(All OVA courses are free and published under aCreative Commons Attribution-NonCommercial license, so help us spread the word among friends and colleagues!)

In this article I’d like to go beyond these basics, taking you behind the scenes and explaining my motivations for creating this project.

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The idea for the OVA was planted in late 2012. That October, in collaboration with the Knight Center at the University of Texas, I launched the first journalism Massive Open Online Course (MOOC) in the world. It was titled “Introduction to Infographics and Data Visualization.”

It was a low-budget — better said, no-budget — experiment: I recorded all the videos at home, and there was barely any editing or planning. And yet so many people signed up (2,000 in just a few days) that we had to close registration and open a second edition right away, capped at 5,200 students. After that, I kept offering MOOCs until the COVID pandemic hit.

Tens of thousands of people from more than a hundred countries have participated in at least one of these massive free courses. To this day, wherever I go — to attend a conference, to give a talk or workshop — I’m approached by at least one person who started their career in visualization, information design, or other data-related fields thanks to these MOOCs.

As someone who considers himself first and foremost an educator and popularizer, I can tell you that there are few things in life that feel better than that. I won’t name them here; let your imagination fly.

The idea for the OVA reached maturity in 2023, when I was giving the last touches to The Art of Insight, a book of interviews with designers I admire. While talking to them, I kept asking myself: I’m learning so much in this conversation — wouldn’t it be wonderful to have all these people, and many more, design courses about the topics we’re discussing, and publish them for free on some kind of open, collaborative platform?

Therefore, the seed for the OVA was my old MOOCs, and it germinated thanks to my latest book. Also to the fact that I could “water” the seed: as a Knight Chair, I have a personal annual budget I can use to fund initiatives I believe will be societally beneficial. The OVA will be my main project in years to come, along with a fifth book.

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If you watch any of the courses already available in the OVA, you’ll probably notice that they look pretty different to what you can find in, say, Coursera or edX.

OVA courses are (deliberately) scrappier, chattier, and sometimes even contain a bit of rambling. All that is by design. Whenever I talk to a new instructor I give them the following recommendations:

Keep it professional, but not too professional. I don’t want a sanitized, perfectly polished production. I want a certain and limited amount of imperfection — the kind that signals a real human being on the other side of the screen. In the very first video of my own OVA course I say that I profoundly dislike strictly scripted, TED-like canned presentations. I find them soporific.

Keep it rigorous, but also personal. I ask every collaborator not to be objective. I don’t want view-from-nowhere courses. I’m not interested in, say, a generic ‘Accessibility in Data Visualization’ class; what I do want is Frank Elavsky’s personal take on ‘Accessibility in Visualization’ (yes, that’s already available in the OVA). I want our courses to be accurate and rigorous, but also to reflect the convictions, personalities, and quirks of their creators.

There’s already plenty of content out there that looks and sounds like it was extruded by probabilistic automatons such as ChatGPT or Claude. I want the very opposite of that.

Make students aware that they are about to become part of an expanding community of friends, which they ought to nurture. At the beginning of my OVA course I explain that I want viewers to feel like they’re sitting with me in my favorite corner at home, surrounded by my tabletop games and my books, sharing a few hours of learning and joy.

I’d like OVA viewers to feel like I felt at the beginning of my career, when my mentors at the newspaper that hired me as an intern, La Voz de Galicia, taught me our craft while letting me watch over their shoulders. Theirs was a rare form of high kindness.

The OVA is my way of honoring those early mentors, and many more that I had the luck to cross paths with throughout the past three decades. As I’ve said in recent talks, if you know that you’ve benefitted from other people’s generosity (and who hasn’t?), eventually you must strive to emulate that behavior.

Convey an ethos. In a recent talk at MIT I explained that I’ve come to believe that what I teach — both at the University of Miami and elsewhere — isn’t just a series of principles or techniques, but a way of being and acting in the world.

That’s how I’ve always understood journalism and visualization design: yes, they are professions, yes, they are knowledge domains with their own methods, heuristics, conventions, inherited practices and so on and so forth. However, to me, they are more than that: journalism and design are ways of looking at reality, while we navigate it together. They are also peculiar ways of being a human being.

I wish the OVA will carry that spirit — not just to teach people how to design data graphics, but to invite them into a particular way of seeing.

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What’s next? We’re planning to release roughly one new course per month; we have nearly a dozen in the works, covering a large variety of topics.

And yet I’m convinced that we’re barely scratching the surface; if you think that you have a brilliant idea for a course, let us know. We’ll need just a title, a description (not more than 2 paragraphs!), a table of contents, and a couple of sample videos to see how well you present to a virtual audience.

If we like your idea, I’ll pay you to bring it to life, and will welcome you to the growing OVA community.

I assure you that it’s a great place to be.

The post The Collaborative Blueprint: The Open Visualization Academy as a Community of Learning and Friendship appeared first on Nightingale.

Early influences

Joe and Paul met while in university. With a background in motion graphics, Joe has always kept an eye out for how a story evolves, frame-by-frame. Paul has a more classic graphic design background: his emphasis is information design and creating clarity for the user through in-depth understanding of his audiences. 

The two worked independently for a few years, and they joined forces to create Applied Works in 2005. Over the years, the studio has remained relatively small and has shifted focus multiple times to stay relevant in a changing landscape. Now, with 15 people, they’re on a growth path.  

Through their projects and clients, Applied Works has had unprecedented opportunities to witness the growth and transformation of an industry over time. From their early days working in moving image, branding, and websites, they had front row seats through the dot com bubble and learned how to code on the job. They ran tests on prototype devices like early satellite communications and the first iPad, and collaborated on many high-profile data vis projects, with the BBC, the Times in London, the London 2012 Olympic and Paralympic Games, and others.

As web technologies advanced, they upgraded their methods to support live data feeds, establishing style and component systems for code reuse. They also experimented with 3D maps for the 2014 Tour de France and advanced image filters for a Black Mirror project in 2018. Their Class Calculator project for the BBC became the broadcaster’s most-shared data tool in 2013. Lately, they have pivoted toward climate and environmental work with nonprofit partners — as well as projects tackling societal issues and inequality — collaborating with philanthropists, intergovernmental agencies, and think tanks to help them communicate complex data and nuanced narratives. They are also expanding their skills into data science and machine learning. 

Themes

The team relies on several “north star” behaviors to guide their exploration, helping to chart a course over complicated and changing terrain. Throughout our conversation, a few strong themes stood out.

Push the boundaries

In design school, Paul observed that the coursework was very structured and quite strict, but the most successful students were often the ones who did their own thing. To develop your own perspective, he realized early on that you need to push the edges to test who you are and find out what you think. Your initial instincts might be wrong, but that’s how you learn. This principle continues to shape how the studio approaches its work. An exploratory mindset and keen appetite for learning helps to feed their creativity and ideas.

Experiment to find out

In our influencer age, it’s worth emphasizing that success is not just about broadcasting your ideas and opinions and hoping that someone else follows along. You also need to test and refine those ideas based on feedback from the world. 

Experimentation and prototyping are a key part of the process at Applied Works. In order to find the limits, you need to push an idea as far as it will go, and then just a little bit further. When it starts to fail, you can pull back and find the place where it works. This process of tuning their approach through experiment, feedback, and course correction has been a consistent theme for Joe and Paul throughout their design practice.

Follow the creative tension

In addition to doing your own thing, you need to find something to push against and someone to negotiate with. Joe and Paul bring different contributions and viewpoints to their collaboration, producing a natural creative tension that drives their approach. 

Joe has a more technical bent. He often starts by analysing complex datasets to propose a narrative, and then they iterate together until it makes sense from both a user and a technical perspective. This collaboration allows the pair to use each other to get to a better solution than either would have achieved alone.

Creative tension also forms the foundation of client engagements. Clients bring new and interesting problems and constraints, and together the group negotiates a new set of solutions to meet those needs. They start by asking challenging questions to get the team thinking, and then they get deeply involved with a client problem and the data, understanding as much as they can about the science of what the client is doing. This process helps them identify the underlying need, and the solutions emerge from that. 

When designing a call center dashboard for Genesys, the team identified a fundamental relationship in the way the key performance metrics are presented. They transformed the data into a user-friendly dashboard build around just three key insights, streamlining the display to allow users to monitor and address issues in real time. This approach later became a foundation for how Genesys designs its products.

Have a perspective

Over time, the team’s projects and creative experiments added up to experience, creating a sense of identity that is both unique to the studio and informed by the external world. This gives them the confidence to stand their ground when needed, which sometimes means forging an alternate path. 

One of their biggest breaks as a studio came in 2010, when the iPad first came out. At the time, most of the industry was using Adobe Flash for infographics. For accessibility reasons, Applied Works had resisted using Flash in favour of HTML5 and CSS. When the Times got a pre-release version of the first iPad, their existing projects worked natively where many others did not.

By following their own inner guidance rather than an industry fad, Applied Works was positioned to take advantage of a major opportunity when the technology changed. The team was quick to point out that it doesn’t always work out this well, but independent thinking sometimes pays off in unexpected ways.

New technologies

Over and over again, Paul and Joe’s experimental approach positioned them to embrace new technologies as they emerged. They are often approached by people who want something done and aren’t quite sure yet what it is. Starting from an unformed idea, they work collaboratively to shape and co-define the work, and that often leads to new and innovative projects that they might not otherwise have created. 

Although the team has often been among the first to embrace a new technology, they work hard not to be defined (or confined) by it. Technologies are a medium or a tool that they use to achieve better results for their clients, but the process often starts on paper, outside of the constraints and limitations of a screen. 

