of representing a space in an infographic) may feel some aversion because it tends to be an overly recurrent and technical representation of reality, and to put any minor obstacle between the information and the reader these days is always a risk.

For me, the most important consideration to keep at the top of the list, is to enhance the ability to discover stories that deserve to be told visually. The technical aspects, interactivity and virtuosity are very important but without the first ability it will be hard to produce interesting visual explainers.

Can you explain how you visualised the award-winning project “Life in a Shoe Box”?

Hong Kong is a vibrant and cosmopolitan city, full of attractions and contrasts, one of them is represented by the great difference in the living conditions of its inhabitants. It is considered one of the most expensive cities in the world, which is partially true in my experience. What is really expensive here is housing. The monthly rent for half of the apartments is at least US$2,250, while Hong Kong households’ monthly median income is US$3,600.

This problem is exacerbated for those living below the poverty line (20% of the population, or 1.65 million people), who face serious difficulties in finding decent housing.

A practice among many landlords is to subdivide an apartment into modules, it can be three or four modules in one flat, but there are also cases where the situation is extreme and the space is forced to accommodate up to 20 small modules (which sometimes means having 20 sq.ft. spaces for one person). Obviously the conditions offered are deplorable.

In general, these types of configurations are found in old buildings, with low maintenance, poor thermal insulation and non-existent security measures. The inhabitants are generally older men with very low incomes and no family to help them.

This is one of the aspects that has been widely covered previously by the media, in the form of reports and documentaries, but the challenge we had as a team was to provide more direct spatial references and represent in a more vivid way (without using photographs) this reality, to put the reader in a new perspective in front of this situation.

From this starting point we proposed to consider any detail that would help to understand the limitations in space and comfort of the residents of these cubicles.

We planned several interviews and a round of visits to apartments where the landlords maintained inhabited cubicles.

With the help of a local NGO that was visiting many of these places to distribute medicine, food or some legal assistance, we were able to enter the flats for field research, in order to cover technical aspects such as materiality, dimensions, lighting, ventilation, use of common and private spaces, etc., and human aspects such as coexistence, urgent needs, sanitation problems, daily routines, experiences and opinions of the tenants.

During each visit the team was equipped with cameras, notebooks, measuring instruments, etc. in order to capture the maximum information, we knew that the chance to visit the places again in the short term was very hard.

The team decided to use mainly illustrations; this was a decision discussed in the planning stage. We completely ruled out the use of photographs or videos in our piece because we didn’t want to expose real homes, and the intention was to respect people’s privacy. In addition, the attractiveness of an illustration, based on analysis and made from videos, images, quick sketches, and 3D modelling tools helped to visualise the elements, and to show more accurately the composition and structure of the small rooms.

Here’s the sketching from original idea to final visual analysis:

A 3D model allowed us to displace-rotate the walls of the cubicle in order to avoid hidden objects and angles and see how every surface of the limited space is used by the resident.

By combining digital and traditional drawing techniques, the final product enriches the user experience and delivers a more immersive result. Animations were included in the beginning to contextualise the location of these houses. Various illustrative styles were combined to accurately depict the critical living situations of these people as witnessed by each artist.

Official figures or data reports from local universities were the complement of the field investigation, in order to show a complete panorama of housing solutions in Hong Kong at all levels. This information allowed us to add references of area and cost per square foot.

Pencil sketches at each location were followed by 3D models and animations. These served only as a base to build the final appearance of the piece, which preserves well-differentiated illustrative styles and follows defined functions. An informative animation at the top gives a very close idea of the real appearance of the places, another line-drawing style done in Procreate helps to explain the cubicles, and a few larger, more generic, illustrations were used to separate and represent the following explanation of each housing type.

After the production of the assets and writing the story, it took us several weeks to make the online piece fully operational for all platforms. We had several rounds of revision, correction and polishing of visual details. The published piece gives readers an updated and realistic portrayal of many Hongkongers’ living conditions.

The full research process and the round of interviews helped us to build one big infographic and three long read stories with illustrations and charts. The active role of our reporter Fiona Sun in all the process of gathering information combined with our field work and research, helped us to have original content and an unique approach to a well-known issue of this city.

As an infographic expert, how do you visualise the growth of infographics and the new platforms on which it can spread?

The growth and [unification] of infographics on the new platforms will necessarily depend on the degree of functionality they offer. It does not mean that complex infographics or those that are a very personal expression of the author will disappear. All kinds of infographics will continue to exist; Just as today it is possible to find a wide range of them, from the unreadable one to a super-efficient piece. At the end of the day, the audiences will always be very diverse and there will continue to be products for specific groups of people.

