As Artificial Intelligence (AI) conversational agents become widespread, people are increasingly using them for health information seeking. The use of off-the-shelf conversational agents for health information seeking could place high metacognitive demands (the need for extensive monitoring and control of one’s own thought process) on individuals, which could compromise their experience of seeking health information. However, currently, the specific demands that arise while using conversational agents for health information seeking, and the strategies people use to cope with those demands, remain unknown. To address these gaps, we conducted a think-aloud study with 15 participants as they sought health information using our off-the-shelf AI conversational agent. We identified the metacognitive demands such systems impose, the strategies people adopt in response, and propose considerations for designing beyond off-the-shelf interfaces to reduce these demands and support better user experiences and affordances in health information seeking.

Co-design is an increasingly popular approach in HCI and visualization, yet there is little guidance on how to effectively apply this method in visualization contexts. In this paper, we visually present our experience of a two-and-a-half-year co-design project with the local arts community. Focusing on facilitating community exploration and sense-making around arts funding distribution, the project involved a series of co-design sessions between visualization researchers and members of the arts community. Through these iterative sessions, we built shared understanding and developed visualization prototypes tailored to community needs. However, the practice is far from complete, and we found ourselves continually returning to the ``fuzzy front end'' of the co-design process. We share this ongoing story through comic-style visuals and reflect on three fuzzy front ends that we encountered during the project. By sharing these experiences with the visualization community, we hope to offer insights that others can draw on in their own community-engaged co-design work.

As visualization systems increasingly engage users in data collection and reflection, new questions arise around how input can better align with everyday life. While prior work on input visualizations often relies on explicit, visually mediated interaction, this paper explores technologies that support less effortful and less intrusive modes of data contribution. Our goal is to expand the design space of input—particularly for modalities that reduce visual, physical, or social demands—so that input might become easier, more sustainable, and more naturally embedded into daily routines. We review a range of modalities—including on-skin sensing, wearable textiles, and shape-changing materials—that shift input beyond traditional screen interactions. Building on this review, we propose a design space defined by interaction effort and social or environmental intrusiveness, highlighting trade-offs and opportunities across modalities. This work aims to prompt reflection on how data input might become more situated, expressive, and continuous, inviting new possibilities for how, when, and where data is collected.

Unlike digital visualization, physicalization design introduces structural and material uncertainties, which require immediate feedback and often rapid iteration. This makes physicalization design a speculative, labor-intensive, and expertise-dependent activity. While speculative reasoning can be central to physicalization, authoring tools remain scarce and there is a lack of computational support that can help in anticipating physicalization outcomes. We explore how feedforward mechanisms (predictive features) might help physicalization designers anticipate post-fabrication qualities like tactile feel and expandability before fabrication by iteratively developing and studying DataCuts, a physicalization authoring tool for designing Kirigami-based data physicalizations. Our study findings show that DataCuts’ simple feedforward functionalities can inform design decisions, shape people’s understanding of physical properties and encourage tactile representation over conventional mappings. Building on these results, we discuss implications for designing data physicalization support tools that integrate feedforward.

There is a growing interest in representing data physically across various domains. However, our understanding of the physicalization design process is minimal, posing barriers to supporting designers and wider utilization of physicalization. In this work, we studied the dynamics of the physicalization design process, to understand how data physicalization designers navigate, iterate, and make decisions throughout their creative workflows. We employed a technology probe approach that facilitates designing KiriPhys – Kirigami-inspired physicalizations. We conducted an exploratory qualitative study, observing physicalization experts design KiriPhys freely and using the probe. From analysing the gathered data, we discovered an interactive data physicalization design process formed of six activities, characterized by non-linear and highly iterative movements between them. A key observed activity within this process is the concept of feedforward, which highlights the designer’s proactive forward-thinking when making design choices, considering the physical aspects of the results. Our findings suggest strategies for digitally supporting the interactive data physicalization process.

We present KiriPhys, a new type of data physicalization based on kirigami, a traditional Japanese art form that uses paper-cutting. Within the kirigami possibilities, we investigate how different aspects of cutting patterns offer opportunities for mapping data to both independent and dependent physical variables. As a first step towards understanding the data physicalization opportunities in KiriPhys, we conducted a qualitative study in which 12 participants interacted with four KiriPhys examples. Our observations of how people interact with, understand, and respond to KiriPhys suggest that KiriPhys: 1) provides new opportunities for interactive, layered data exploration, 2) introduces elastic expansion as a new sensation that can reveal data, and 3) offers data mapping possibilities while providing a pleasurable experience that stimulates curiosity and engagement.

This book chapter discusses and reflects on an ideation methodology that can help imagine future mobile only visualizations through a human-centered design approach. The chapter starts by outlining the general approach of the methodology. Ideation activities of three different design groups are then described to illustrate how one can adapt and adjust the methodology to specific ideation scenarios; and four different ideation activity approaches are presented with example results. The chapter ends with a reflection on the methodology itself and how the flexibility of the methodology can encourage a wide range of ideas to emerge.

Social media is increasingly integral to daily life, promising global connections but often falling short of fostering meaningful interactions, as highlighted by media coverage. To examine people’s social media experiences, we conducted a qualitative study using a two-pronged approach: (1) two technology probes to elicit feedback on alternative features and functionalities, and (2) one-on-one creativity sessions with 16 participants to explore social media’s impact and future potential. Participants actively shared their experiences, focusing on connections and agency. Findings reveal a desire for features enhancing expressivity, control over content curation, and deeper connections beyond current platforms’ offerings. We also discuss how privacy, anonymity, agency, content curation, and echo chambers shape social media experiences.

This pictorial illustrates an autoethnographic exploration of the first author’s design practice for the data physicalization “Shredded Lives: A Decade of Migrant Loss.” It emphasizes the parallel development of seven design components--Interaction Mode, Technology, Data Representation, Physical Configuration & Scale, Dataset, Engagement Mode, and Spatial Experience. This flexible, non-hierarchical approach allows each of the seven design components to inform and evolve alongside the others, stemming from a desire to thoroughly explore the design space without confinement by initial restrictions. As these design components overlap and intersect, dynamic interactions occur, leading to the manifestation of design ideas

We present an interactive carbon emission data physicalization based on the Kirigami technique. Leveraging the interaction and data representation possibilities of Kirigami, we physicalize total and per capita carbon emission in a way that reflects the data set relationships: Total emission divided by population is equal to emission per capita.

This article presents a computational approach to generating large-scale architectural forms using paper-cutting techniques, where a flat sheet expands into a 3D structure. Four key challenges were addressed: (1) mapping kinetic properties by analyzing cut parameters, (2) simulating structures via finite element analysis (Ansys), (3) developing a predictive model using data mining and regression analysis (400 simulations), and (4) validating the model with physical prototypes. The resulting system optimizes cutting patterns and predicts structural behavior, advancing a traditionally ad-hoc design process.

This paper presents a computational system for designing large spanning structures using paper-cutting techniques, where a flat sheet expands into a 3D structure with minimal force. Unlike prior ad-hoc methods, our approach predicts optimal cutting patterns and structural behavior through finite element simulation, data mining (400 pattern variations), and regression analysis. Given a few designer inputs, the model rapidly estimates transformation volume, improving precision and efficiency. Future work will extend predictions to additional structural properties.