Instead, the team comes back to core design principles to guide their work. Usability has always been central to what the team does. The term has changed over time, from accessibility and user centered design to usability, human centered design, and now inclusive design. It’s similar for data visualization: the team sees it both as a practice and a tool that’s best applied to a problem, and not necessarily the skill that defines an artist in its own right.

Regardless of terms or technology, the quality standards remain the same: is the design easy to use? Interesting? Intuitive? Coming back to Joe’s background in motion graphics, does the sequence and hierarchy of information over time make sense? Everybody learns differently, and the team focuses on using a mix of technologies and skills to facilitate core use cases and needs. A recent article on a project about trade flow for Chatham House shows how all of these different pieces work together. 

Embracing change

Across all of the team’s experiences, there is a strong pattern of learning and embracing change. Where there are no precedents, Joe and Paul see opportunities. Learning alongside their clients makes experimenting and trying new approaches a more collaborative way of introducing fresh perspectives.

Applied Work’s content focus has changed over time, shifting with their interests and the industry. Starting out with websites, corporate work and data journalism, they transitioned into data products and design systems as those opportunities emerged. They are now refining their focus again, focusing on enlarging their scope and creating a better future for the planet. 

The team’s process has also changed over the years. In the beginning, they worked mostly from creative briefs. As their experience and expertise grew, they moved into more open-ended engagements based on client trust. Paul likened it to going on a journey together: the ideal situation is when a client has an open-ended idea, and they can sit down and work out how to approach it together. 

They’ve also been working to make their work more scalable, developing a process and a system to support a larger, more distributed team. They’re deliberately creating more opportunities for R&D and making space to explore their personal interests and curiosities to keep the team engaged. Joe in particular is interested to see what happens if they let technology lead the way a bit more, to help them invent what could be. In 2017, the team got the chance to work on chapter artwork for a book about the Netflix series Black Mirror. Taking inspiration from the anthology’s dystopian themes of losing control of technology, the team used creative coding to generate imagery of each episode, relinquishing a certain level of control over the visual aesthetic. 

Looking back

Applied Work’s 20th anniversary has been an opportunity to pause and make sense of the journey the team has taken over the years. This kind of progress usually doesn’t follow a linear path. You can’t draw these connections with a ruler: you can only look back and connect the dots after the fact. The guiding principles above helped the team to navigate the shifting terrain, and to find their way. 

Joe and Paul created a successful studio built around care for their people and their team, their clients and affected audience, and the legacy that they leave behind in the world. They negotiated an ever-changing landscape by optimizing at each point in the process, following their principles and intuition to find the best path.  

Imagining the future

Looking forward, the Applied Works team is excited to help their clients navigate a world that is subject to ever-increasing change. They are interested in partnering with climate and environmentally-minded non-profits, data scientists and academic partners to understand and share their impact, communicate their mission, and design their approach to funding and future research. They hope to go deeper with their clients to articulate the core identity of their organization, to help them see further and ensure the continued success of their work.  

Especially in the area of climate awareness, some of the team’s major clients are already thinking far into the future, asking questions like: “if we do our job properly, in 10 years we won’t need to exist in our current form. What should we do next?” Paul and Joe would like to help them to answer that question. They are also positioned to help facilitate new connections between their clients, creating an exchange of ideas that could lead to more collaborative and impactful work. 

Of course, Applied Works will continue leveraging technology to solve problems and experimenting to push beyond the current limits. They’re excited to shape our technical evolution beyond the screen into a more immersive and experiential virtual environment. Joe recently completed a MSc in geographic data science to expand his skillset for an AI-enabled world. The team is also ready to engage with the many new creative tensions introduced by AI: questions of bias and ethics, where and how we should use AI methods, and the many conversations about profitability and exploitation that this new technology poses. 

Overall, Joe and Paul are looking to help lead the push toward ethical, sustainable progress, both globally and for design. With two decades of experience navigating complex landscapes, they are well-positioned to “work together with clients to take each other into the future.” It will be interesting to see where they go next. 

Get in touch if you are interested in working with Applied Works, or subscribe to Rows and Columns to get updates on what’s happening with the team. They are also accepting applications to their Springboard program to solve big, global problems until Dec 17, 2025.

For more information about the team’s projects and history, see their recent anniversary post on LinkedIn.

The post Mapping Change: How One Design Studio Navigated 20 Years at the Forefront of a Changing Industry appeared first on Nightingale.

“LA on the Move”, our exhibition organized by Metro Art at Union Station in Los Angeles, California, opened in October and will remain on view through next year. Through larger-than-life graphics, a massive 3D map, playful character designs, and even animal sounds, we’ve created an immersive experience that asks Angelenos to see themselves reflected in the lives of coyotes, mountain lions, monarch butterflies, red-tailed hawks, and california kingsnakes.

From City Animals to Union Station

The seeds of “LA on the Move” were planted at ArtCenter College of Design, where we first encountered the City Animals class taught by Santiago Lombeyda and Ivan Cruz. “It was a topic I hadn’t really thought about before,” Jen recalls. “The interaction of humans and animals in LA County—it was super intriguing. The more we got to know the projects and the students, the more excited we became.” Then there was a chance to have an exhibition that pulled together a lot of these concepts and also showcased the student work, created in association with Metro Arts at Union Station. From there it just started rolling”.

The final projects from the City Animals class focused on speculative projects that explored how Angelenos could redesign their homes, backyards, and neighborhoods to better integrate with the natural world. Jason explains, “The projects that the students did were really about how people in LA could think about the intersection of the built environment—their homes, their yards, their backyards—with the natural world”. From there, we led two intensive workshop sessions with the students, working side by side to visualize ecological data in bold, accessible ways that were displayed in the ArtCenter student center for the following month.

From there, we were connected with Arroyos & Foothills Conservancy, a non-profit organization focused on preserving and restoring natural open spaces and wildlife habitats. They became an essential partner, sharing datasets on animal sightings, migration patterns, and habitat corridors across LA County as well as expert advice and access to Southern California’s environmental researchers.

The research process: Data meets daily life

“I think the first thing that we did, and what we always do, is begin with research,” Jen explains. “but in time, we leaned on the expertise of our friends at Arroyos & Foothills Conservancy—they were incredibly helpful. The other part, I think that’s very important, is collecting anecdotal information when you’re talking to people that live in Los Angeles about their experiences”.

For us, stepping away from the data is essential. “It’s important to step away from the facts and the figures, and start talking to people because the experience that Californians have with wildlife is completely different than a New Yorker’s,” Jen says. “You can’t just go about your business like a city dweller and ignore nature in California. It’s integrated into your day-to-day experience”.

Los Angeles, we discovered, is extraordinary in its biodiversity. Jason notes, “Los Angeles has such a unique environment. And what we found is that it’s actually one of the three areas in the world that is considered a biodiversity hotspot“. This became a cornerstone of the exhibition—LA isn’t just a city with some nature on the edges; it’s where wildness lives alongside urbanity in remarkable, sometimes precarious, ways.

Five animals, five stories

We chose to focus the exhibition on five species: coyotes, pumas (mountain lions), red-tailed hawks, california kingsnakes, and monarch butterflies. Each animal became a character in the larger narrative of LA residents navigating neighborhoods, dating scenes, commutes, and survival just like the humans around them.

“One of the first things that you drew was the coyote that says: ‘I love LA.’ That’s one of the featured images in the show,” Jason recalls. For Jen, this illustration became a statement of intent: “A human says, I love LA—and we all know this phrase—but animals live there too. What’s their role in this? So, we wanted to make sure that the animals and humans get equal time in this show”.

The personification of the animals was deliberate and humorous. Jen explains, “The more you learn about animals, how they’re mating with other animals, for instance, you think about the LA dating scene, and then you think about animals, which have some funny crossovers. As we have these neighborhoods in a city, they also have their neighborhoods.” Jason chimes in, “For example, a monarch butterfly says, ‘Hey babe, let’s overwinter in Mexico’—a line that could just as easily come from an Angeleno planning a winter getaway…” Jen adds, “And the monarch is saying like, I’ve got a really busy schedule.” Jason elaborates: “They have this multi-generational migration habit where up to five generations of butterflies will go from Central Mexico all the way up to Nova Scotia and Southern Canada and then back again. And they do this over five different generations. Even more remarkable—five generations later they’ll return to the same tree”.

The California kingsnake became another favorite. “Well, it’s not an LA Dodgers hat. Thank you very much,” Jen jokes, describing the snake’s illustrated headwear. “It’s a Los Angeles hat”. The kingsnake’s ability to live almost anywhere—from woodland to wetlands to suburban basements—made it a perfect symbol of LA’s adaptability. As we say, “you live in my backyard.”

Navigating the hard truths

While humor runs through the exhibition, we didn’t shy away from difficult realities. Rattlesnakes, for instance, posed a design challenge. “I made this drawing. When you might be on a hike, you may encounter a rattlesnake. And this is frightening, right?” Jen recalls. “There was like a discussion about making the rattlesnake so it wasn’t so intimidating, which was funny because I was like, well, a rattlesnake is intimidating and very scary, and you can’t really take animals and smooth out all the rough edges, right? Because that’s not what they are”!

The story of P-22, the famous mountain lion, underscored the fragility of human-wildlife interactions. Jason reflects, “Take the story of P-22—a famous mountain lion that was known around the Mount Wilson Observatory. And eventually, through a series of interactions with humans (and despite best intentions) he dies”. The exhibition addresses this directly, including data on rat poison’s devastating impact on mountain lions and the importance of hazing techniques—like carrying a can filled with coins—to maintain healthy boundaries.

“Even though we anthropomorphized the animals, we shouldn’t forget the fact that there are negative results of some of our interactions with the animals. We should be mindful of that”.