But the visual journalist, which seeks to inform well and quickly, will need to put the user at the centre of his or her priorities.

If we ask ourselves, “What is a successful infographic?”, today we can have multiple opinions, according to our principles, aesthetic beliefs, experiences, or needs. Maybe in the future, we will say something totally different. But my feeling is that the answer related to the number of visits or clicks will be the one at the top of the list. 

European, American, and Spanish approaches to infographics look very different. How do you differentiate them?

It is well known that information graphics departments around the world are very different in their nature, functions, and origin.

There are some teams with 30 talented people ready to cover different needs, and others with only four designers trying to give their best, and in many cases achieve amazing results. What determines the approach to infographics of each team is the relevance they have in the newsroom, the autonomy and support they receive, the resources they are provided with, and the topics they are allowed to cover, among other factors

I don’t think there is a big difference in how topics are explained, the visualization formulas or explanatory techniques used in Europe or America are similar—what obviously changes is the story they want to tell, but the most relevant factor to make a huge difference is the resources available backing the infographic work.

Infographics or data visualisation. Which one do you love most? And why?

Today and during the past, the term infographics has been widely used to describe products that are not infographics, when searching in Google, practically 100% of the results are wrong, and then it is necessary to refine the search to find a real one.

Both disciplines are in my heart, but my love is much greater for infographics (which also include clear and clean data visualizations, useful for a big audience).

Since my childhood I was intrigued and captivated by the brilliant way that diagrams, thematic maps, scientific illustrations, and later, infographics explain complex phenomena, structures, places, and situations.

I started in infographics in 1996, back then it was a different scenario, different urges and concerns, different skills to learn, different things to feel proud of, and different motivations. And the constant evolution that infographics experienced along all these years keeps me amazed. I would say, the Malofiej Awards made our beloved profession grow and change to reach unexpected limits. I really miss that event, same as many other colleagues

Infographics is something that wraps you from the beginning and shows you multiple paths; it can be kind but it also can be harsh. It can show you all the fields of knowledge, it gives you the chance to learn, it can take you to many places if you want, and it can introduce you to plenty of interesting people.

At this point, I think it is a kind of unconditional love.

The post Marcelo Duhalde’s Graphics Bring Journalistic Investigations to Life appeared first on Nightingale.

If you received Issue 2 of Nightingale magazine then you would have seen “Inspiring a Movement,” an article by Claire Santoro, and the accompanying data visualisation, “The Growing Influence of the Warming Stripes,” which together tell the story of how Ed Hawkins’s Warming Stripes have grown into an international visual symbol of the climate movement. As we began researching the many ways that Hawkins’s visualisation has been used in the five years since he first displayed it at the Hay Festival, Claire and I found the story so interesting that we couldn’t wait to dive in and explore the Warming Stripes’ impact visually. What we uncovered was fascinating, starting with the Stripes’ origin story (it was inspired by a baby blanket, and came after another, similar visualisation on a scarf), through to its adoption as a symbol of the climate movement and appearance on a vast collection of items—from coats at London Fashion Week, to Greta Thunberg’s book cover, to Reading FC’s uniform, to multiple U.N. Framework Convention on Climate Change events.

In this article, you’ll be taken behind the scenes of how the data visualisation was created, the research behind the graphic, and my personal process when it comes to designing information. Here, the six steps of my design process, as used to create “The Growing Influence of the Warming Stripes.”

1. Choose a subject that intrigues you

The Warming Stripes is an unusual data visualisation. The graph has no numbers, no axis, no labels and no legend; instead, it consists solely of red and blue stripes that show a sharp increase in the average global temperature over the last century. And yet, it has become one of the most well known, most popular pieces of information design over the last couple of years. 

Why is it a “good dataviz” if it breaks all the rules? Because it plays on what humans know already. We know that a timeline traditionally flows from left to right, and that blue colours imply cold, while red implies hot. Hawkins’ choice not to follow the traditional dataviz rules, in my opinion, probably helped create a graphic that people instantly relate to on an emotional level, which makes it more likely to spark change within the climate movement. I was excited to dive in and learn more about its impact.

2. Research your subject thoroughly (it might take a while!) 

Our research into the Warming Stripes kicked off by interviewing Ed Hawkins himself (who, of course, wore a Warming Stripes shirt!) to learn how his visualisation came about, followed by a very long Googling session to find notable instances of the Warming Stripes being used on items. 

