Bringing Data Closer: Han Qiao on Designing More Tangible and Sustainable Futures

Data is everywhere, it increasingly mediates how cities understand themselves. It informs decisions about housing, transportation, public health, climate adaptation, and access to essential services. Yet as urban life is translated into datasets, dashboards, and models, the people and experiences represented by that data can become harder to see.

For Han Qiao, a PhD candidate at the University of Toronto’s Faculty of Information and a researcher with the Just Sustainability Design Lab, this distance goes beyond a communication issue. It is a design problem, and a political one.

Han’s doctoral dissertation, Designing Data Visceralization for Imagining and Navigating Sustainable Futures, examines how people use data to understand the present and imagine more sustainable futures. Across three connected projects, she combines qualitative HCI research, critical design, community engagement, and creative practice to challenge the assumption that data is an objective and neutral representation of the world.

Data may appear to speak for itself, but its production involves choices about what to measure, how to classify it, whose knowledge counts, and which realities remain outside the dataset. Han asks what data interaction could look like if those choices were made visible, and if emotion, embodiment, imagination, and lived experience were treated as essential forms of knowledge.

Data near and far

The first project in Han’s dissertation emerged from conversations with community advocates working on urban sustainability across Toronto. With Siyi Wu and Professor Christoph Becker, she interviewed 17 people involved with 23 grassroots and nonprofit organizations addressing issues including affordable housing, public transit, road safety, mental health, climate action, and access to parks and food.

These advocates move between very different kinds of evidence. They may use government databases and research datasets, but they also rely on observations, community conversations, lived experiences, and locally collected information.

To describe these relationships, the researchers developed the concepts of “near data” and “far data.” Near data is close to the people using it and connected to the circumstances in which it was produced. Far data has travelled through institutions, systems, or processes that can separate it from its original context.

Neither is inherently better. Large datasets can reveal patterns that would otherwise remain invisible, while lived experience can expose what those datasets leave out or misrepresent. The challenge is to connect them without flattening their differences.

Han and her collaborators identified three pathways for doing so: connect data exploration with storytelling, communicate context and uncertainty, and place relationship-building at the centre of data work.

The resulting paper, “Near Data” and “Far Data” for Urban Sustainability: How Do Community Advocates Envision Data Intermediaries?, was published in Proceedings of the ACM on Human-Computer Interaction. It received a Best Paper Award at the 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) in Bergen, Norway.

The study recognizes community advocates not simply as users of data tools, but as experts who collect, interpret, challenge, and communicate data. Their knowledge can reshape how those tools are designed.

Moving from visualization to visceralization

The distinction between near and far data led Han toward data visceralization. Traditional data visualization aims to make information easier to see and understand. Data visceralization explores how people might also experience data through emotion, embodiment, and personal connection.

For Han, visceralization is both a way of making unfamiliar measurements more tangible and a critical approach to exposing the politics embedded in apparently neutral representations. This approach became central to Save the AI, a satirical campaign developed at the Just Sustainability Design Lab. By humorously asking people to sacrifice their own water, electricity, and other needs for artificial intelligence, the campaign makes a serious point: the environmental and social costs of AI infrastructure are often hidden from its users, even as those costs are borne by communities, workers, and ecosystems.

In Humour as Resistance: Visceralizing the Environmental and Social Impact of AI through Humour-based Creative Practices, published at ACM Creativity & Cognition 2026, Han and co-authors Rowan O.A. Munson, Nadia Mariyan Smith, Eshta Bhardwaj, and Professor Christoph Becker examine what humour contributed to the campaign.

Drawing on workshops, event ethnography, surveys, and interviews, the study identifies four roles for humour-based creative practice. Humour can connect people willing to question the assumptions of computing, create an emotional space in which distant impacts become tangible, act as social glue, and disrupt dominant narratives.

The research does not present humour as a replacement for policy, regulation, or organizing. Instead, it shows how creative practice can open conversations, support collective reflection, and help people imagine that alternatives are possible.

Connecting data to alternative futures

Han’s third dissertation project, now in development, will examine how community groups connect near and far data through creative practices.

Planned as a multiple-case study, the project will investigate initiatives that combine data from different sources or scales with practices such as art, storytelling, theatre, participatory design, installations, and performance. Through document and artifact analysis, interviews, and comparison across cases, Han aims to identify tactics and transferable design principles for connecting data with lived experience, and examine how these approaches operate across community settings and contribute to collective imagination and action.

Reorienting how HCI works with data

Together, Han’s projects advance data visceralization as both a theoretical lens and a creative research practice. Her dissertation trajectory is introduced in Designing Data Visceralization for Imagining and Navigating Sustainable Futures, presented at ACM Creativity & Cognition 2026 in London.

Han has also received an SDGs@UofT Student Award for research advancing the United Nations Sustainable Development Goals through interdisciplinary scholarship. Her funded project, Designing with Near Data and Far Data, explores how sustainability data is produced and mobilized in community advocacy, with particular attention to power, participation, and justice.

At a moment when data systems increasingly influence how institutions define problems and possible responses, Han’s work offers a timely intervention. It asks HCI researchers and designers to move beyond making data tools faster or easier to use. Designing data interactions also means shaping how people understand the world, opening a broader design space for HCI, one in which data can be questioned, felt, contested, and collectively reimagined.