While it is proven that the individual construction of a data physicalization aids personal sense-making, little is known about how sense-making is negotiated when it is shared by multiple, co-located participants. Since participatory data physicalization can inadvertently prioritize dominant views, we interpreted data feminism principles to design a collaborative physicalization construction process that empowers stakeholders and participants to co-determine how meanings are represented. This process revealed how the interplay of physical and non-physical actions during construction negotiations supported collaborative sense-making among 14 groups of 55 participants during 4 workshops, enabling us to articulate how explicit power is embodied by the physicalization artifact and negotiated between authoring and collaborating participants, and facilitators; whereas tacit power operates through artifact meanings, participant identity and design decisions. By providing one operationalization of data-feminist critique into the form of design requirements, our contributions support the design of more equitable physicalization and visualization construction methods.

Participatory data physicalisation (PDP) is recognised for its potential to support data-driven decisions among stakeholders who collaboratively construct physical elements into commonly insightful visualisations. Like all participatory processes, PDP is however influenced by underlying power dynamics that might lead to issues regarding extractive participation, marginalisation, or exclusion, among others. We first identified the decisions behind these power dynamics by developing an ontology that synthesises critical theoretical insights from both visualisation and participatory design research, which were then systematically applied unto a representative corpus of 23 PDP artefacts. By revealing how shared decisions are guided by different agendas, this paper presents three contributions: 1) a cross-disciplinary ontology that facilitates the systematic analysis of existing and novel PDP artefacts and processes; which leads to 2) six PDP agendas that reflect the key power dynamics in current PDP practice, revealing the diversity of orientations towards stakeholder participation in PDP practice; and 3) a set of critical considerations that should guide how power dynamics can be balanced, such as by reflecting on how issues are represented, data is contextualised, participants express their meanings, and how participants can dissent with flexible artefact construction. Consequently, this study advances a feminist research agenda by guiding researchers and practitioners in openly reflecting on and sharing responsibilities in data physicalisation and participatory data visualisation.

In light of machine learning's increasing computational needs, developers created energy and carbon-reporting tools to calculate and communicate their models' environmental impact. These tools use modeling parameters as inputs and respond with expected or incurred energy requirements or carbon emissions. This work critically and systematically analyses them regarding their content, form, and design process. Besides their noble intentions, many of the shortcomings of early sustainable HCI eco-feedback tools are still being propagated in these tools. Moreover, their design and development have limited inclusion of potential stakeholders. We argue the need for a next generation of approaches to ML eco-feedback that (a) further support rematerialization, (b) use participatory approaches in their design and development to support collaborative team environments and go beyond individual persuasion, (c) consider complexities of ML models and processes, and more broadly, (d) re-center around sufficiency rather than only efficiency.

Organisations require diverse technological infrastructures to create value from data. Because these infrastructures are often haphazardly developed, they cause frictions between the socio-technical agencies of the involved stakeholders. Datopolis is a role-playing game consisting of cards, tiles and tokens that was specifically designed to support such stakeholders to experience, understand and reflect on how data infrastructures should be developed and maintained. Although the game has reached more than 20 organisations in 8 different countries since its original release 8 years ago, little is known about how its resources and rules actually elicit critical reflection among its players. By conducting a retrospective qualitative study consisting of 27 interviews with stakeholders, we uncovered that the prototypical role-playing narrative drives critical reflection through 3 facilitation approaches and 3 play strategies that are anchored in organisational contexts shared among players. We are thus able to present three contributions: 1) a retrospective study grounded in interviews with actual stakeholders being affected by the game; 2) an overview of play strategies and facilitation approaches that enacted the infrastructuring processes through role-play; and 3) critical considerations to operationalise how role-play supports learning, situated in real-world contexts and shaped by facilitation. This study calls for a critical examination of the role of interpretation during learning activities to empower stakeholders in reclaiming control over organisational practices.

Data physicalizations have gained prominence across domains, but their environmental impact has been largely overlooked. This work addresses this gap by investigating the interplay between sustainability and physicalization practices. We conducted interviews with experts from diverse backgrounds, followed by a survey to gather insights into how they approach physicalization projects and reflect on sustainability. Our thematic analysis revealed sustainability considerations throughout the entire physicalization life cycle—a framework that encompasses various stages in a physicalization’s existence. Notably, we found no single agreed-upon definition for sustainable physicalizations, highlighting the complexity of integrating sustainability into physicalization practices. We outline sustainability challenges and strategies based on participants’ experiences and propose the Sustainable Physicalization Practices (SuPPra) Matrix, providing a structured approach for designers to reflect on and enhance the environmental impact of their future physicalizations.

Energy communities are a key focus for governments around the world in support of more sustainable energy practices. However, interactive systems for supporting energy communities to coordinate around renewable energy resources are still lacking. We present SolarClub, a demand-shifting visualization system that supported households in coordinating their energy usage by booking energy-hungry activities when solar energy was available. We deployed SolarClub with four groups of neighbors (N=15) for a month. SolarClub successfully enabled neighbors to coordinate, even when some of those participating households were less flexible. While participants reported that SolarClub did not foster a feeling of community, it helped them empathize with their neighbors. Our findings demonstrate the potential of sensor- and visualization-based technology to help understand the relation between everyday practices and resources consumption, beyond individual eco-feedback. This work thus contributes to the development of a next generation of practices and technologies that support collective action for environmental sustainability.