Thanks to all that Googling, I identified more than 80 “notable” uses of the Warming Stripes and documented them within a large spreadsheet that described each item, its location, category, creator/company, and any reference links to photos or news articles. It was inspiring to see the spreadsheet grow as I discovered new examples of where the Stripes were being used.

I was then faced with the challenge of how to quantify these items. How can you measure something without a numerical metric? How can you document the impact of an item when you don’t have a comprehensive list of its uses and locations? To overcome this, I came up with a common metric to use across all items: the total social media following for the item’s creator or promotor. For example: Enter Shikari headlined at Reading music festival in 2019 and used the Warming Stripes as their backdrop. I quantified the social media “bubble” for this use as the sum of the band’s 1,029,008 followers and the festival’s 1,085,000 followers.

Alongside collecting data on the items that used the Warming Stripes, I compiled Google Trends data on search terms relating to the graphic. This provided rich data from around the globe that I could use to understand the relative popularity of the Warming Stripes over time. The search terms I included were:

• The Warming Stripes
• The Climate Stripes
• #showyourstripes
• Ed Hawkins
• Show your stripes

3. Sketch to bring out ideas quickly

My typical process for visualising data goes from Google Sheets straight to my sketchbook. Sketching is a brilliant way to quickly get ideas out of your head and into a visual form. You aren’t held back by pixels or grids; instead, the empty pages provide the freedom to imagine what’s possible without restrictions. 

Quite often, the data you have will determine what kind of graph you should use. For example you wouldn’t show a part-to-whole relationship with a line graph, or visualise a timeline with a donut chart. The Data Viz Project by Ferdio is a fantastic resource that I often use to help me understand the relationship within the data I have and the visual structure that might suit it. 

In the case of the Warming Stripes, I knew I needed to visualise certain metrics by year, with additional notes and insight to contextualise the results, so my sketches revolved around a timeline. I used the numerical values for the social media following to show the scale of each item. 

4. Test your data through wireframes

Sometimes, you’ll sketch an idea with an imagined dataset. You see tall peaks and sharp dips in your mind, but when it comes time to build your design, you realise the actual data doesn’t show those same peaks and dips. Maybe the data is so flat that you need to change your imagined design. (This happened to me: The sketches in the image above show my early thought processes, where I was exploring the idea of using a stacked area chart, which ended up not working due to the shape of the actual data.) It’s super important to test out the data early in your  design process to avoid major changes in later stages. 

Once I’ve sketched a few ideas for a graphic, I use Flourish or RAWgraphs to quickly plug in the data and test how it looks. For the Warming Stripes, this part of the process was even easier—Google Trends already provided line charts of my identified search terms.

This was super helpful as I could see straight away if there were any patterns or trends worth visualising. I was able to download this line chart as an SVG and edit it in Adobe Illustrator, my primary tool for creating this data visualisation. As Claire and I dug into the data, it was fascinating to see the patterns that emerged around the search terms’ popularity, like peaks around each U.N. COP event and the dip in search interest during the onset of COVID-19—we called these out with annotations so that others could explore the patterns, too.

5. Design your data visualisation 

Finally, I was ready to create the part people actually see—the infographic design. I went through many design iterations that included a variety of colourisation options and layouts with supporting graphs on the side. The final graphic used only colours from Hawkins’s graph and included two supporting graphs that visualised search interest by country and item counts by category.

Creating such a dense visualisation that was still readable for print was highly challenging but exciting. It also required close collaboration with Claire, as we figured out what information to keep in the visualisation—in annotations, captions, and supporting graphs—versus explaining in the article. The time we spent thinking through these decisions ultimately made our work stronger and more refined.

6. Share your work!

After months of work, the visualisation was finally printed and released online for people to read! 

My hope is that after viewing the data visualisation, readers realise how powerful and impactful the Warming Stripes have been despite breaking all the traditional rules of datavis. I’d love to see others inspired to follow suit and break the rules themselves!

And, of course, because the data visualisation and article focus on climate data and climate activism, I also hope that it continues to spur people on in using the Warming Stripes as a conversation starter and symbol for change.

The post The Making of “The Growing Influence of the Warming Stripes” appeared first on Nightingale.

I really enjoyed reading this book as a data visualizer because the guidance about color, typography, organizing information, considering audience, goal, context, and seeking user feedback all apply to data visualization, as well. Plus, it was fascinating to learn about science graphics, which, prior to reading this book, I’d only encountered as a reader of textbooks, magazines, and research papers.

