The Art of Telling Stories with Data

How to make people care about the things you've discovered

You've spent months on this. Maybe it's your thesis, hundreds of drone flights over a wetland, tracking how vegetation changes through the seasons. Maybe it's a community project, your watershed group finally has thermal imagery showing where agricultural runoff enters the creek. Maybe you're just someone who fell in love with photogrammetry and now you have a hard drive full of 3D models of places that matter to you.

The data is beautiful. The patterns are real. You've discovered something.

And then you try to explain it to someone, your advisor, your town council, your neighbors, your family, and their eyes glaze over. They nod politely. They don't get it.

This is the heartbreak of data collection. You can spend years gathering information about the world, see things that genuinely matter, and still struggle to make anyone else care. It's not that people are stupid or uninterested. It's that we, scientists, researchers, hobbyists, citizen scientists, were never taught how to tell stories.

The Uncomfortable Truth About Data

Here's something I had to learn the hard way: data doesn't speak for itself. We like to think it does. We imagine that if we just present the facts clearly enough, people will understand. The numbers will convince them. The imagery will amaze them. The truth will be self-evident.

It doesn't work that way.

Researchers who study science communication have known this for decades. Michael Dahlstrom, writing in the Proceedings of the National Academy of Sciences, put it bluntly: narrative formats are simply easier for people to comprehend and engage with than traditional scientific communication. Once people leave school, they get most of their information about science from mass media, and mass media runs on stories, not datasets.

"Data gives you the what, but humans know the why."

There's even a famous line in science: "The plural of anecdote is not data." It's a warning against drawing conclusions from cherry-picked stories instead of systematic evidence. And for doing science, it's absolutely right.

But when it comes to sharing what you've learned? The mantra flips. "Data does not go viral," as one research team put it. "Stories do."

This isn't a flaw in human nature. It's how our brains evolved. We learned to survive by telling stories around fires, passing knowledge through generations in narrative form. We remember characters, conflicts, and resolutions. We forget spreadsheets.

What Actually Makes Something a Story?

Researchers have spent a lot of time trying to figure out what separates a "story" from just "information," and the answer turns out to be surprisingly precise.

A good story violates expectations.

That's the core of it. Stories work by presenting something unexpected, a cause that surprises us, an effect we didn't anticipate, a pattern that challenges what we thought we knew. There's an old journalism saying: "If the dog bites the mail carrier, it's not a story. If the mail carrier bites the dog, THAT is a story."

Think about what this means for your data. If you survey a forest and find exactly what everyone expected, you have useful information, but you don't have much of a story. If you survey that same forest and find something surprising, regrowth where everyone assumed there was decline, disease spreading faster than models predicted, an unexpected species thriving in the understory, now you have the foundation for a narrative.

Surprise creates engagement. Engagement creates learning. When your aerial imagery reveals something that contradicts assumptions, something that makes people say "wait, really?", that's the moment to build on.

The Gift of Seeing from Above

There's something special about aerial data for storytelling, and it goes beyond technical capability.

Aerial imagery is beautiful.

Aerial perspective of frosted trees.

I don't mean that as a throwaway compliment. Beauty matters for communication. When you show someone an orthomosaic of a river delta, the colors of a vegetation index, the intricate geometry of a photogrammetric model, something happens before they even process the content. They feel wonder. They lean in. They want to understand.

Researchers studying data visualization have found that emotional response is a "catalyst for learning." Aerial imagery triggers that response almost automatically. You don't have to convince people to pay attention, the image does that work for you.

Patterns invisible from the ground become obvious from above.

But there's something deeper too. The aerial perspective fundamentally changes how we see the world. Patterns that are invisible when you're standing in them become obvious from fifty meters up. The shape of erosion. The health of a canopy. The way water moves across a landscape. The cumulative impact of human activity on places we thought we knew.

This shift in perspective is itself a kind of story. You're not just showing data, you're offering people a way of seeing that most have never experienced. Your neighbor has walked past that creek a thousand times, but she's never seen it the way your thermal imagery reveals it. Your city council has driven past that development site for years, but they've never understood its topography the way your elevation model shows it.

That novelty, that "I never knew it looked like that", is a violation of expectations. It's the beginning of a story.

Data That Belongs to a Place

Some of the most powerful data stories come from community science, projects where the people collecting data are also the people who live with its implications. When your watershed group monitors water quality, when your neighborhood maps urban heat islands, when your school tracks bird populations in the local park, the data isn't abstract. It's personal.