Making data visible and inviting

One of our core practices is taking complex datasets and transforming them into visuals that invite exploration rather than intimidation. “Part of what we do is find information and basically make it much more understandable to the general public and to ourselves,” Jen explains. “Like rat poison killing pumas, right? We made this diagram so that we have the data there, but you can just see it more clearly”.

A standout piece in the exhibition is the massive chart “Animal Species at Risk in California”, which visualizes 930 species by class and phylum, showing which are extinct, endangered, or imperiled. Working with data visualization collaborator Paul Buffa, we transformed this overwhelming dataset into the shape of a California poppy—the state’s native flower.

“If I saw this information in spreadsheets, I would be very intimidated because it’s just a lot of information,” Jen admits. “But since we put it into this California poppy, which is a native plant, it invites you over to explore it. You don’t have to look at every single detail, but it is fascinating”.

The wall also includes a Sankey diagram comparing California’s at-risk species to global standards—revealing that California has considerably more species in danger. And the bar chart showing imperiled species? “It literally towers over your head. It’s about seven and a half feet tall, so we wanted it to have a physical relation to how you encounter the data”.

The iconic title wall: Observing Union Station

The exhibition’s title wall features three illustrated characters walking across a vibrant gradient backdrop—each carrying something that subtly references animal behavior. Jen describes how these characters emerged: “We were standing in Union Station, and I could see people walking through, going from the trains to the entrance, and it gave me this idea about what kind of people would be walking through LA and walking particularly in Union Station”.

The older gentleman carries a bag of groceries, echoing how animals travel to forage and transport food. The young woman holds a bundle of flowers, referencing seed distribution—how seeds attach to animal coats or are eaten and deposited elsewhere. “All said and done, the more time you spend with the exhibition, you know every element is intentional and thought out and has a relationship to the information that we learn as we go along,” Jen explains.

The massive 3D map: Placing yourself in the data

Perhaps the most captivating element of LA on the Move is the enormous 3D map, created in collaboration with Julian Hoffmann Anton. This wasn’t just a cartographic exercise—it became a months-long process of negotiation, expansion, and refinement.

“Every project we do, we discuss a map component,” Jen says. “And sometimes we have time to do it, and sometimes we don’t because what starts as a simple map becomes very complex. It’s because a map is political. You can’t leave anyone off because they’ll notice”.

Initially, the map focused narrowly on downtown LA and Union Station. But through conversations with Metro Arts staff and community input, it expanded dramatically—eventually encompassing all of LA County and parts of Orange and San Bernardino Counties. “We were pushed and pushed on the map, but that’s not a bad thing. It’s a much more inclusive map, so when visitors come to Union Station, they can find themselves”.

In addition to showing every detail of the city, the map tracks sightings of all five featured species across the region, revealing fascinating patterns. Mountain lion sightings appear surprisingly far south of downtown; California kingsnakes cluster in parks and mountains but occasionally show up near Marina Del Rey; while coyote sightings may reflect research centers as much as actual populations.

“I’ve never seen a map of this scale, physically, of this detail,” Jason marvels. “It’s an extremely detailed 3D rendering of the entire metro area”. And because it wraps around a corner, visitors can find neighborhoods that might have been cropped out of a conventional map. Jen describes a photograph of a man pointing to the side panel: “He’s finding himself, which we wouldn’t have had in our original idea”.

Adding Sound: Activating the Space

For the first time in a Data Vandals project, we incorporated audio. “I pushed for this because we wanted to activate the space as much as possible,” Jen says. “We’re dealing with walls, and we wanted ways to expand these rectangles out”.

Visitors can hear the sounds of pumas, coyotes, and hawks. “I thought, okay, if I’m walking through Union Station, what is it like to hear some of these animals?” Jen explains. The sounds are surprising—sometimes beautiful, sometimes unsettling. Jason describes, “The mountain lion has lots of really low growls, more aggressive than a purr, and I found those to be unsettling”. Coyote calls also sound strange and a bit frightening, but these sound elements ground the exhibition in sensory reality, reminding visitors that these are not cartoons but living, breathing neighbors.

Iconic cutouts and LA signage culture

Atop each wall, we placed large cutouts of the animals lifted high on Sintra board to add height and visual drama. Jason says, “We wanted them to refer to the history of the Hollywood back lot, even the Hollywood sign itself.”

Jen reflects on LA’s distinctive signage culture: “I think the signage is very different from anything you ever really see on the East Coast; in New York we don’t have that kind of sign culture and I find it fascinating and really attractive”.

The billboard aesthetic also responds to Union Station’s architecture—a stunning 1930s Art Deco space with soaring ceilings and intricate tilework. “Union Station is so gorgeous, you want to try to do it justice. Something that iconic, you worry that whatever you do is going to be overwhelmed”. To honor the building, we photographed the tile floors and extracted colors to integrate into our palette, creating a dialogue between the historic architecture and our contemporary street-style graphics.

As the exhibition settles into its year-long run, we hope it becomes a recurring destination; a place where commuters pause for five extra minutes, where families return to discover new details, where Angelenos see their neighborhoods reflected in a 3D landscape populated by shared species.

“I just want people to enjoy it and have fun with it and see themselves in the data,” Jen says. “It’s so fun to see the different types of people, and I feel like I could draw those people and put them into the exhibition. It reflects a lot of our intentions”.

Jason hopes for depth and revisitation: “I’d love that the exhibition is very detailed; you can return to it over and over and learn something new each time that you revisit it”. And Jen adds with a laugh, “I hope it brings us back to California again and again –  we love LA “!

“LA on the Move” is on view at Union Station through 2026.

For more information: https://datavandals.com/la-on-the-move.

The post LA on the Move: Data Vandals Bring Wildlife and Humans Together at Union Station appeared first on Nightingale.

As a former organiser of UX Camp Hamburg—an annual UX bar camp—and now of the DataViz Meetup Hamburg, one of the many things I am curious about is: can I use data visualisation as a tool to foster community and exchange? Thus, I took the opportunity to give a workshop at the above mentioned bar camp. To create a together-datavis about the interests of the participants over time. In a slot of 45 minutes only. To see what happens. To make people talk and think.

Understanding the challenge

I sketched it for myself first. Defined colours for interests, made a timeline on an x-axis, thought about specific moments that helped me remember what I was into at that time and drew that onto the y-axis. An easy exercise.

But how should this work out with more people? How many colours would we need? How can we draw it into one chart? All at once? How many participants would there even be? How many different interests would they have? How old would they be? I was swaying between “forget it, that is going to be too complex” and “let’s find out”.

So, I tried. I organised my process and wrote down a prompt to identify what data types there would be: “Which topics were you interested in at a certain moment of your life?” Hence, I needed to find a visualisation that presents data by different people, development over time and interests grouped into categories. How many manifestations these data types would have, I would know for sure only then, in the workshop.

Finding a visual idea

I skimmed through datavizproject.com and sketched ideas. I was searching for a flexible type of visualisation that everyone could draw at the same time. Everything showing data by area size dropped out. We would have needed to calculate it beforehand. The data should be collected while drawing. Besides, I decided to show time spans instead of a whole timeline for each participant, to simplify the process and address the problem that there would be people of all sorts of ages.

I checked out charts with distinct symbols as Column Sparklines. They turned out to be not flexible enough. Bee Swarm Plots. Too much chaos. Just bar charts out of different coloured lines stacked upon each other. How long would that take until everyone got hold of a pen in a particular colour? A heatmap would be cool with squares of transparent paper we could layer! “But who would buy so much paper and cut all the squares?” I was asking myself.

In search of different inspiration, I took Visualising Complexity (by Darjan Hil and Nicole Lachenmeier) with me to the playground. Instead of looking into it, I bathed it in the contents of my water bottle. This book being all wet, Dear Data (by Stefanie Posavec and Giorgia Lupi) became my bedtime reading. And there it was. Giorgia Lupi’s “Phone addiction” visualisation: different circles spread over the postcard, surrounded by the data points.

Each participant could work on their own “circle”. The “circles” would hold different symbols embodying different interests. And the circles wouldn’t be circles, but forms depending on the decades the participant has already spent on earth. They will be spread over a canvas. This way, everyone would be able to work on their own datavis at the same time. We wouldn’t need different colours.

Planning the details

I sketched the idea. Planned the structure of the workshop. Squeezing everything into 45 minutes. Drew the legend beforehand. Made an analogue presentation to be independent from technical restrictions at the venue. I collected the material and bought paper on a huge roll. One thing I learned from previous workshops: better bring your own material and be prepared for any local conditions. Since I found pens in grey and blue, I came up with another piece of information to add to the drawing: symbols for interests that are still relevant today would be blue, while all others would be grey.

My plan: Give an introduction and explain the data visualisation we are going to build. Collect interests together and cluster them into categories. Assign a symbol to each category. Give the participants some time to sketch their own part. At the same time, pre-draw the bigger forms according to the different ages. Put everything together.

What happened?

We ended up in the canteen. There we had a big table to draw on, and no space to stick post-its to. So, the collection of interests and clustering took quite some time. We had to use the windows. The final drawing worked out quite well. At least with the participants not heading off for lunch. The benefit of being so present in public: everyone else could take a look at our emerging drawing.

All in all, I gained the experience that producing a data visualisation with more people at once can work out—if one defines everything beforehand. It is still usable for self-reflection and talking then. Probably more than any dot voting. However, I don’t think participants can learn much about data visualisation, and they sadly cannot become creative on their own. Still, I hope that with a bit more time and in a calmer setting, we will achieve even better results. What’s your take on this? Have you ever tried anything similar? I am still curious.

The post Datavis as a Community Experience: How to (Not) Create a Datavis in a Group appeared first on Nightingale.