Jen, a senior graphics editor at Scientific American, has filled the book with excellent examples and case studies that illustrate her points. For example, after introducing guidelines for making better graphics, she demonstrates how those guidelines work in practice, by walking the reader through a series of infographic “makeovers,” complete with “before” and “after” images that showcase her points.

Jen has included several Q&As with content experts in the book, including one interview with information designer Sheila Pontis, who specializes in researching how audiences engage with design. Sheila offers several examples of how to seek audience input beyond traditional interviews, such as workshops, or asking users to keep a diary or make a video of themselves as they try to understand what’s in front of them. This was a fascinating interview, and very applicable to the broader field of data visualization design as well as science graphic development. 

The book is organized into four parts. Part one, which encompasses the first half of the book, provides an introduction to science graphics and design fundamentals. Most of this section is applicable to data visualization, as well. I particularly liked Jen’s ideas for laying out information, details about color and typography, exploration of science communication, and thoughts on collaborating with communities to improve communication of scientific findings and concepts.

Jen emphasizes the importance of considering different visual styles based on both the audience and the goal of the science graphic—advice that translates to data visualization, too. For example, she recommends a more inviting style for a general audience and a more abstract and minimalist one for an expert audience. She also covers storytelling strategies and provides many methods that can be applied to data visualization, especially introducing characters (including a narrator), showing not telling, and adding context to present a more complete story. 

The second half of the book is more specific to science graphics. Part two covers frameworks and structure for science graphics, including ways to add context and communicate uncertainty. Part three lays out a comprehensive and detailed process for creating science graphics along with illustrative case studies. Jen also includes a helpful step-by-step guide—drawn as a decision tree—to structure the processes behind making a graphic. Part four covers collaboration and includes advice for working together as scientists and designers.

It’s clear throughout the book that Jen has a thoughtful and reflective approach to her work. This, in turn, prompts the reader to reflect and dive deeper into topics of their interest. I loved that each chapter ends with a “More to Explore” section with additional resources for further learning about the topic covered. The book also includes footnotes throughout, providing another source for more exploration and independent discovery.

While the focus of this book is on creating science graphics, I found many of the ideas and frameworks applicable to data visualization. If you’re a data visualizer looking for a slightly different take on data and science communication, I’d highly recommend this book. I have never made a science graphic, but I learned a lot from Building Science Graphics, and if I were tasked with making one in the future, this is the first book I would pick up.

I especially recommend this book as a resource to anyone in the field of science communication—it’s a very comprehensive guide with beautiful examples and clear guidance from an author whose expertise clearly comes through along with her deep reflections on design, process, and the field as a whole.

Disclaimer: Some of the links in this post are Amazon Affiliate links. This means that if you click on the link and make a purchase, we may receive a small commission at no extra cost to you. Thank you for your support!

The post Review: <em>Building Science Graphics</em> Is Not Just For Science Illustrators appeared first on Nightingale.

As a data visualization designer, I think about the pieces I’m working on as the visual equivalent of articles or stories. I love reading and writing using words, but I also love reading and writing using shapes and visual alphabets. Keeping in mind the people who will see and read my visualizations is essential, especially because most of my potential readers are not data visualization experts and may need keys and support to read these visual stories.

Over the years, I’ve created pieces for all different types of readers, but they all had a common characteristic: they were adults. A few years ago I was asked to use data visualization to communicate with children. I loved this challenge from the start and I’m going to talk about what I learned and the unique characteristics of this project here (thanks Nightingale for hosting my words!).

But before that, I’d like to quickly explain how I got there. I’ve been designing data visualizations as a freelancer since 2015 and I’m extremely interested in visual experimentation as a way to communicate to readers, and to engage them (when the usage context justifies it). A collaboration that allows me to explore my interest for this kind of experimentations is the one I have with La Lettura, the cultural supplement of Corriere della Sera. I design static data visualization pieces for them, combining informative content with data art: I’m in fact asked to visually experiment while communicating topics and stories.

Designing a Sky Map

Some years ago they asked me to design something different from the projects I usually work on: a “Sky Map” that would combine cartography, data visualization and illustrations to depict our world as seen by the eyes of an airplane pilot, with different boundaries and reference points to navigate the world. The visualization was inspired by Mark Vanhoenacker’s book Skyfaring. A Journey with a Pilot.

