The idea

Anyone who loves their job has probably wanted to share it with their kids—get them excited about it, show how cool and meaningful it is. Even if they don’t follow in our footsteps, maybe they’ll at least respect and appreciate what their parents are passionate about.

Sometimes it’s just a dream, but we want to find a bright and engaging way to talk to our children about what we do for work.

That’s how it was for us—Alex and Natalia—working in the field of data visualization. We really wanted to share our world! Data visualization is amazing: it’s full of beauty and logic, sleek designs, a variety of charts, fascinating topics, and the chance to work with important data.

Moreover, working with data and visualization is not just interesting—it’s useful! Especially in our fast-changing world. We wanted to give children valuable skills early on so they’re ready to face the grown-up world.

We want to create shared, precious memories: to capture that magical moment when a child is still curious enough to wonder, “What does Mom or Dad do at work?”

So we thought: let’s tell and show them!

With these thoughts in mind, we started exploring the idea.

Natalia already had experience creating data viz characters and telling stories about them, but now she wanted to make stories not for adults; but for kids. Still all about data visualization. Alex already had experience writing books!

And we wanted to bring this story to life as a book!

We agreed to start the project and went off to brainstorm, sketch, and imagine!

Characters and first sketches

What’s a book without characters? Natalia decided it’d be better not to make them diagram-like people, but cute monsters or creatures. This way, they’d be easier for kids to tell apart—and we’d avoid having a big crowd of kids running around the book (great for comics, but not ideal for a storybook).

Naturally, the prototype for the girl character was Natalia’s own daughter, Maya—a curly-haired girl with red pigtails who loves bunnies. Over time, the character changed—her hair, color, and age evolved, which is completely normal.

We decided to name the girl Christine!

Then came the pie chart character. In the data viz community, the pie chart is often viewed with skepticism due to its limitations and how easily it can be misused. It’s unfortunate, because people do love the bright, round pie chart—it’s just part of reality. The trick is learning to use it well.

Our first diagram character was a pie chart, and we called him Piechi. Since pie charts need careful handling, Natalia imagined Piechi as a kind of dog that needs to be trained—not to overeat!

Everyone who learned about the book instantly loved Piechi. He became the mascot of the story and our favorite character—just like pie charts: lovable, though not always easy to manage.

Later, we started developing the Dad character, bits of the plot, and other chart-characters.
We tried several versions of the Dad—he’s a tired, somewhat sad data professional. But (spoiler!) this is so he can become joyful again by the end of the story.

At this early stage, the other chart characters were still not fully formed. But we did keep some early sketches of them too.

The plot

So, you have an idea who this book is about—but what actually happens in it?

We decided to go with a plot as old as time: a girl travels into a mysterious world of data to rescue her father, who’s gone missing within it!

Alex worked on the twists and turns of the plot, inventing obstacles and adventures, vividly describing the challenges on Christine’s path to save her dad. He also dreamed up the mysterious chart characters who not only help Christine on her journey but teach her how to use each chart properly!

Each chart has its own personality and unique “diet.” They’ll share those secrets in the book, too!

Christine bravely journeys toward her goal—a mysterious Data Tower always shimmering on the distant horizon—accompanied by her loyal chart friends, overcoming tricky challenges to discover what happened to her father and to rescue him!

Illustrations

Of course, making a book isn’t easy. We started with the plot and text. We outlined the key story points and structure. Afterwhich, Natalia did a storyboard while Alex finished writing all the text. That’s how we finally understood the storyline, the placement and meaning of illustrations, and completed the manuscript.

Then came the time to draw!

Natalia can draw, but mainly in small formats. She didn’t have experience with book illustration, and creating book artwork takes a lot of time—especially while working and raising a small child. It became clear we wouldn’t finish the illustrations in a year… or even two. So we decided to look for help and find ourselves a wonderful illustrator!

This too was a challenge—we needed a style both authors liked, someone with experience in children’s books, available time, and ideally some familiarity with data visualization.

All the illustrators were incredibly talented, though we couldn’t work with everyone. But it was amazing to see different takes on our characters—Piechi in particular got a lot of interpretations!