1. Having four authors does not mean the book gets written four times as fast

Throughout our conversation, the topic of the sheer size of the author team came up a number of times. I asked explicitly about their experience working together because much of the book sounded like a single voice, not four. In response, Amanda said:

“You mentioned the kind of unified language, that it actually reads like a book that’s not written by four different people, despite having different authors on chapters. I think that took a lot of honing. I think we learned in the initial drafting process and my drafting content for Part I, that I write in very verbose prose that I really appreciate reading, but my co-authors are much more adept at writing for more business audiences. And so, that’s one of the reasons Andy and I collaborated on the first part, was him working with me on taking some of the big ideas and long sentences and helping to make sure that the content was accessible for folks who are reading the book and who might be skimming through it or looking for insights in bits.”

2. Disagreement is healthy, and sometimes it’s important to show it

With four authors, disagreement is inevitable. I asked the authors about how they handled those disagreements behind the scenes, and how they decided to put some of them on the page. Andy talked about how debates during the making of The Big Book of Dashboards (authored by Andy, Jeffrey, and Steve) resulted in them starting Chart Chat, to which they later invited Amanda. That experience helped prepare them for making Dashboards That Deliver, he said:

“There are challenges because you add one more person to the group, but that actually creates many more vertexes of disagreement and logistics. So it was a challenge, but you know, like in the first book, you end up with a better product, because even before anything gets to Wiley or a copy editor, it’s already gone through a painful process with the other three authors. So, even though it might have been difficult, we were always working to improve the end product. So, a challenging but fruitful process.”

Jeffrey also talked about how working together on previous projects helped him and his co-authors navigate disagreements:

“I think this would have been a lot harder had we come together, not working together, right? We worked together for years: Steve and Andy on the first book, and then Amanda on Chart Chat for, you know, years and years and years. So we work together on a regular basis. I know them, I trust them, you know? I respect them and their work. I think that really helps, especially when you get into a disagreement or something that’s really difficult.”

Steve mentioned how he appreciated the fresh perspectives his authors brought to the table, even when they were different from his:

“It’s good to have someone else reading the stuff that someone else has written, you know? Because, gee, this stuff’s so clear to me! I don’t need a figure here, I don’t need an illustration, I don’t need a call-out to accentuate the most important point, because I’m living and breathing it and thinking about it 24/7. Someone else reading it goes, ‘this isn’t clear, wait a minute, I don’t know what you’re talking about.’”

3. Authors really do think about how readers will use their book

I’ve always been told “think about your audience!” when taking writing courses, but was curious whether that was something real authors actually did when writing their books. Well, the authors of Dashboards That Deliver certainly did! Amanda talked about how the book is designed to be read in multiple ways:

“I think one of the best parts of the book is you can sit down and read it cover to cover if you want to, or you can pick and choose and read pieces of it. I hope it becomes a reference book that people have that, when they’re doing dashboard design work and they’re getting to their kind of prototyping and kind of layout design pieces, they can pop open the book and open that chapter and be reminded of some ideas. Or they’re looking for an example of a really great dashboard around financial data, and they can go pop open the big banking dashboard scenario. And so, I think that that was a big part of getting to a really accessible book—which we hope it is for a lot of people across different levels—to make sure that it reads as an accessible book and has lots of good examples, and can be read modularly or cover to cover.”

Andy pointed out how the framework for designing dashboards described throughout Part I of the book can be used for many applications outside of dashboards:

“I think the framework that Amanda’s come up with, and that we’ve obviously worked through the whole front section of the book, is focused on dashboards, but it is a data application design framework, right? You know, that framework took inspiration from Design Double Diamond, from Agile, from user-centered design, you know? Those are paradigms that are not dashboard-specific. So when you get into things like user stories and wireframing and prototyping, you’re just in application design. So we’ve framed it within a dashboard world, but, you know, that framework is applicable to anybody who’s trying to take data and to produce something that other people are going to use with data. This is a book for them.”

4. Even 500 pages can’t capture everything

I asked the authors about what was left on the cutting room floor when Dashboards That Deliver was finalized. Could there really be more than the nearly 500-page book? Turns out, there could be much more, but they didn’t feel having a thicker book was the most productive course of action. Steve reflected on their tool-agnostic approach to the book:

“The book is already fairly thick. And if we had something about, ‘and here’s how you make all these things in each of these tools,’ it would be 10,000 pages long. So, it’s wonderful for people who teach Tableau, people who teach PowerBI, because it will create this need for, ‘oh, you need to be adept in your tool? Here are these people who are great at it, and they’ll teach you, and they’ll help you with it.’ So, that’s where the frustration comes from. We’re not going to tell you, step by step, how to build this thing. We make it very clear, we’re not going to tell you how to do that. We can’t—there’s too many tools.”

In a similar vein, there were hundreds of real world projects and scenarios to choose from for the book. Ultimately, only so many could make the final draft and be useful to readers without too much overlap. Jeffrey addressed their process for deciding what stayed in:

“The list was probably twice as long, both on scenarios and real world examples. We had a long, long list of real world, and they just started getting cut. Some of them combined themselves. We said, ‘oh, that might fit with this chapter,’ and kind of moved in and combined. Some of them were written all the way to the 11th hour, and didn’t make it, and got cut, and didn’t make enough sense to have in the book. And some of them we felt like they just, you know, weren’t the right topic, or just didn’t make it.”

After chatting with Andy, Amanda, Jeffrey, and Steve, I have an even greater appreciation for the hard work and dedication it took to create Dashboards That Deliver. Even though I don’t make dashboards often, I definitely see myself referencing the book regularly as I complete other data visualization projects. If you want even more behind the scenes information about Dashboards That Deliver, you can check out the authors’ discussion of some of the book’s inner workings on Chart Chat 57: Under the Cover of Dashboards that Deliver.

Dashboards That Deliver is currently available for preorder and will publish on September 23, 2025.

The post Behind the Scenes: Dashboards That Deliver appeared first on Nightingale.

Stakeholder whispering by Bill Shander is an approachable book about why it’s important to solve the right problem, and how you can make sure that you’re doing it. Having worked with many designers over the years, I can say that stakeholder whispering is the hardest part of the job to get right, and often the most important one. The book offers simple, clear advice on how to make sure you’re getting to the bottom of a situation before diving in with solutions. 

It can be very hard to whisper well. Consequences for failure can be severe, but there aren’t a lot of books that focus on just this one aspect of working with a team. This book offers guidance from an expert whisperer on the small things that might trip a new designer up. Reading it is like shadowing a senior designer at work.

Bill brings the reader along at a level that’s gentle enough for a beginner but also valuable for an expert. Written with empathy and a sense of humor, the book feels like a comfortable conversation over tea with a friend, commiserating and sharing tips with someone who has had all of the same struggles and knows what it’s like. At different times, I found myself laughing out loud, grimacing in recognition, and nodding along. I appreciated how Bill used simple, practical examples to demonstrate his points (usually accompanied by a verbal wink, just to make sure we saw what he did there).

What does this have to do with data vis? Everything, really. Helping people push past “I want this chart” and get to a good outcome is a struggle we all face. This book is for anyone who needs to work with multiple stakeholders to help their projects succeed. (It might also be useful for stakeholders who need to work with designers, so that they can understand why we’re asking all these questions.)

Here are some of the topics addressed in the book.

Common painpoints:

• Pushing back without saying no
• Stakeholders who dictate solutions or don’t care about their stakeholders (especially the hidden ones)
• Knowing how & when to lose the battle
• Breaking a problem down into manageable chunks
• Switching roles as you moving from problem identification into the design process, and remaining flexible in your approach

What you will learn:

• Using neuroscience and cognitive behavioral therapy to understand stakeholder dynamics
• Keeping the focus on the problem, and not making it about you
• Empathy as a tool to enter the client’s frame of mind, without losing your own
• Creating a space for not-knowing: encouraging curiosity, even when people think they know what they need
• How to prepare for a conversation, and how to use what you hear
• The four components of productive listening: focus, attention, interruption-free, and picking up on nonverbal cues 
• Switching between the surface ask and deeper structure when solving a problem
• Listening for holistic understanding, and simplifying without oversimplifying
• Why finding the right problem might not be enough (and what to try next)
• What success looks like
• How to tell whether your stakeholders are open to whispering, and what to do when they’re not

These topics apply everywhere. I think these techniques might matter more for data vis for a few reasons:

• Stakeholders are less likely to understand the details (of the user task, or the solution)
• Other designers may not have the technical experience to follow along 
• Experts may be so frustrated by trying to explain the problem that they won’t even try. When you can use these techniques to demonstrate understanding, you get to the real conversation faster.

As with all experience, the magic happens in knowing how to dance, not in just following the steps. You need to develop a sense of rhythm and an instinct for where these principles apply. That said, experiment. Apply these techniques. They will help.

Question time with Bill!

I had a few questions after reading the book, so I reached out to Bill. He kindly answered them here, to share as part of the review:

This book was focused mainly on what I would call framing the problem: the needs identification step before you get into the design work. Can you talk about why you chose to focus on that part of the process?

The short answer is that I haven’t seen enough people write about or talk about this. It’s the part of the process that is mentioned but rarely explored in detail. In other words, designers (and others) are told they need to do “needs assessment” or “requirements gathering” and “ask questions”, etc. But to me, that’s like saying “make some beef stew” without providing a recipe. Because it’s not so simple. The recipe is the “how”. You need to ask the right questions, in the right way, of the right people, with the right tone, to really figure out what is called for. And that takes either years of hit and miss experience to figure out on your own or you can learn a process and a way of thinking about this that will get you up and running much more quickly. I wanted to provide that to people based on my experience. Oh, and by the way, a key part of all of this is to first just acknowledge the idea that our stakeholders often don’t know what they need. They need our help figuring it out. Once we acknowledge this, we can move on to the “how”.