I had never mixed data visualization and illustrations before, so that project was a very interesting starting point. I’ve always loved to draw, but I stopped doing it when I started working as a designer and was losing confidence in my illustration skills. (I still don’t consider myself a professional illustrator.) In fact, at the beginning I didn’t think I would have been able to work on the illustrations and I had contacted a very talented friend of mine asking her if she had time to work on it with me (Debora Guidi). But she wasn’t available and I decided to give it a try myself. I’m very happy about that decision now!

Airplane pilots use reference points called waypoints to define their routes. Some waypoints have very nice and evocative names, such as MOON or GNOME or WHALE. I decided to use this aspect as starting point to add an illustrative element to the map and I’ve drawn some of them.

I was particularly focused on finding a style for the illustrations that would work in concert with the data visualizations — I visualized data about airplane passengers by country and airports — and I worked a lot on the palette and the shades to obtain such a result. Sky Map is a project I’m still very fond of. First, it pushed me to use illustrations as communicative and informative layers and now I love mixing drawings and data visualization when I can. Moreover it allowed me to look at the world — and then to illustrate it — from a totally different perspective: I saw it and then depicted it with different eyes, borrowing an airplane pilot’s glance (and — fun fact — I love traveling but I definitely don’t love airplanes, so it was an interesting change of perspective!)

And finally, I’m very fond of it also because it brought me a beautiful, entirely different opportunity.

A few months after the publication of the piece I was contacted by a publisher: they had seen the way I had combined illustrations and data visualization and they asked me to try something similar for a children’s book.

‘Planet Earth’: an infographics children’s book

The aim of the book, which was titled Planet Earth: Infographics for Discovering Our World, was to depict our planet combining infographics and illustrations. I was extremely excited about the idea of working on an infographic children’s book: shifting my focus from adult readers to kids would allowed me to look at things — again — with new glances and from a new perspective (such a refreshing one!) so I accepted the proposal almost immediately.

Even so, I was conscious of the fact that there would be challenges. First of all, I had never designed data visualizations for children before: I mentioned how keeping the audience in mind is essential for my job and in this case I needed support to better understand how to talk to my potential readers. Many of my visualizations — as the ones for La Lettura for instance — explore topics in their complexity layering different levels of information: they are the visual equivalent of a long article and they need time to be read.

I don’t think this is a problem when the usage context allows it: I think there is a wide range of possible approaches to designing data visualizations that depend on context, readers and communicative purposes. But such a “long reading” approach wasn’t the right one this instance. I remember a lot from my childhood, including the things I didn’t understand (I perfectly remember the first time I saw division on a blackboard at elementary school: I immediately thought, “Will I really be able to understand such a thing?”). Similarly, I wanted to entertain the young readers with something interesting, easily understandable and enjoyable.

This is why I decided to work on Planet Earth with Chiara Piroddi, who is the co-author of the book. She is a psychologist, expert in Developmental Neuropsychology and her role was extremely important because she helped me design visualizations that could be understood by our young readers. During the design process I used to send her my ideas and sketches for the potential visual representations and she was able to tell me if she thought they would be understandable for children. I think that without her support I would have oversimplified the project, afraid of designing unreadable pieces. I wanted to work on clear but also evocative and organic shapes and her feedback helped me in finding a balance.

We also worked together on the main structure of the book, which provides information on our planet from different points of view: from the atmosphere to the ocean depths, showing data on animals, plants and the environments.

Then she focused on the research phase: she extracted data from official sources and encyclopedia and we worked together to clean them and select the information to be visualized. In the meantime — while she was looking for the data — I started defining the overall style of the book: the second challenge.

Defining the style of a project is always a challenge, and this time I particularly wanted to work on the connection that a children’s book can create with readers.

I’m constantly interested in such connection with the readers. I strive for an emotional component when designing for adults, but I think that working on a book for children particularly requires giving a lot of space to this aspect. It’s important to create an emotional relationship with young readers in my opinion, trying to turn on the spark of joyful connection that a child can have with a book: I curated shapes, colors and the overall composition to try to turn on such connection.

Remembering

In general, I often find it useful to start from a personal point of view when I begin a new project: I “start from myself” trying to put myself in my potential readers’ shoes. For this reason, in my design process I dedicated a lot of time to remembering. As child I loved to lose myself in the pages of books and I remember that I really loved certain illustrated books because of the colors, the shapes and the details. This is why I spent an afternoon re-looking at my old children’s book — my parents still keep them — flipping through the pages and re-feeling all the positive emotions that they used to bring me (that they still bring me, actually). These positive feelings — and the feelings I get from the visual elements in particular — were the starting point for my own work.