We tried out a few spreads with different illustrators before finally choosing Anastasiya Lykova as our lead illustrator. She has a young child herself, so the story resonated with her—and we loved her soft and expressive illustration style.

We didn’t want the book to be just a story—we wanted it to be useful too. So we included a chart chooser, and pages with profiles on each chart-character at the end of the book.

What’s next?

To start telling the world about the book, we put together a website introducing the story and its characters—the charts! Now this website has grown into a full-fledged data project for kids: Data2Kids! It includes a children’s competition, educational materials, merch, and of course, this book.

We even want to bring together a local community of data-parents and try out this format all together!

And we wanted to create more opportunities for shared activities between children and parents.

We decided to make a little workbook for kids: with fun, simple data visualization tasks, drawing prompts, unusual challenges, and ways to spend time together collecting data and making charts. The workbook is currently in development, and we’re testing the first version with our local community!

With the book finally published and a growing local community of parents and children learning data visualization alongside the book’s characters, we’re excited to launch an international children’s data-visualization competition—Data Kids!

Dates will be announced soon—meanwhile, you can already explore examples of children’s data-viz projects and educational practices from our local contest and subscribe to the project’s newsletter! 

We’d be happy to see you there! And we really hope to run more data-visualization activities for kids this spring! We also decided to create a themed workbook where the book’s characters will help children practice creating and using charts.

If you’re interested in the Data2Kids project, and want to help introduce kids to the world of data and dataviz, check our book Christine and the Magic Charts!

Thanks for reading!

We hope that, like us, you want to pass on the magic of this unusual but fascinating profession to the next generation!

The post Christine and the Magic Charts: A Data Visualization Book for Kids appeared first on Nightingale.

For much of the twentieth century, photography was a paper-based medium, yet little research has explored how photographic papers influenced the art. Accessing and analyzing historical paper samples have been a challenge—until now.

The Lens Media Lab has cataloged more than 7,200 paper samples—dates ranging from 1890 – 2010—documenting their material, technical, and visual characteristics. This dataset, the most comprehensive of its kind, is now publicly available, offering an unprecedented resource for researchers, conservators, and photography historians.

To describe plainly, Paperbase is an incredible project about photography and its technical side—paper.

According to Paul Messier, Director of the Lens Media Lab, the paper collection “preserves the experience of a physical photograph” and through Paperbase “this experience is contextualized and made universally accessible.”

You can approach it as an analyst, dissecting the data, or as a photography enthusiast, admiring the masters of the past, or as a publisher.

As someone passionate about data visualization, what fascinated me most was the interactive tool built for this project. It’s incredibly flexible—one moment you’re looking at a map, the next you’re working with bar charts, then diving deeper into clusters or radar charts. 

“Collections viewers typically constrain your view to a narrow window. This is fine if you’re only interested in a small part of the collection, but if you want to see patterns at the collection level, you need to be able to see at that level. Paperbase was designed with this in mind.”

And through it all, you’re still surrounded by an overwhelming number of data points—every detail remains visible!

A closer look at the project

Look at these golden highlights on a deep brown background—reminiscent of antique furniture or old ornaments. They pull us into the past, revealing old photographs, inviting us to study the faces of those who lived before us. But they also ask us to explore the technical side—what kind of paper is this? What’s the thickness, texture, gloss, and whiteness?

Then, suddenly, all of it comes alive. A dataset that once seemed purely physical becomes interactive, shifting perspectives and taking on new forms. A powerful tool at the cutting edge of computational analysis.

You start with a chart, some bars, and dots—then suddenly, from those samples, faces from the past smile back at you. It’s magic.

Visual exploration of photographic history using data

Not every sample is an actual photograph—some are technical sheets or even stacks of blank photo paper. You can filter the dataset based on that too, turning each point or cube into a time capsule of an era.

For me, the most fascinating part was studying the historical trends. You can instantly see which decades favored certain types of photographic prints. The rapid rise of photography in the mid-1930s, its peak around 1950, and the gradual decline by the 1990s—it’s all there in the data.