What do you do when you’re stuck with a stakeholder who can’t be whispered?

As I say in the book, the short answer is that you should find new stakeholders. If your boss, or client, or whoever, won’t engage, then you should find a new boss/client/whoever. Honestly. Life is much more fulfilling when you’re working with people who respect you and engage with you as a thought partner. That being said, there are some techniques to help soften an intransigent stakeholder. For instance, start small. Just ask ONE key question, like “how will we measure success”, which is a very informative question to help you understand true needs pretty quickly. For instance, if your boss says “make a dashboard of our HR data”, but the measure of success is “employee retention goes up”, then you know retention is a key part of that HR data that needs to be the focus, and maybe it will lead to follow-up questions about how that data might help with retention, what other data might affect it, etc. Part of starting small is realizing you have to gain trust to engage with reticent stakeholders, so a short focused meeting with incisive questions will earn you longer and more complete conversations over time.

Designers are often very good at listening, but struggle when it’s time to transition from a position of understanding to become the expert presenting solutions. It can be hard to be seen as an expert when you’re in the role of listener and learner (especially working with an experienced team). Can you talk about ways to avoid this trap?

Expertise is an incredibly valuable thing. If you are new in your career, you may not be perceived as the expert, which makes things harder. But the great news is that you can lean on others’ expertise. Rather than saying to your stakeholders something like “pie charts suck!”, you can say, “we know from research on human visual perception that humans aren’t very good at distinct value comparisons when looking at circular shapes, so a pie chart won’t be as effective for this visual because you really want your audience to compare those two numbers – research also shows that a bar chart will be much more effective here, so I’d recommend that.” When you cite research, that glow of expertise will shine on you and you will gain trust. As you gain more and more trust, you will eventually be perceived as the expert and you will walk in the room with the gravitas and respect you need to engage effectively with any stakeholder!

Interruption free can sometimes be a problem for time management when talking to an expert. Can you share some techniques for using active listening to guide the conversation, as opposed to giving up control?

There is a fine line between active listening (really listening and hearing everything, without jumping constantly to your own thoughts and reactions and perceptions) and simply being someone’s audience, and they’re driving the entire conversation. The difference between the two is a true dialog where you are asking good follow-up questions based on what they’re saying. BUT, the key to doing this well is to NOT be perceived as just listening so you can jump in and respond, which is what most people do, right? (Listen, react…listen, react…) No, you need to truly listen, really hear what they’re saying. What they’re saying will trigger thoughts and reactions in you. Capture that if you need to. And respond with questions. But probably not every thought and question you have needs airing. What are the ones that you really need to address in the context of helping your stakeholder figure out what they really need? This is a gray area and something you can only learn over time and in your context, so this is something I can’t exactly teach, except to suggest you try to find that balance. Simply being reminded that there is a balance to be found will hopefully help you get there in time.

You discuss the importance of building a holistic understanding of the problem, and switching between superficial and deeper concerns. Can you talk about how to interpret what you hear, and how to process that interpretation with stakeholders?

One of the most important initial ideas in Stakeholder Whispering is to acknowledge that we live our lives driven largely by our subconscious. So in the context of work, that plays out in the automated response to all of our work. For instance, in today’s world, what do we do when we want to make “data-driven” decisions? We measure stuff, and then we make a dashboard out of it! This automated response isn’t bad, but it’s just so rote that we don’t always think it through. We need to measure stuff, but which stuff, and how much, for how long? And we need to understand that data, but is a dashboard the answer or might it just be a 5-minute call to review one key metric? It depends. So we have to probe deeper than the automated response. This applies to everything. So to the question, the “superficial” is the initial obvious concern/request/plan. And “deeper” review is literally the entire point of Stakeholder Whispering. Sometimes the superficial initial idea may be all that’s needed. But sometimes it isn’t. Whispering to figure that out is what it’s all about! The way to do it is to ask incisive questions, open your ears with your domain and data expertise, trust your gut about things that you know might be concerns or worth further exploration, and probe those. The book is full of specific techniques to do it, and it’s hard to explain without diving deep. But the short answer is simply to engage what I call “useful paranoia”. Something is always missing or not quite right, so probe it! But that doesn’t mean everything requires a deep rabbit hole. Explore thoughtfully, and know when you’ve done enough to move on to the next concern. This is also something you will develop over time, but hopefully the ideas I share in the book will speed up that process.

For a new researcher, it’s often hard to balance best practices from the quantitative social science research they might have learned in school and design research in a business setting. Concerns about deviating from script, “biasing” responses, etc. are common. To me, it’s always been a matter of incorporating those best practices into a more fluid dance of the conversation. Can you talk more about how you think about that balance?

I think that balance is actually inherent to the Whispering process. Because the way I recommend doing it (and I talk about this in the book) is like therapy. When you go into therapy, and you share your childhood trauma or relationship troubles (or whatever), your therapist doesn’t give you solutions or ask leading questions. They ask intentionally open-ended questions like “how does that make you feel?” The point of therapy is to help you understand what you’re feeling. That’s what Whispering (and research) is about. You ask unbiased questions to be sure your data is pure. Now, in Whispering (as in therapy), sometimes the questions will eventually start to lead the witness a bit. The therapist may eventually say “it seems like you’re getting angry…is that what you’re feeling?” because they are there to guide their patients to some degree, based on their expertise. And in a Whispering session, you may start to ask less open-ended questions as you get a sense of where things are going. You might start with something like “why do you think a dashboard is best for this project?” But later in the conversation, you might ask something like “do you think a report might be more effective since you mentioned that people will be reviewing this on a plane and only 2X per year…maybe a dashboard isn’t the best tool for the job?” It’s OK to get to this point because, as the therapist, using your expertise and experience and active listening, you can help guide your stakeholders to the best decision based on the conversation. You’re not conducting primary research, so the standard does shift a bit from those types of conversations, and that’s the “dance of the conversation”, as you describe it, that you need to get comfortable with.

The post Review of Stakeholder Whispering by Bill Shander appeared first on Nightingale.

As an industrial-organizational psychologist, I started my career with a clear plan. Study workplace behavior. Research. Consult. Maybe teach.

Data visualization changed everything. It defined my approach to driving change in organizations. Data visualization transformed my career path.

When numbers become stories

Early on, I wanted to share everything I found in our HR data. But leaders ignored my work. Thoughtful reports sat on desks, unread. Sound familiar? Okay, I’m dating myself; today it’s the inbox. Slack. Teams.

The turning point came during a turnover presentation. Our standard practice was to display bar charts showing annual turnover rates over the last five years. The yearly turnover rate hid the crisis. I needed to show the issue. I switched to a line chart with new hire retention rates.

The Head of Product frowned: “Three years to master our product; gone before they lead projects.”

The room went quiet. The VP of HR leaned forward: “What do we do about this?” That’s another story.

That moment taught me everything. Data visualization makes problems visible and urgent.

This realization shaped my doctoral research. I explored cognitive processes that interact with visual design to create meaning. I wanted to understand the “seeing and thinking” of data. The findings confirmed my hypothesis: thoughtful design influences how people comprehend information.

The skills that open doors

As my visualization skills grew, something shifted. I wasn’t just better at my job—I became an advisor who told stories with data.

Data visualization is a career multiplier. Complex analysis becomes clear stories. Bridge the gap between data teams and the C-suite. 

Here’s how this transformation happens in practice: Analyst becomes advisor. Take the data scientist who predicts turnover with 80% accuracy. Her reports gather dust. She builds a dashboard showing teams with high turnover risk and when people will leave. Predictions become strategy. Managers act before losing talent. She becomes the team lead.

Data storytelling amplifies influence. Walk into a room of skeptics. Show them what they’ve missed. Charts inform; stories transform.

Picture this: One professional trapped in endless reporting. He maps employee onboarding journeys—where friction happens, when frustration peaks. Leadership finally sees the problem with follow-up. Budget approved. Problem solved. He now leads employee experience.

It transforms how you build teams. Leadership requires both skills: analyzing complex data and communicating it clearly. Not an analyst or storyteller. Both in one person.

Here’s what happened: A hiring manager struggled to fill a senior analyst role. Candidates excelled at SQL or Tableau, but not both. She shifted her approach. Hire for curiosity and communication, she thought. Train to close the technical gaps. The new hire connected with stakeholders immediately. Within six months, she presented to the board and led cross-functional projects.

The career playbook

For early career professionals: Don’t wait for perfect job descriptions. Lead with your visualization strengths. Show how they solve business problems. Build a portfolio for your industry. In interviews, explain: “Here’s the story I found, how I made it accessible, what decision it enabled,” and so on. Show before-and-after examples.

For experienced professionals: Your visualization skills differentiate you. The best analysts communicate the meaning of data to non-technical audiences. Explain impact: “This dashboard cut time from 10 hours to 30 minutes and boosted engagement by 40%.” 

For hiring managers: Hire storytellers, not just data analysts. Find people who craft compelling narratives that inspire behavior change. How the message is communicated matters more than complex models that gather dust.

The path forward

Data visualization careers don’t follow straight lines. We come from diverse backgrounds, including psychology, journalism, engineering, art, and many more. Many different disciplines. But we have the same goal: to make information meaningful and actionable. 

Here’s what I’ve learned about navigating career paths:

1. Embrace differences. Your unique background is an asset. Different perspectives make visualizations more intuitive.
2. Learn by doing. Solve real business problems. Volunteer to create dashboards for different departments. Find what works.
3. Build bridges. Work across disciplines. You don’t need expertise everywhere. You need curiosity and collaboration.
4. Think beyond job titles. The most fulfilling work happens outside traditional descriptions. When you turn data into stories that drive change, opportunities find you.
5. Find your community. DVS connects you with others who understand both technical and strategic sides. Get involved.

