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How do we design visualizations that not only represent, but actively protect, nurture, and respect the environments and communities embedded within datasets? As the world becomes increasingly shaped by algorithmic systems and automated decision-making, visualization must evolve beyond a purely technical act. It becomes an ethical, cultural, and emotional process. How can data visualization embody collective care? What practices emerge when we approach visualizing data as a responsible, thoughtful, and caring act? VISAP 2025 invites participants to reimagine data not as static or neutral, but as a living archive, a vessel for memory, identity, and shared histories. In this context, care is not sentimentality; it is relational and collective. It acknowledges the responsibilities we bear toward the data we use and the lives it represents. We are called to visualize with empathy to illuminate environmental issues, uncover hidden collective stories, surface silenced narratives, and expose systemic biases. VISAP 2025: Collective Care seeks works that explore data through frameworks of reciprocity, solidarity, and ethical collaboration. We welcome projects that resist extractive or exploitative data practices and instead propose alternative aesthetics and methodologies rooted in care, as data is never neutral. From speculative design to AI co-authorship, from community-centered storytelling to environmental data engagement, we are looking for work that reimagines the relationship between data, technology, and humanity. In embracing collective care, we advocate for a future in which data visualization becomes a process not only for insight, but for restoration, connection, and long-term social resilience. We ask: What becomes possible when data is treated as a space for healing, resistance, and belonging? How can we co-author meaning with algorithms with care, and engage AI as a collaborator in envisioning critical, thoughtful, future-oriented ideations? How might we take care of our environment and close-related communities by making use of data visualization? And when we give data physical form, how might the materials we choose and their environmental impact reflect the values of care we uphold?