The first aspect I focused my attention on was the illustrative element. I’m not a professional illustrator and I wanted to make sure that my style would have been approved by the publisher.

I already knew that they liked my illustrations for the Sky Map, so I used them as starting point. I hand-drawn the illustrations (with a black pen — I always use the same one) scanned them and then colored them with Photoshop.

I love soft shades and light colors, but this time I “pushed the saturation button” a little bit more than usual, inspired by my old children’s books. I defined a main palette of ~10 colors and I used them to create different shades.

Designing data visualizations for children

I then worked on combining them with the data visualizations. I wanted to design elements that were understandable but also visually evocative at the same time. There are certain shapes I love — I’m often inspired by the shapes of nature such as leaves, flowers, jellyfishes (I’ve been inspired by a cabbage lately) — and I kept such shapes as base also in this case and then I simplified them.

I worked on small compositions of infographics and illustrations. Drawing soft and clean visualizations helped me in creating a dialogue between the hand-drawn illustrations and the vectorial infographics: I didn’t want the two elements to clash, but rather to have a harmonic relationship.

Again, Chiara Piroddi’s role was essential. She helped me understand if my visuals would have been clear enough for a young public. A very useful suggestion that came from her is that — with data visualization being a new language for most children (and not only for them actually) — creating a familiarity connection with the shapes was important: for this reason there are some shapes and visual models that recur often in the chapters, to help children get used to them. I worked on creating a consistent alphabet and then on constantly helping the readers in using it.

This is why I’ve designed both small legends for each chapter, and also — at the same time — a unique legend in the first pages of the book, so that they could have all the tools to visually read the information and slowly learning how to use them.

This was a great opportunity to work on the emotional component of visualizations and visual elements and on how this component can help me — as designer — in creating a connection with the readers. And I had the chance to see some children’s reactions during a few workshops I’ve given. I guided them in designing compositions of infographics and illustrations inspired by the book and their enthusiasm, care and interest were truly heartwarming.

I’ve talked about the importance of keeping our readers in mind: working on this book allowed me to think about that focus during all the design phases. And this constant reminder has been absorbed and then consolidated in my current design process. This book made me also reflect on the importance of starting from a personal point of view to design a project that can create a “connection.” I’ve started from my memories and I used them to design shapes and elements with the purpose of explaining topics, communicating stories and contents but also engaging the readers. The coexistence of these factors is very important for me, also when I design visualization for adults: using the communicative potential of shapes, colors and compositions to create engagement and understanding.

And talking about potentials, I think that data visualization can be a very useful tool to communicate information and contents to children. Giving a shape to numbers is a good way to transform their abstractness into something that young readers can actually count, measure and compare. Numbers can carry with them interesting and meaningful stories and visually translating them can help bring these stories to light. I loved bringing some of our planet’s stories to light and narrating them to children.

P.S. While writing this article I was forgetting to mention two important aspects!

1. Caffeine was a major support for this project: Chiara Piroddi and I only had four months to create the book and we spent a few nights awake working on it. Time was another significant challenge!
2. The publisher asked us to design a mascot who would have guided the children in discovering the different environments, from space to oceans. I’m a longtime fan of tardigrades because they’re simply amazing and they can basically survive everywhere. So I didn’t think too much about who our mascot could have been

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Looking at the wide range of contemporary board games presented there, I couldn’t help noticing how much board games have in common with data visualizations. In fact, at their core, all board games are data visualizations. Data and information are visualized as pieces of different colors and shapes (called meeples) placed on boards specifying coordinate systems. The rules of the game determine how the current situation of the data can be transformed into a more desirable state.

Board game players are willing to pay 30–50 € for standard games, and well over 100 € for elaborate expert games. Players spend hours and hours poring over these visual representations of data. That is a degree of user engagement that would be great to also achieve for data visualizations.

The good news is that many of the elements that make board games so engaging, fun, and accessible, are equally applicable to data visualizations. In the following, I will discuss a few such points. Board games use easily readable data encodings, use overarching plots and metaphors, have graphic design that fits the topic, and represent the data in physical form.

Board games tend to use easily readable encodings of data. Categorical data is usually encoded via color hue and shape. This goes, for example, for the different kinds of meeples controlled by each player. Numerical data is usually encoded via location among common axis, number of elements, and size of elements. Board games seldom include more difficult to discern encodings like shades of a color hue (light to dark) or orientation. Using them would quickly result in misreadings and confusion.