Of course, this could reflect the specific collection methods rather than global trends, but it’s likely that this dataset also mirrors the overall history of photography, at least in the U.S.

Here’s the radar chart system—each element on the map can be visualized with a small glyph, a symbol encoding its characteristics. This adds another layer of texture to an already complex visualization.

A few clicks, and bars and squares transform into fascinating radar glyphs. Each object gets its unique symbol, allowing researchers to highlight and compare different samples up close.

Here are the parameters embedded in these radar glyphs (probably more useful to a photographic paper expert than a data viz enthusiast like me):

• Thickness
• Color
• Gloss
• Texture

When you analyze gloss dynamics over time, the chart suddenly becomes color-coded, revealing yet another layer of insights.

For serious researchers, the dataset allows filtering, analyzing, and downloading the exact data they need for further study.

On the project’s website, you’ll find a few key numbers that help grasp the sheer scale of this archive.

Another aspect I loved? The team’s storytelling about their journey of collecting, classifying, and visualizing this data. If you think this process was simple, just check out the algorithm breakdown on the homepage.

At one point, the workflow splits into two paths—it turns out evaluating stacks of paper versus photo book samples is an entirely different challenge.

Beyond diagrams and algorithms, you can read the history of the collection itself—a story filled with dedication, loss, and 25 years of continuous work.

Data insights based on the Paperbase project

The website also features analytical insights, prepared for curious visitors—like a chart showcasing the increasing whiteness of photo prints over time. Ever wondered why old photos appear more yellow? No, they haven’t aged that way. Chances are early paper production used different whitening agents, reflecting changes in manufacturing technology.

The visual style of this analysis differs from the project’s own, but it’s fascinating to see how different people approached the same data.

A few video tutorials will help you navigate the tool, spot intriguing trends, and discover unique patterns in the data. And beyond that—it’s simply stunning to look at. Highly recommended!

In the publications section, you’ll find a vast list of studies and research articles about this project. Perhaps your name could be among them one day?

I may not be able to fully appreciate the technical intricacies of photographic paper thickness and whiteness, but I can lose myself in admiring historical photos from past decades.

Step into history with Paperbase!

The post Paperbase: A Window into Photographic Paper History appeared first on Nightingale.

It was clear to me that Data Art could be approached from several angles: it could provide more creative practice for data-minded people, while also offering insight into working with data and tools for those in the art world. And pondering about these two opposing camps with different motives and skills kept me going in circles.

And one day, simply inspired by an article about the Data Garden community—where women learn to program with a focus on creating simple data art—I just posted in my channel and invited people to come together and start creating something based on data.

Surprisingly, several dozen people showed up, and I didn’t even have a plan. Some came from the data visualization field, others from illustration. So, after thinking for a few days, I started methodically posting materials on the theory and practice of data art, starting with the simplest exercises.

One of the training projects I decided to start with was creating a portrait of this small community—so-called data badges. They are quite popular in the data visualization field, often made at conferences, data visualization events, or communities.

The inspiration for this direction was probably the wonderful Giorgia Lupi and her well-known project Data Portraits (2017), but the roots of this idea may go back even further. Giorgia briefly describes this project as follows:

“For the Target space at TED 2017 in Vancouver, we developed and created unique visual portraits of participants: visual designs based on responses to simple but memorable questions, which we turned into wearable buttons to stimulate communication and connections throughout the five-day event.”

After the formation of the Data Visualization Society in 2018, they also introduced their own DVS Badges in 2019, which encoded the skills of the community members. There is an article about them on the old Medium account of Nightingale, and Amy Cesal writes about this initiative as follows:

“Every organization needs a logo. For a group of people specializing in data visualization, the logo for the society should reflect this passion.”

They were also inspired by Neil Richard’s badge project (2018), and Giorgia Lupi’s talking bouquets (2018), which used the concept of a group of elements encoding data of members of a certain group in a beautiful and unique way.

One of the recent projects by Kimley Scott also impressed me—it describes the community of MomsWhoViz, elegantly encoding data about them and creating round badges.