What’s next?

Want to experience this transformation yourself? Try this: Pick a visualization you struggle to explain. Think about its story. Share it with a colleague. Get feedback. Iterate. 

Data storytelling is strategic, not just an afterthought. It’s a mindset that prompts change.

It might change your career path. Career paths twist and turn. What’s your story?

The post How Data Visualization Became My Career Catalyst appeared first on Nightingale.

The internet “reads” your interests, and gradually your network expands. At some point, I became part of the Flowers and Figures community, joining others who are interested in data art and passionate about creative projects.

My path

At first, I was just studying the works of others, hesitating to try it myself, though ideas for data encoding had been circling in my head. As is often the case, my first attempt happened by accident. A few members met offline at a café just before Christmas to get to know each other and to attempt creating a data art project right there, on paper, using pens or markers, based on each person’s own data.

I loved it! Both the process and the result, even if it looked quite simple.

After that, I was eager to create something of my own—something real, not on paper.

As with any data visualization project, the key steps are:

• choose a topic
• find data
• and, in this case, invent a way to encode the data into visuals—the most creative part, in my view

An important decision is the path you take in encoding and presenting data art:

• One way is symbolic—any geometric figure, flower, or petal can mean anything, depending on what data value or category you assign to it
• The other way is to keep it as close as possible to the real object in the data, which isn’t always feasible.

The first step for every new community member is entering their data into a shared Google Sheet. This forms a dataset that can be used to create a full-fledged piece of data art. A community portrait—sometimes called data badges—is a popular format in data viz spaces, especially within communities or at conferences and events.

The range of themes for data encoding in the community is wide: geometric shapes, flowers (matching the community’s name), even bugs, and coats of arms. I wanted to create a community portrait that stood out from the gallery. And this time, I really wanted the project to exist physically; to photograph it and then compile a digital version.

According to the format rules, the portrait had to show:

• skills—drawing, crafting, data, data viz
• proficiency level in each skill
• name, gender (optional)

Dataset: Google Sheet where each new participant fills in a row about themselves.

The idea of physical data art

For representing the skills, I chose colorful plastic cable ties—commonly used to bundle wires and cables. They’re a simple and effective way to connect elements, widely used in construction and daily life. My daughter, a student, used longer ones to secure her rolled-up architectural drawings. These ties can withstand quite a bit of stress.

I wasn’t interested in technical specs though—the important factors were color and minimal size. There wasn’t much variety in colors—most sets offered standard combinations: red, blue, green, yellow, and orange. So I worked with what I had.

The encoding took shape

• Colorful ties = skills: drawing, crafting, data, data viz
• Proficiency level = length of the tie: trimmed literally to 1, 2, 3 cm or fully cut off if the level is 0

The hardest part was figuring out what to attach the ties to. I tried wooden coffee stirrers—too long. Chopsticks—needed cutting or grouping data for 2–3 people, which felt clunky and undermined the clarity of the concept.

I browsed various craft supplies, school kits, and eventually found counting rods—those plastic sticks used in early math learning kits for first-graders. Perfect for the project: 6 mm in diameter, 6 cm long—exactly what I needed.

One stick = one participant.

Everything else fell into place: gender represented by the color of the stick—black or white, painted with gouache. Labels repeated this info. At first, I tried writing names with a gel pen, but eventually moved to printed labels.

The result

I tried different layouts for the finished sticks. You can’t twist them too much—names become unreadable, lighting matters, shadows too. The final shot of the stick layout became the data art piece. The legend was made in Figma, and the whole composition was assembled there too.

The data art includes information from just a portion of the community—it’s grown a lot, and photographing the full dataset in one frame was technically impossible at home. I really didn’t want to use photo compositing. I added numbers to the printed name labels so participants could find themselves quickly, since names repeat. The whole process took about two weeks.

The sticks themselves turned out charming, and during our offline meetups I can hand them out to participants. They’re nice to touch and sort through—each with its own texture. Honestly, I didn’t want to put them down. But all things end—and the data art now fits neatly into a small box from a gadget.

I’ve seen breathtakingly beautiful projects shared in our channel—complex constructions from paper and thread, beads, even 3D-printed pieces, and what amazed me most—made of clay.

I couldn’t wait to share my result. I didn’t expect the post in the community to get so many comments and positive feedback on my modest effort. A short moment of fame—delightful and inspiring.

Now I’m thinking of making something material on a socially meaningful topic. To do that, I’ll need to: find the data, come up with an encoding in a specific material, and bring it to life. And in my most ambitious plans—participate in a data viz competition!

The post Plastic Portrait: Visualizing Technical Skills Through Cable Ties appeared first on Nightingale.

This year at VISAP—a mini conference and exhibition exploring the intersection of data visualization, art, and science—we’re asking what it means to approach visualization not just as a practice of analysis and synthesis, but as a form of collective care. How do we design visualizations that not only represent, but also actively protect, nurture, and respect the environments and communities embedded within datasets? What practices emerge when we begin to visualize data with thoughtfulness, empathy, and intention? In a time when data shapes public perception, policy, and personal identity, centering care in our visual methods becomes not just desirable, but essential.

In the world of data visualization, “care” is not a term we use often. We usually talk about clarity, insight, and impact; terms that suggest objectivity and utility. But as datasets expand to reflect our bodies, beliefs, environments, and communities, and as algorithms increasingly shape our collective realities, the visual representation of data becomes an act reflecting politics, culture, and ethics. It shapes how we understand one another and the systems built around us. In this light, the role of the visualizer extends beyond aesthetics or clarity, calling for a deeper engagement with social consequence and ethical responsibility. Recognizing this role means accepting that visual choices can influence narratives, reinforce or challenge biases, and shape public understanding in lasting ways.

In contemporary digital culture, data functions not as a static artifact but as a living archive, one that holds memory, identity, and collective history. Biometric scans, environmental sensors, and geotagged images—nearly every aspect of human life today is captured and converted into data. Giorgia Lupi suggests that working with data can uncover deeper connections, revealing not just patterns in the world, but insights into what it means to be human. Her approach invites us to see data not as detached or abstract, but as deeply embedded in the stories, emotions, and lived experiences of individuals and communities.

Within this context, data visualization is not merely a cosmetic tool for representation, but a critical process of reinterpretation, contextualization, and communication. It offers a means to narrate our datafied collective histories, shaping how communities are made legible. Artists and designers working in data visualization act as communicators and storytellers. Through visual, sonic, spatial, or even olfactory forms (such as scent-based installations) they transform abstract data into something tangible, something we can feel, question, and connect with. In doing so, they turn datasets into living archives and visualizations into spaces for reflection, empathy, and care.

Maria Puig de la Bellacasa calls this orientation “matters of care.” It’s a call to move beyond surface concern and into the thick, entangled, affective labor of maintenance, repair, and relationality. It’s an invitation to care for our practices the way we care for each other—not just efficiently, but attentively and critically. Within this framework, care is not about sentimentality; it is a relational and communal ethic. It urges us to take responsibility for the data we engage with and to honor the lives, communities, and ecosystems it represents. To visualize with care is to visualize with empathy: to make visible environmental harm, surface suppressed narratives, reveal shared experiences, and confront the structural biases that too often remain hidden.

Building on this understanding of visualization as a relational and embodied practice, we envision a future in which data visualization becomes a process of restoration, connection, and long-term social resilience. This vision invites us to approach data as a space for healing, resistance, and belonging. It encourages the use of data visualization to support the well-being of both environments and the communities most affected by them. These same values must also guide how we collaborate with emerging technologies, especially as we begin to co-create meaning with algorithmic systems and AI—for example, by shaping how data is interpreted, narratives are generated, and decisions are guided by machine learning tools. This collaboration raises critical questions around authorship, agency, and ethics: Whose data is used? Whose voices are amplified or erased? A care-centered approach to AI foregrounds transparency, accountability, and relational design, prioritizing systems that are socially responsible and culturally aware.

VISAP ’25 explores the theme Collective Care, inviting bold, critical, and creative works that reflect on the role of visualization in an interconnected world. In conjunction with IEEE VIS 2025, the program welcomes papers, pictorials, and artworks engaging with care, solidarity, and ethical collaboration. VISAP will take place in person at the University of Applied Arts Vienna from November 6–15, while IEEE VIS runs at the Austria Center Vienna from November 2–7.

Submission deadline: June 13, 2025.

For details, visit: https://visap.net
LinkedIn: https://www.linkedin.com/company/ieeevisap/
Instagram: https://www.instagram.com/visapnet/
Contact: art@ieeevis.org

The post Visualizing as a Form of Collective Care appeared first on Nightingale.

However, there is one group with which I’ve worked and written about before for Nightingale—the Yurok Tribe in far Northern California—where there is no well of data from which they can draw. For many reasons, overdose data are not available for them to understand the deep impact of overdose on Native American tribal members. I remember Yurok Tribe members telling me that they were flying blind with no access to useful data and that they often don’t know about an overdose until one of their tribe members dies from it, when it’s obviously too late to provide supportive and life-saving services.

I fear we may be entering an era when many more communities across California and the country will be flying blind without access to data–and on a range of issues, not just the devastating impact of overdose. Among the swirl of changes taking place within the federal government these last few months, you may not have noticed that the availability of meaningful, community-level data is under serious threat. As staff across U.S. data-collecting agencies are let go (and with it, institutional knowledge is lost); budgets for data work shrink; and federal data advisory boards are disbanded, the capacity for the federal government to collect data, conduct surveys, and publish community-level findings could greatly diminish. 