The table shows the encodings used in traditional and contemporary board games. The game of Go uses the simplest encoding with black and white stones (interpreted as categorical color hues here although factually color shades) placed on a grid (position). Modern games very seldom use further encodings beyond those already used in the game of Monopoly, first patented in 1904.

In data visualization, if the intention is to get information clearly across, easily readable encodings should likewise be used. The experimental encodings of data art play a very important role in extending the boundaries of the genre. But for many, such elaborate encodings pose a barrier to understanding. I personally have to admit to often skipping elaborate data art if it is too tiring to decode.

Board games make use of overarching plots and metaphors to integrate masses of complicated information. Typical settings of board games include medieval trade, fantasy adventure, armed conflict, and science fiction exploration. The setting provides the information encoded on the board with an easy to understand and memorize mental model. Entirely abstract board games are much rarer. Chess is the most popular abstract strategic board game in the western world. In 1924, Bauhaus designer Josef Hartwig created suitable abstract pieces for the game. The forms reflected the movements of the pieces. These did not catch on. Today, chess still uses the metaphor of two armies with knights and bishops maneuvering against each other to kill the other’s king. The human brain craves tangible plots and metaphors.

Over the last few years in data visualization design, there has been a strong trend to move from presenting rational arguments towards telling emotionally involving stories. This was especially initiated by Cole Nussbaumer Knaflic’s 2015 book “Storytelling with Data.” Narratives integrate lots of individual data visualizations into a whole to make a clear point. The narrative also makes individual facts much more memorable. A good story usually consists of a three-part structure with introduction, conflict, and resolution of conflict.

Board game publishers go long ways to make the graphic design fit the topic. Often the general mechanism and layout of board games are designed by one person (the board game designer/author), and the final illustrations done by a professional illustrator, who sometimes remains unnamed. Illustrations, color palettes, and fonts are chosen to reflect the content.

A wide range of illustration styles are used from rational flat infographics to realistic and very artistic styles. Photographs are rarely used as image material in board games. One reason could be that the use of somewhat abstract illustrations and icons makes it easier to remain in a mental state of imagining and abstract reasoning. In Germany, there is even an award solely for the visual design of board games, the Graf Ludo. If something is beautifully designed we are much more willing to invest time understanding and engaging with it.

Data visualizations can equally be made more enjoyable by using a graphic design language that fits the topic. Header fonts can be chosen to go along with the topic. Color schemes can set the general mood of a visualization. Integrated illustrations and icons can serve decorative purposes. Many good examples of this can be found in the Tableau Ironviz qualifier Dashboards (not in the quickly prepared finals).

Part of the fun of playing board games is to have tangible objects before you. The quality of the game material plays a big role in the enjoyment of a game. Usually, cardboard, wood, and plastic are used. It is nice to touch and literally walk around visual representations of information.

Most data visualizations are pure digital products for the screen. But for workshops, showrooms, and conferences it can be worthwhile to bring a visualization into the physical world. A low-level method is to print a (static) data visualization out as a large poster. Today, there are many possibilities of turning digital graphics into physical objects by 3D printing plastic, laser cutting plywood, or laser engraving on plastic, metal, or glass. If one is willing to put in some manual work, the possibilities are endless.

In this article, I have demonstrated how many elements that make board games so engaging can also be applied to data visualizations. The points discussed in this article are the use of easily readable data encodings, the use of overarching plots and metaphors, the use of a fitting graphic design, and the physicalization of the visualization. These are the more static aspects of board games. Further discussions would be warranted for the social aspects, the interactivity (think interface design), and the gratification and rewards integrated in board games (think gamification).

After a long day, I left the board game trade fair with lots of new ideas and inspirations. To me, it is clear that data visualization designers can learn quite a few tricks from board game designers and illustrators. But the inverse also holds true. I’ve seen quite a few board games that could have been improved with basic data visualization know-how. And it makes me think: “How would a board game look that was designed from the ground up by a data visualization designer?”

The post What Board Games Teach Us About Data Visualization appeared first on Nightingale.

