FOGATA

Inspiration

Project FOGATA (Spanish for "campfire") was born from the urgent need to address the "Infocalypse", a phenomenon where synthetic media erodes public trust. We were inspired by the concept of "Counter-data" from Data Feminism: the collection of information by communities when institutions fail to act. Research shows that 96 percentage of deepfake videos online are non-consensual pornography targeting women. In Colombian schools, these digital attacks are used as weapons of systemic gender violence to humiliate and silence girls. FOGATA fills the "Missing Datasets"—the gaps in information that reveal institutional bias and a lack of priority for minority issues.

What it does

FOGATA is a platform for Restorative Data Justice. It functions as a safe space for students to report deepfake attacks and, more importantly, document institutional negligence.

• Accountability: It allows users to search for reports on how specific directors or teachers reacted to cases, transforming the registry from a simple list of attacks into a tool for institutional change.

• Combating Denial: By systematizing reports, it breaks the "Liar’s Dividend", preventing perpetrators from claiming evidence is "fake" by showing patterns of behavior rather than isolated cases.

• Humanizing Data: It moves away from "deficit narratives" by reframing the data. Instead of focusing on "victim numbers," it highlights "Policy Failures," such as the percentage of reports ignored by school boards.

How we built it

We designed the platform following the principle of "Privacy by Design". To protect victims from the "Exposure Paradox"—where visibility creates more risk—we implemented a mathematical model based on $k$-anonimidad.

We used a decision matrix based on Colombian demographic data (DANE/MEN 2023) to determine the granularity of public data:

$$\text{Estimated Students} = \frac{\text{Territory Population} \times 0.15}{\text{Number of Schools}}$$

Any combination of filters must return at least $k=5$ individuals to be public. If the estimated number of girls in secondary/media per institution is less than $15$, the specific institution name is hidden to prevent doxxing.

Challenges we ran into

• The Exposure Paradox: Navigating the fine line between making harm visible and exposing victims to further violence or trauma.

• Institutional Privilege Hazard: Overcoming the fact that school leaders often lack the "empiricism of lived experience" to recognize the severity of digital attacks.

• Collective Identity Risk: In Indigenous and NARP (Afro-Colombian) communities, a report can risk not just an individual, but an entire legally recognized community or family, especially in conflict zones like Chocó or Cauca.

Accomplishments that we're proud of

• Reframing the Narrative: Shifting the "burden of proof" from the vulnerability of the girls to the negligence of the institutions.

• Technical Integrity: Designing a system where metadata remains verifiable for evidence while the user's identity is completely shielded.

• Community Model: Creating a "campfire" (fogata) architecture that prioritizes co-liberation and solidarity over a simple administrative dashboard.

What we learned

We learned that data is not just numbers; it represents "stolen years" and affected bodies. We adopted the Matrix of Domination to understand how power operates across structural, disciplinary, hegemonic, and interpersonal domains. We realized that what institutions "choose not to measure" is a direct reflection of what they do not value.

What's next for FOGATA

Our goal is to expand FOGATA into a national infrastructure for Data Justice in Colombia. We plan to:

1. Integrate specific protections for territorial and ethnic safety, ensuring that reports from Resguardos or Councils do not compromise collective security.

2. Develop automated tools to help student communities present these Counter-data reports directly to local education secretariats to force structural changes in school regulations.

3. Expand the "fogata" model to include mental health support networks that are activated when a cluster of reports is detected in a specific region.

Built With

• bcrypt
• css
• dm
• google
• mono)
• next.js
• node.js
• prismaorm
• react
• recharts
• sha-256
• shadcn/ui
• sqlite
• tailwind
• typescript
• vercel