We won’t notice these impacts immediately. After all, the Census Bureau, Centers for Disease Control and Prevention along with other federal agencies often take a few years to publish community-level data on poverty, crowded housing, nutrition, smoking, domestic violence, and suicide prevention, among many other topics. One person with deep experience managing federal data described to me recent developments with the U.S. data infrastructure as a slow rot, as if termites are, bit by bit, eating away at the foundation of federal data. So it may be years before we truly see the extent of this damage, and by then, it won’t be easy to simply reinforce the foundation with minor repairs.

Few would likely argue with the concept that we need detailed data—including from federal data systems—for the U.S. to compete effectively in a worldwide marketplace where companies, and countries, increasingly rely on data to get ahead. From the perspective of global competitiveness, deconstructing our federal data systems seems short-sighted. After all, to compete globally, we need current and reliable data, better breakdowns, and a greater capacity to interpret, visualize, and communicate meaningful findings.

But that’s the world stage. And for those of us in the visualization community, we soon may have less social good data to visualize, and innovation with public sector visualization could slow. Why, however, are data important to communities across America? There are countless ways in which individuals harness these data to save lives, build safer communities, and improve local well being:

• Schools use data on reading and math proficiency, for example, to improve curriculum for our children
  
• Local hospitals and county health departments examine government data about service delivery and health care conditions impacting the community, in order to improve medical care and provide preventative services
  
• Adult kids seek Medicare data on the quality of nearby nursing homes for aging parents
  
• Realtors increasingly share public data with clients about crime and the quality of life in neighborhoods to help people make informed decisions about where to buy a home
  
• Many of us consult the local weather forecast each day—the federal government is a key source for this information, especially for tornadoes, hurricanes, heat waves, and other weather emergencies
  
• And, as noted above, data are used by coalitions to help communities save lives by addressing the threat of overdose

These data are not bound by political lines. They benefit Republicans, Democrats, and independents alike. People of all political persuasions can, and do, make use of the treasure trove of data that the U.S. government publishes, often thanks to data translators that participate in the Data Visualization Society. 

Our local elected officials—county supervisors, the school board, town council members—rely on these data, too, for good governance and effective policymaking. And, of course, access to quality data helps us evaluate our politicians’ policy choices and keep them honest. 

In short, these data are vital to help communities thrive, and lives hang in the balance with decisions we make using these data. These data are not just numbers. They represent each of us and the communities in which we live, and we have every right to the high quality, detailed data for which we pay as taxpayers.

Actions you can take

So, what can you do as someone focused on data visualization about the threats to federal data? 

Be aware of the slow rot that we’re beginning to see in our federal data infrastructure. 

Use the data we have now while encouraging your community leaders to do the same. Maybe such usage will make it harder to take away these valuable resources. There are an array of data tools that leverage what’s available now from federal sources to provide summaries of how your community is faring on wide-ranging topics (I maintain a listing of roughly 100 such data websites). 

Join efforts to do something. National groups taking a lead role include the Association of Public Data Users, the Data Rescue Project, and the newly launched Federal Data Forum, sponsored by the Population Reference Bureau. For anyone in California who’s concerned, there’s a group of us now meeting to address the threats to federal data on our state’s communities, so you can join us. And other states could be, and maybe are, taking similar action. 

And let politicians on both sides of the aisle know that federal data are under threat in ways that harm all of us and could have lasting negative impacts for the communities our children and grandchildren will inherit.

The post Data About America’s Communities Are In Jeopardy, and Lives May Hang in the Balance appeared first on Nightingale.

The Data Visualization Society (DVS) launched on February 20, 2019 with a post on Medium. It was a shock, a movement, a global phenomenon.

That article begins: 

“Over the last few years, data visualization has grown dramatically more common in our day-to-day experience. We see it in our news articles, in our social media and, for many of us, every day at work. The task of designing, creating, and deploying data visualization isn’t just a single profession but shows up in the work of engineers, analysts, salespeople, doctors, journalists, designers, students, and more… We created the Data Visualization Society in order to address that lack of professional development in the field, create a larger community, and provide a space that makes it more possible to learn from one another, differences and all. In doing so, we hope to establish guidelines for professional development to support people starting out in data visualization as well as those who have established careers.”

The DVS was started by Elijah Meeks, Amy Cesal, and Mollie Pettit months after a great conference called Tapestry held at the University of Miami in the fall of 2018. I was there because, earlier in 2018, I had written a series of lengthy articles about the data visualizations of W.E.B. Du Bois and had been chosen to give what was probably the first public presentation on his amazing work. I was so nervous that I read my talk word-for-word from a paper script because I was so worried that I’d mess up in front of a room of my new heroes.

On the first day, I met Elijah and he invited me to sit with him for lunch. In the next few minutes, the people who joined that table were a who’s who of dataviz—Cole Nussbaumer Knaflic, Mona Chalabi, Steve Wexler—I think Amanda Makulec was there too, or maybe she was at the next table. I was a big fan of RJ Andrews and he was at the next table. I was buzzing just to be near them all. I met Robert Crocker in the coffee line. Bill Shandler, too. Mollie Pettit had some kind of an amazing jacket and I told my wife how cool she was that night. Joey Cherderchuck showed off a demo that literally blew my mind the next day. I had no idea at the time, but many of the people at that conference turned out to have a major role in my life ever since. I had arrived into a scene somehow without even realizing it was a scene.

But a few months later, when Amy, Elijah, and Mollie made their announcement, I instantly joined. I think I was the seventh person to sign up for the DVS, and I pretty much blew off work to watch the DVS Slack grow by hundreds of people every few minutes. Something was happening and it was exhilarating!

Like I said, I had been writing a lot about dataviz and I was bummed about not having a good home to publish in. The main game in town at the time was Toward Data Science, and the data visualization subsection was a small, neglected back corner of their Medium empire. 

I was chatting with Elijah—it was my fourth or fifth message on the first day of the DVS Slack: “You know, if we do this thing right, we could make an amazing publication.” A few messages later I said, “if DVS grows, maybe we could do a print magazine one day!” That was the beginning of Nightingale. I knew from day one that we could make a community publication, and we would eventually make something physical. 

I became the Publications Director, and together with Elijah, we brokered a deal with Medium to create an exclusive publication which they paid for monthly. It felt clandestine.

On July 15, 2019, we launched Nightingale the Journal of the Data Visualization Society with four articles: 

Welcome To Nightingale by me, Jason Forrest, an introduction to the new publication.

Florence Nightingale is a Design Hero by RJ Andrews, which was the germ of an idea that evolved into his incredible book on Nightingale a few years later.

Beyond Nightingale: Being a Woman in Data Visualization by Stephanie Evergreen on tokenism in our community.

From the Battlefield to Basketball: A Data Visualization Journey with Florence Nightingale by Senthil Natarajan on creating a rose diagram for basketball stats.

Together, we felt these four articles represented a significant new direction for discourse in our community. These were not peer-reviewed papers, these were not articles playing second fiddle to hum-drum machine learning how-tos—these were serious explorations into divergent corners of dataviz that had never been explored. They were interesting, and they were alive!

My article started with this perky introduction:

“Nightingale will bring you high-quality articles each day covering many of the applications of data visualization — including education, entertainment, history, sports, best practices, new techniques, and any other form of visual information design we find compelling. We’ll host interviews with thought leaders and interesting people from the DVS community and beyond. Like all adventurers, we want to explore the unexplored, to look to the past and dream of the future. It’s exciting!”

So, here we are, six years later, and it’s worth noting that, as adventurers—we have done exactly this. We have explored so many new concepts that have never been written about in dataviz before. We created new ways to share our thoughts, spotlight new perspectives, share our work in progress, and reflect on our accomplishments and failures in an effort to help others. We held interviews, reviewed books and conferences, and created a global platform for our field to easily share their feelings and half-baked ideas. I am shocked at how thoroughly our mission at Nightingale has lived up to this initial statement and that of the DVS in general. We have created a living, active dialogue.

But establishing Nightingale in partnership with Medium also created two crucial mechanisms for our success: it allowed us to pay writers and hire staff to edit, illustrate, post, and promote each article, but it also provided critical start-up funding for the DVS. It can not be underscored enough how building this editorial team has helped our community! While no one has become rich from writing a Nightingale article (or being on our team) we can honestly say that everyone involved has been paid. By establishing an editorial team, we ensured that articles were systematically published at a sustainable rate to keep the conversation going. Consistency is so important for a professional publication, and we’re proud to have fought the good fight to keep Nightingale standards high, to keep everyone paid, and publish roughly two thousand articles.

Building an editorial team was the real joy

It started with our first managing editor, Isaac Levy-Rubinett, a sports journalist with an interest in dataviz. He helped us establish our first group of editors, created standards and processes to get articles edited, designed, posted, and promoted. Isaac was a gifted editor and created the theme week concept and much more. Our next managing editor was Mary Aviles, a design researcher and writer from Detroit who brought our publication to the next level in many ways. Mary got shit done but with grace and a deep consideration for our writers and community. 

On Feb 8, 2021, Mary and I co-published an article called “The Future Of Nightingale,” announcing the brazen goal of launching a print magazine. I honestly don’t think anyone really understood what that meant, but Mary and I were excited to give it a try. We pulled in our hot-shot editor Claire Santoro to be our new “Content Editor”—a role focused on creating and editing the best content for the new print magazine. Claire is a data analyst focused on sustainability and she crafted much of the vibe of Nightingale Magazine. Claire came up with a lot of our series content, like the popular Dataviz Horror Stories, etc.

