SurakshaLens: Building People-First Climate Data to Protect Communities

This group discussion explores what it truly takes to build a people-first data platform designed to protect communities at the intersection of climate risk and exploitation. Using SurakshaLens as a case study, the session will unpack how data can move beyond dashboards and surveillance logic to become a tool for prevention, resilience, and collective agency.

SurakshaLens is envisioned as a climate exploitation risk platform that identifies patterns linking climate stress, migration pressures, and trafficking vulnerabilities. But the central question is not technological, it is ethical and political: How do we ensure such a platform is built with communities, not merely about them? How do we translate complex data into insight that district officials, frontline workers, and community leaders can use? And how do we prevent data tools from reinforcing harm, stigma, or over-policing?

Key discussion themes include: • Translating data into protection: from signals to actionable prevention • Community-led design and participatory data processes • Ethical AI and safeguards in vulnerable contexts • Visualization as a bridge between evidence and decision-making • Trust, accountability, and long-term resilience

This topic matters deeply to me as a criminologist working at the intersection of climate risk, exploitation, and technology. Too often, data systems in justice and security contexts are extractive, opaque, and imposed from above. SurakshaLens attempts a different approach — one grounded in community validation, multilingual accessibility, and practical usability for frontline actors.

The session connects directly to broader conversations in data visualization. Effective visualization is not about aesthetic clarity alone; it is about power. Who interprets the data? Who benefits from it? Who is protected by it? We will explore how layered mapping, risk indexing, and simplified visual narratives can translate complex, multi-source data into tools that strengthen early warning systems rather than intensify surveillance.

The session will be structured in three parts: 1. Framing the Challenge – Brief introduction to climate-linked exploitation risks and the need for preventive data systems. 2. Designing with Communities – Interactive discussion on participatory design, ethical guardrails, and trust-building. 3. From Data to Action – Small-group dialogue on what makes a platform usable, accountable, and locally owned.

The intended audience includes data visualization practitioners, technologists, researchers, policymakers, civil society actors, and community advocates interested in ethical data use and public-interest technology.

Participants will leave with: • A clearer understanding of people-first data design principles • Practical considerations for translating complex data into protective action • A framework for embedding ethics and community ownership into digital platforms • Insight into how data visualization can strengthen resilience rather than merely monitor risk

Ultimately, this session asks: What would it mean to build data systems that communities trust, shape, and use to protect themselves?