Researchers have found that this creates something they call "experiential knowledge", participants don't just contribute observations, they develop understanding of the data practices themselves. They become part of the story. They're not audience members; they're characters.

Aerial imagery can amplify this beautifully. When you fly a survey over a watershed that volunteers have been monitoring from the ground for years, you're giving them a new view of something they already care about deeply. That recognition, "I know that place, I've walked those trails, but I've never seen it like this", creates emotional engagement that no amount of outsider expertise can match.

There's a framework researchers developed called STORCIT, storytelling approaches for citizen science, that's specifically designed to honor this kind of local knowledge. The idea is that data stories should give voice to communities, not just extract information from them. When the story belongs to the people who gathered the data, it has a authenticity that resonates.

Think about what this means for your project. If you're monitoring something in your community, the story isn't just "here's what we found." It's "here's what WE found, about OUR place, and here's why it matters to US." That possessive pronoun changes everything.

Turning Your Data into Narrative

So how do you actually do this? How do you take a point cloud or an orthomosaic or a time series of vegetation indices and turn it into something that moves people?

Find the Surprise

Before you present anything, ask yourself: what did I find that I didn't expect? What contradicts the assumptions? What made me say "huh, that's interesting"? That's your hook. That's the mail carrier biting the dog.

If you can't find a surprise, look harder. Compare your data to historical records, to predictions, to what people believe. The surprise might be in the gap between perception and reality.

Give It Stakes

Why should anyone care? What hangs in the balance? Stories need stakes, something to win or lose. Maybe it's a species, a place, a way of life. Maybe it's a decision the community needs to make. Maybe it's simply understanding something true about the world that was hidden before.

The stakes don't have to be dramatic. "If we don't understand this, we'll keep making the same mistakes" is a stake. "This place is changing and we should know how" is a stake. "This is beautiful and more people should see it" is a stake.

Create a Journey

Stories have shape: beginning, middle, end. For data, that often means time, a "before" that establishes baseline, a "now" that shows current state, a "what's next" that gives direction. Time-series comparisons are natural narratives: watch the glacier retreat, see the forest recover, track the development spread.

But even single-survey data can have arc. "Here's what we expected. Here's what we found. Here's what we think it means." That's a three-act structure.

Let Them Discover

The most powerful moment in any story is when the audience figures something out for themselves. Interactive 3D models let people explore and discover. Animated flythroughs reveal patterns sequentially, building understanding. Side-by-side comparisons let viewers spot differences without being told what to see.

Don't just tell people what you found. Create the conditions for them to find it too.

The Responsibility of the Storyteller

Stories are persuasive. That's the point, but it's also the danger. A beautiful visualization can make uncertain findings feel definitive. A compelling narrative can flatten nuance. An emotionally resonant presentation can obscure the limitations of the data.

Researchers who study data storytelling take this seriously. "The transformation of data to an understandable format," one team noted, "might also result in (un)intended misuse." The same techniques that make your findings accessible can make them misleading.

So tell stories, but tell them honestly. Show uncertainty when it exists. Acknowledge what you don't know. Don't let the narrative override the science. Your goal is to help people understand, not to manipulate them into believing.

The best data stories don't just make people feel, they make people think. They create conditions for insight, not just emotional response. That's the difference between education and propaganda.

Why It Matters

Right now, on hard drives all over the world, there is beautiful aerial data that no one will ever see. Graduate students have imagery that could change how their communities understand local ecosystems. Citizen science groups have time series that document changes no official monitoring program captured. Hobbyists have 3D models of places that are already being destroyed.

That data represents thousands of hours of work, genuine discoveries about how the world works, and perspectives that most people have never been offered. And most of it will stay locked in technical formats, seen only by the handful of specialists who know how to interpret it.

That's not a technical failure. It's a storytelling failure.

You collected this data because something mattered to you, a place, a question, a community, a curiosity. Other people can care about those things too, if you show them how to see what you've seen. The aerial perspective is a gift. The data is a gift. But gifts only matter if they're given.

Learn to tell stories. The world is listening, it just doesn't know it yet.

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This essay draws on research in science communication, data visualization, and citizen science. Key works include Dahlstrom's "Using narratives and storytelling to communicate science with nonexpert audiences" (PNAS, 2014), systematic reviews of data storytelling practices, and the STORCIT framework for inclusive citizen science storytelling.

Aeria Solutions is a remote sensing company based in Squamish, BC, working with researchers, non-profits, community groups and industry using aerial imagery to understand and protect the places that matter to them.