Zero has special significance for many axis scales. If you are traveling at zero miles per hour then you are standing still. If you have zero dollars then you are broke. The zero line is often emphasized accordingly by making it thick. Willard Cope Brinton explains in 1939’s Graphic Presentation:

The horizontal axis, zero line or other line of reference, should be accentuated so as to indicate that it is the base for comparison of values. There is no such base of comparison for the time scale in a time-series chart, however, there being no beginning or end of time. … The zero line or other base of comparison should never be omitted when the interest is in relative amount of change between points on the same curve. –Willard Cope Brinton, 1939

The zero line is essential to bar charts ?, which link total value to total height. William Playfair introduced this rule in 1786 using a stack of coins metaphor¹. If a man stacked all the coins he made at the end of each day into a new pile, then he would be able to see time, proportion, and amount all at once simply by looking across all of his stacks. Pierre Levasseur poetically referred to vertical bar charts in 1885 as columns of stacked facts². In either case, you have to see the whole stack, i.e. the zero line, to have an honest look.

We sometimes omit the zero line on line charts ? when our interest is in the absolute, not relative, amount of change. In this case a non-zero baseline appears (in the cartoon above, 50). This is familiar to many as the movement of a stock price over time. We like zooming in to see detail. It is bad practice to accentuate this non-zero baseline because that implies undue importance. Instead, today’s standard practice has us style all non-zero lines the same way because they all share the same significance. Design mirrors — and conveys—meaning.

Standard practice does not directly indicate the omission of the zero line. I contend that this standard practice is too passive—and passive design is risky design. Here, the risk is that the non-zero baseline’s position, even with uniform styling, may still convey undue importance. How can our approach be more active? Brinton provides the answer:

A torn paper metaphor helps. A jagged or wavy baseline calls to the reader’s attention: This is not a reference line! It alludes to the zero line, offscreen, by showing that only part of the scale is on display. The wavy baseline is intentional. It is forward. You might even say it is more honest.

Brinton’s wavy lines³ are not an accidental fluke. They appear in many more examples and their use is detailed in the chapter “Standards for time series charts”: When the zero line is omitted, this is one method of indicating its absence. Brinton even includes a variant, a straight line waved at each end, pictured here as method (b).

Data visualization, and graphic computing generally, has made great hay from pictorial metaphors that mimic the real physical world. By linking abstract concepts, like deleting a file, to real-world objects, like the ?, we make the strange more familiar. Designing with worldly metaphors in mind, such as bar charts representing stacks of stuff, can help us produce visualizations that are more accessible, and more meaningful, to all.

Willard Cope Brinton was an American consulting engineer famous for his landmark Graphic Methods for Presenting Facts, a 1914 textbook that perfectly packaged all of the previous century’s graphic inventions for modern industrial use. He also led the Joint Committee on Standards for Graphic Presentation, which included 15 scientific societies and 2 Federal Bureaus. Andy Cotgreave, Tableau’s Technical Evangelism Director, was the first to introduce me to Brinton via his 100 yrs of Brinton tumblr. Read Andy’s highlights from Brinton there, then dive into hundreds of beautiful charts and expert commentary from the original book and its sequel: Graphic Presentation (1939):

The torn baseline example above was brought to my attention by Jason Forrest. He shared it in a Data Visualization Society thread about historic visualization. While we certainly delight in appreciating the craft of those who showed before, I believe our interest has a practical undertone.

Historic practitioners faced the same challenges we do today: Data overwhelmed their capacity to manage it. The audiences they had to inform were lacking in graphic and numeric and statistical literacy. Yet, historic practitioners worked to meet these similar challenges in totally different contexts. They had different tools, different constraints, and different advantages compared to modern practitioners. It is the intersection of such a similar pursuit with such different conditions that produced so many interesting solutions. Many of their natural solutions, like the torn baseline, are less likely to emerge in today’s digital environment, where we work under own unique constraints.

Certain creative paths open at different moments in history. I am so happy to have learned from this example and am excited for the future discovery of more past solutions. It excites me to return to Brinton—and the many who inspired him—and keep looking.

☞ RJ Andrews is a data storyteller and author-illustrator of Info We Trust.

[1]: From William Playfair’s The Commercial and Political Atlas (1786) p. xi: “Suppose the money received by a man in trade were all in guineas, and that every evening he made a single pile of all the guineas received during the day, each pile would represent a day … so that by this plain operation, time, proportion, and amount, would all be physically combined.”

[2]: Levasseur’s original text is “ Les colonnes de faits empilés.” See the original essay “La Statistique Graphique” in the Jubilee Volume of the Statistical Society (1885). Link.

[3]: Of course, the lessons from this single Brinton example do not have to end with the wavy baseline: note the beautiful year-quarter labels, accentuated 100 Per Cent line, and use of color to show change in data.

☞ Thanks to Jason Forrest & Elijah Meeks & Duncan Swain & Alan Wilson for contributing to the original enthusiastic discussion about this design.

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