I remember we had a few meetings with our editorial committee team where we asked questions like: “What even goes in a print magazine?” and “How do you ship them?,” but we figured it all out together. We also re-platformed from Medium to our own website (this one) and set up a CMS, which was a total pain, but it meant that all articles would be free and open to everyone.

This was right as the first Outlier was happening. It was still the pandemic, so it was online, and that’s where we first saw the amazing work of Julie Brunet (aka datacitron). It was a leap-before-look moment when I wrote her on Slack, and immediately said:  “Do you want to be our Creative Director?” She agreed and designed our brand and (almost) every page of our print magazines since! Some of my most exciting professional moments over the past six years were seeing her designs for the first time—and there are too many of those special moments to count!

Various images from the first five issues of Nightingale Magazine

We had published two issues of Nightingale magazine when our next Managing Editor, Emily Barone, joined us after being a data journalist and editor at Time Magazine. We were so excited because we were finally working with someone who had done this before! Emily brought so much care to her role in addition to her operational publishing expertise. She came up with the special sections in the back of each magazine, among many innovations, and helped us publish two more print magazines and another few hundred articles online. Emily also handled a bunch of the extremely difficult shipping logistics and set us on the right road for Issue 5 of the magazine.

Printed copies of Issue 5 at the printers. About 600 of these also took an international trip to EU that took more than three months—UGG!

I’m so proud of each member of our editorial team! Our current group—Will, Teo, Ale, and Julie—have already begun to take over my day-to-day responsibilities and will continue to provide the same level of care and enthusiasm for our writers and community as we have for the past six years. Honestly, there’s so much I can say about each of our editors (my friends) that I could go on and on. But I’ll wrap this up by saying that I truly learned so much from each one of you and I will forever be grateful for your collaboration!

My master plan—revealed!

Ok, I’ll admit it. For the last six years I had an agenda all along—to expand our community and influence it towards creating more illustrative, human-focused design. When I announced the magazine, I told people “it’s like a fashion magazine, but for dataviz”—and that was exactly the point. To make dataviz more alluring and to build on the magic of embodying data by showing our community the added power of illustration and design.

This is in service to attracting more attention to the data, to shining a light on new perspectives, and to propose a new way of communicating information to people. If you look at dataviz before Nightingale, and look at it today, I think you can see how we helped dataviz evolve our field in this direction. Sure, Nightingale hasn’t been the only publication pushing for this, but it’s easy to see how we championed creative, engaging ways to illustrate data and expand the scope of what is possible—and we have done this on a global scale.

In conclusion

So, here it is, the 1,444th article. Yes, it’s a bit bittersweet, but transitioning into my next phase as contributor, patron, and I hope, advertiser, means that I get to find new ways to engage with our community and support this amazing publication that has done far more for me than I can express. 

I thank my co-founder and friend, Elijah Meeks, for your collaboration over all these years. You always showed me so much respect from our first meeting to today, and I have learned much from your guidance and become wiser for (mostly) following it. 

I’d also like to warmly thank my friend and collaborator, Amanda Makulec, the former Executive Director of the DVS, who has been with me from the beginning of the DVS until now. We have a deep respect for each other and have supported each other through the ups and downs (yes, there have been a few of those), but we always remained focused on doing what was best for our community. I can’t wait to see where you go in your next chapter!

Lastly – I WANT TO THANK YOU!!! For the past six years, I have constantly engaged with our global dataviz community as an editor, on social, at conferences, answering your customer questions and complaints (yes, mistakes have been made!) and I remain still buzzing to just be part of it all. It’s like that moment back at the Tapestry Conference, when I was surrounded by all those famous dataviz people I had heard about—and that feeling just never stopped. In many ways, the community I feel a part of today is a reflection of the community I had always wanted to be part of—like a dream come true, a fantasy realized, a warm conversation with old friends. Thank you all for being so amazingly kind.

What’s next for me?

As most people know, I have a lot of energy and a lot of ideas!

I’m currently building the Jason Forrest Agency—a dataviz agency specializing in interactive projects in business. We’re small but growing fast, and I think we bring a different perspective on how to apply data storytelling concepts in a way that feels more relevant than ever.

I have also been hard at work on Data Vandals, a data activism project which is becoming increasingly more public. There’s so much more to explore by making dataviz more experiential and public. We’re excited that the idea is catching on! 

I also have a third “big thing” that is starting later this year. Unfortunately, I can’t announce it just yet, but my goal of advancing a more illustrative, human version of dataviz, and helping to open it up to the general public remains my focus—and it feels like the conversation will only get more dynamic from here.

Lastly, I look forward to writing more! I started Nightingale because I was a writer, but slowly this got pushed aside to deal with fun tasks like international shipping. I’ve also finished a book, so there will be so much more to write about, elaborate upon, and promote! 

So yes, I’ll be busy, and easy to find.

THANK YOU SO MUCH—IT’S BEEN AN HONOR!

Jason Forrest

The post My 6 Years at Nightingale: 1,443 Digital Articles, 5 Print Magazines, and a Whole Lot of Love appeared first on Nightingale.

Sure, I could wait five minutes more, right? I was in no rush (actually I was), I had nothing better to do (I did) and it wasn’t like it would put me in a difficult position (it definitely would). I tapped my fingers on the table, looked at the window, took my phone, and scrolled a bit on the old Pinterest. Was it…? Did I hear…? No, false alarm. It was not her. I sighed, put my phone away and tried scribbling on my notebook. 

Another five minutes went by but still no trace of the awaited guest. I started to wriggle in my chair, growing impatient and restless. I decided to take a few steps before anxiously coming back to my table: what if I missed her? But, as I waited there alone, alarming thoughts started to creep in: what if she won’t come? What if she left me for good? What would I do without her? She’ll be back, I comforted myself, she always does. But what if this time she won’t? Silence grew louder, it was an hour now. I suddenly jolted from my chair and left my desk, grabbed my keys, and slammed the door behind me. She had not come. Inspiration had not come, she wouldn’t come, she had failed me. 

Inspiration is such a d*ck. It has to be said. I know we all praise it and live by it, but when inspiration is a no-show, what are you left with? Having to work on a creative project with no inspiration is like driving a car with no wheel. Sure, you can move, but where the hell are you going? I wouldn’t say that working without inspiration is like living without internet connection because I don’t want to be over dramatic, but that’s pretty close and we all know it. We’re all terrified about it happening.

I don’t recall how many times I’ve been asked about how to find inspiration. Of course, that’s the pressing problem we all want the formula for. Maybe my answer should have been a brutal, honest one: you won’t. You won’t find inspiration and you never will. Stop looking for it everywhere—in books, in pinterest, in museums, in nature walks, in your sleep, or under the sofa. Any active search for inspiration is doomed to fail because in reality, inspiration is the anti-Beetlejuice—say its name three times and it disappears. 

Naturally, that’s not what I answer. I usually say what we all say: look into books, look into nature, look into museums and previous manifestations of it, look around you; inspiration is everywhere! Well, as long as you’re not actively searching for it, that is. Because the second you need it, the second you’re looking for it, inspiration left the building and you can organise a search party, but you’re not closer to finding it than common sense in current US politics. 

And don’t get me wrong, of course I believe in all that; I believe inspiration is everywhere. The fact is, I’m surrounded by inspiration. I sometimes even feel overwhelmed by inspiration. Every shell I see on the beach, every discarded paper on the street, every fabric sample, every color in pictures—they all call my name and ask to be turned into a project somehow. I try to note all their prayers on countless notebooks, I put them in storage boxes and give them the same half-empty promise of making them into a project, one day, soon. But that’s because finding inspiration and being inspired are two very different things. It’s easy to be inspired in a world filled to the brim with beauty and oddities. Open your eyes wide enough and everything sparkles back at you. But to me, that’s a very passive process. Inspiration strikes, it does the hard work, while you take the blow, inert recipient. Everything changes the minute you try to take a more active part in this role-play. When you’re in the hunt for inspiration, especially in the urgent need of some because of a work project—nature, art, history—they all show you their empty pockets. 

There’s something of a cruel irony at play to observe that inspiration is something that takes you by surprise, when you look the other way, that little spark of light you can see with the corner of your eye, but disappears when you try to look at it straight. I sometimes feel I’m not even around when I have great ideas. It’s like I’ve left the room for a minute to attend to something else and when I’m back, I found a sticky note on my brain urging me to do this or that. I don’t know where it comes from, it’s just there now. I guess that’s what you call inspiration and how it works—an outsider, an exterior gush of wind that entered you because you left an unattended window open. It’s a happy surprise of course, but it makes you ponder if your inspired ideas are never truly yours. Creativity is a weird thing. Everybody praises you for it but if you’re never really the one in control to begin with, is it really empowering?

After hours of failing to find inspiration when I needed it the most, I came to realise this common good becomes a rare currency when in demand; that’s why you should stockpile it. Inspiration is the one thing you should always hoard. I don’t count the number of Pinterest pins or tagged visuals on Instagram (actually, I counted and my Pinterest account currently holds 14,609 pins), the number of books or weird records stacked on my shelves as well as random objects that sparked joy in me at the time. And of course, hoarding like this, there’s no way I could find anything when needed in this bizarre gigantic library of curiosities; but remember, that’s the whole point. If finding inspiration is jinxed, you need to stumble upon it. Recreating by yourself the inspiring chaos of life seemed to me the best way to trip and fall on creativity on purpose, like you would when you’re not looking.

I’ve finished my long walk outside now. As I slide my key into the lock, I can feel my heart pound in my chest. Would this annoying roommate that is inspiration, always leaving stuff all over the place to hide them away when I look for them, have discarded some precious little nothing, tucked between the pages of a book for me to uncover? Let’s find out.

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The post Good Morning Data #10 | The Inspiration Geotag appeared first on Nightingale.