Deciding to do something similar, I started with copying and decided to replicate Kimley’s project for my local motherhood community. I slightly changed the questions, posted a Google form, and made the project in the same style, tweaking some elements. I used the same color palette as I’m not very confident with colors.

Working on the project was very interesting, and the girls in the community liked it. But it seemed to me that it was not entirely unique, but rather a copy of Kimley’s beautiful project. I wanted to try something more unique, so I decided to draw badges for the D&D community that I am a part of with friends. I collected the data but didn’t make any progress after that.

And here comes a wonderful opportunity—my newly acquired group of data art enthusiasts, where we can finally discuss interesting data arts, ask for advice, and share work in progress. So, for practice, I suggested to the guys to also take a small test on their skills and based on the resulting dataset, try to create data badges!

I wrote and drew simple lessons and tips to start immersing in data art with recommendations, showed examples, and suggested trying different options. I started sketching to show how to get started: I talked about the peculiarities of sketching, recommended drawing quickly and roughly to avoid getting into details!

At first, the community was not very active, members were observing each other, and the first sketches began to appear, but only two participants with an illustrator background were actively involved. People with data backgrounds remained silent for the time being.

The ideas were very interesting, but they didn’t progress any further. I even created my own small project, but the engagement in participation was low. So, I decided to find out more about the people who had gathered in my community. I looked into the closed section of the survey to see what they were expecting from the community and what experience they had, as well as any common groups and interests we shared. Then I talked to each person individually to learn what resonated with them and what they thought about such activities.

It turned out that many people couldn’t draw, some were inclined towards crafts only, some were good at working with data, code, or just data visualization. Some were interested in one topic, while others were interested in different ones. Some had quite unique hobbies and skills. Of course, I immediately started thinking about what interesting projects could be done or proposed to these people. After the conversations, I gained more ideas and understanding, and the guys became more involved. Many started sharing their projects and studying materials.

Natasha Tyulpanova created a beautiful version and experimented with several legends and types of symbols. It is incredible that she encoded the same simple data with the height of the function, the number of characters, the size and color! I do not even know which of these encodings I like more! The diamonds are great, and the graphics are very original!

Ulyana encrypted the names of the community members into the stems of the flowers—it’s not even immediately noticeable! A wonderful idea!

It’s especially great that everyone used different techniques and different shapes! Look at these adorable bugs made by Alla!

So in the end, I managed to gather a total of eight completed projects. Nadia Andrianova also actively participated, with whom we have already conducted several live streams on data art.

Nadia Andrianova has made a wonderful geometric project based on Euclidean geometry! And to make a tribute to the famous version of Oliver Byrne in narrow circles. Wow! 

Now we have several more topics on the agenda:
• Friends
• Crafts
• Data encryption based on illustrations and patterns
• DVS Contest
• Favorite books
• Data art projects for charitable foundations on topics that concern us…

I hope everyone will find an interesting topic to work on. Because data art is truly a magical discipline—where you can combine any of your skills with any interesting (important) topics and create a unique project!

In such a creative company, my projects also started to progress faster—because I shared some life hacks, talked about tools, invited guests to live streams if the topic interested them. Surprisingly, my D&D project was quickly completed, and I even received help in understanding color balance (which I’m not very good at despite many years in the field of data visualization).

It’s always nice to share your work in progress, receive feedback and support, and maybe even some advice! In the beginning of the journey, criticism only hinders, but support and motivation are much needed! Yet, the advice of experienced designers often comes in handy.

Since then, the community has grown threefold, and I’m glad to have been able to gather such interesting people passionate about creativity and data in one place! Each of them brings something incredible, sharing knowledge, lessons, and ideas.

I’m very happy to have created such a small and cozy data art corner!

Thank you for reading!

Webpage of the Flowers&Numbers Community: https://eolay.tilda.ws/flowersnumbers/en 

If you’re generally interested in the field of data art, I recommend checking out this telegram channel: https://t.me/dataart11

And if you also want to practice a bit with Flowers and Numbers, I invite you to join our small telegram group! https://t.me/dataart_practice 
You can watch live streams on the topic of data art here: https://www.youtube.com/@datacomics

The post Flowers and Numbers appeared first on Nightingale.