Why This Project Exists

As a Latina immigrant, I have witnessed how marginalized communities become invisible in the data that is supposed to represent them. Census categories that don’t fit. Air quality reports that stop at the neighborhood border. Income statistics that flatten the complexity of Latine life into a single line. The data exists — but it was made without us, and it tells a story that doesn’t feel like ours.

Data Para Todes was born from a simple conviction: data democratization starts with making. Not just reading charts or consuming dashboards — but physically building the instruments that collect the data, deciding what gets measured, and owning the story that comes from it.

When George Fifield of Boston Cyberarts selected me to develop a solo show, I saw the opportunity to bring together everything I’d been working toward — a methodology where the Latine community could collect, through basic and affordable electronics, and tell stories of environmental justice within their own experience.

The Community: First-Generation Latine College Students

I partnered with Bottom Line, an organization that supports first-generation college students in Boston. The cohort were all first-generation Latine students from communities in Chelsea and Boston — neighborhoods disproportionately affected by environmental hazards, yet consistently underrepresented in the datasets that inform policy.

These students didn’t come to the project as data scientists. They came as community members who breathe the air, live in the apartments, and navigate the systems that data is supposed to describe. That’s exactly the expertise I was looking for. The question I brought to them was not “Can you learn data?” — it was “What does your data say that nobody else’s can?”

Building the Sensors: From Consumers to Makers

Data democratization, for me, begins at the hardware level. If communities depend on institutional sensors to know what’s in their air, they remain consumers of someone else’s measurement. I wanted to change that relationship entirely.

Through summer workshops, the cohort built their own indoor air quality sensors from affordable, open-source components. Each sensor measured Volatile Organic Compounds (VOC), small Particulate Matter (PM2.5), Humidity, Temperature, Ozone (O3), and Carbon Dioxide (CO2) — six dimensions of the air they breathe every day in their homes and dorms.

The students learned soldering, wiring, prototyping, and troubleshooting. They failed, debugged, rebuilt, and solved problems together. From the maker’s perspective, they gained critical thinking, design collaboration, and the confidence that comes from creating something functional with your own hands. They went from being consumers of technology to being makers of the tools that generate data about their own lives.

Students building affordable, open-source air quality sensors — from soldering to calibration.

Collecting What Institutions Don’t

For weeks, the cohort placed their sensors in their homes and dorms and collected indoor air quality data — data that, for these communities, simply did not exist before. There was already a body of work on outdoor air quality in Boston. But there was almost nothing on indoor air quality among underserved communities — no data on the apartments, the shared rooms, the aging ventilation systems where people actually live.

The students worked to identify errors in the sensors and the data, cleaned and organized it using Excel, and compared their indoor readings with outdoor data from commercially available Purple Air sensors in their neighborhoods. They didn’t just collect — they questioned: How does the air change depending on where you live? How close are you to the highway? How many people share your apartment? How old is your ventilation?

Visualizing Our Own Stories

Using Tableau, the cohort learned to bring their data to life — building interactive visualizations that told stories only they could tell. Each student crafted a narrative rooted in their own lived experience, comparing indoor and outdoor air quality, documenting conditions in their neighborhoods, and adding photographs and personal context that no institutional dataset would ever include.

I chose Tableau because it was accessible, easy to learn, and allowed the students to export interactive presentations that could function as exhibition pieces in the gallery. The tool mattered less than the principle: the community decides what the data means.

Explore the Data

This interactive visualization brings together the cohort’s data — indoor air quality measurements collected from their homes and dorms, mapped against the demographic landscape of Massachusetts. Navigate the story the students built from their own experience.

The Exhibition: Making Data Physical

The gallery became a space where data left the screen and entered the body. Every piece in the exhibition was designed to confront the audience with the reality of environmental inequality — not as an abstraction, but as a physical, sensory experience.

The 18-Foot Demographic Map

I created an 18-foot map visualizing the Latine population across Massachusetts. It shocked me that this map did not already exist in any publicly accessible form. The data came from the US Census — but had to be extracted manually, because there is no single view of the Latine community. Even the labeling on the Census raised questions about miscategorization and the invisibility of our population in official records.

The 18-foot demographic map — data extracted from US Census records to create a view of the Latine community that didn’t previously exist in public form.

The 25-Foot String Installation

To bring the air quality data out of the digital realm and into a tactile experience, I created a twenty-five-foot installation drawn with strings on nails. Each colored string represented one cohort member. Each line traced their data journey through two months of indoor air quality — VOC, PM2.5, humidity, and temperature.

I wanted the wall to become a canvas that confronts the audience. You stand in front of it and you are looking at a line chart — but it’s physical, it’s human-scale, and it represents the air that someone in your city is breathing right now. The goal is to ask: how does your air compare to theirs?

Each string is a cohort member. Each color is a measurement. Each nail is a data point — two months of the air they breathe, made visible and tangible.

LED Income Inequality Visualizations

Using LED light bars, I created graphs that make visible the stark contrast between the percentage of the population each racial group represents and their share of income in Massachusetts. The blue glow was intentional — intimate and welcoming, a counterpoint to the harsh reality the numbers reveal.

Understanding the relationship between median income, accessibility, and environmental racism requires seeing the full picture: historical segregation, systematic miscategorization, and economic disparity are not separate from air quality. They are the reason air quality is unequal.

Putting a Face to the Data

Every member of the cohort created an interactive data story using Tableau, displayed on individual screens in the gallery. But data without a human face is still abstract. So I photographed each student in their neighborhood and created life-size silhouettes that stood next to their screens.

This was essential. The piece is not just about technology or data visualization — it is about the person behind it. A first-generation college student from Chelsea who built a sensor, collected data from their apartment, cleaned it, analyzed it, and told a story that no institution had ever told about their home. We should strive to tell our own stories and put a face to the data.

What Changed

Data Para Todes created a methodology — not just an exhibition. First-generation Latine college students who had never soldered a wire built functioning air quality sensors. Students who had never opened a spreadsheet cleaned, analyzed, and visualized datasets that didn’t exist before they collected them. Community members who had never seen themselves in an environmental dataset became the authors of one.

By empowering the underrepresented Latine community with data literacy — from the hardware up — we start to close the gap between those who control the data and make decisions, and the communities that are affected by those decisions. Data democratization is not about access. It is about authorship.

The Workshops

Summer workshops with first-generation Latine college students through Bottom Line — from electronics fundamentals to functioning air quality sensors.

Presented & Recognized

BARI Conference 2023 — Greater Boston’s Annual Insight-to-Impact Summit, Northeastern University at the MIT Media Lab.

Community Conversation: Data as Power — Massachusetts Cultural Council, 2023.

The Paul and Edith Babson Foundation Grant — Funding support for the project.

Learn more at dataparatodes.com