Despite extensive efforts to create fairer machine learning (ML) datasets, there remains a limited understanding of the practical aspects of dataset curation. Drawing from interviews with 30 ML dataset curators, we present a comprehensive taxonomy of the challenges and trade-offs encountered throughout the dataset curation lifecycle. Our findings underscore overarching issues within the broader fairness landscape that impact data curation. We conclude with recommendations aimed at fostering systemic changes to better facilitate fair dataset curation practices.

As visualisations reach a broad range of audiences, designing visualisations that attract and engage becomes more critical. Prior work suggests that semantic icons entice and immerse the reader; however, little is known about their impact with informational tasks and when the viewer’s attention is divided because of a distracting element. To address this gap, we first explored a variety of semantic icons with various visualisation attributes. The findings of this exploration shaped the design of our primary comparative online user studies, where participants saw a target visualisation with a distracting visualisation on a web page and were asked to extract insights. Their engagement was measured through three dependent variables: (1) visual attention, (2) effort to write insights, and (3) self-reported engagement. In Study 1, we discovered that visualisations with semantic icons were consistently perceived to be more engaging than the plain version. However, we found no differences in visual attention and effort between the two versions. Thus, we ran Study 2 using visualisations with more salient semantic icons to achieve maximum contrast. The results were consistent with our first Study. Furthermore, we found that semantic icons elevated engagement with visualisations depicting less interesting and engaging topics from the participant’s perspective. We extended prior work by demonstrating the semantic value after performing an informational task (extracting insights) and reflecting on the visualisation, besides its value to the first impression. Our findings may be helpful to visualisation designers and storytellers keen on designing engaging visualisations with limited resources. We also contribute reflections on engagement measurements with visualisations and provide future directions.

Embellishments are features commonly used in everyday visualisations which are demonstrated to enhance assimilation and memorability. Despite their popularity, little is known about their impact on enticing readers to explore visualisations. To address this gap, we conducted 18 interviews with a diverse group of participants who were consumers of news media but non-experts in visualisation and design. Participants were shown ten embellished and plain visualisations collected from the news and asked to rank them based on enticement and ease of understanding. Extending prior work, our interview results suggest that visualisations with multiple embellishment types might make a visualisation perceived as more enticing. An important finding from our study is that the widespread of certain embellishments in the media might have made them part of visualisation conventions, making a visualisation appear more objective but less enticing. Based on these findings, we ran a follow-up online user study showing participants variations of the visualisations with multiple embellishments to isolate each embellishment type and investigate its effect. We found that variations with salient embellishments were perceived as more enticing. We argue that to unpack the concept of embellishments; we must consider two factors: embellishment saliency and editorial styles. Our study contributes concept and design considerations to the literature concerned with visualisation design for non-experts in visualisation and design.

Due to their historical nature, humanistic data encompass multiple sources of uncertainty. While humanists are accustomed to handling such uncertainty with their established methods, they are cautious of visualizations that appear overly objective and fail to communicate this uncertainty. To design more trustworthy visualizations for humanistic research, therefore, a deeper understanding of its relation to uncertainty is needed. We systematically reviewed 126 publications from digital humanities literature that use visualization as part of their research process, and examined how uncertainty was handled and represented in their visualizations. Crossing these dimensions with the visualization type and use, we identified that uncertainty originated from multiple steps in the research process from the source artifacts to their datafication. We also noted how besides known uncertainty coping strategies, such as excluding data and evaluating its effects, humanists also embraced uncertainty as a separate dimension important to retain. By mapping how the visualizations encoded uncertainty, we identified four approaches that varied in terms of explicitness and customization. This work contributes with two empirical taxonomies of uncertainty and it's corresponding coping strategies, as well as with the foundation of a research agenda for uncertainty visualization in the digital humanities. Our findings further the synergy among humanists and visualization researchers, and ultimately contribute to the development of more trustworthy, uncertainty-aware visualizations.

This study introduces Co-gnito, a participatory physicalization game that supports collaborative urban mental mapping through storytelling. Through Co-gnito we investigate gaming as a means to elicit subjective spatial experiences and to steer the synchronous construction of a physicalization that aligns and represents them. Co-gnito was evaluated during seven deployments by analyzing how 28 players mapped their spatial experiences of two university campuses. Our results indicate that storytelling as a gaming mechanic, guided and motivated the gradual addition of personal contributions towards a collective outcome, but its reward system did not nudge the mapping direction as expected. We also demonstrate how the shared construction process of a physicalization is influenced by how the data encoding scheme was negotiated, by the token physical affordances and by the game mechanics. We therefore believe that our core contributions, comprising of: 1) a working research prototype; 2) an augmentation of the physicalization pipeline towards collaborative settings; and 3) a set of reflective considerations, provide actionable knowledge on how to design participatory physicalizations in the future.

While we know that the visualization of quantifiable uncertainty impacts the confidence in insights, little is known about whether the same is true for uncertainty that originates from aspects so inherent to the data that they can only be accounted for qualitatively. Being embedded within an archaeological project, we realized how assessing such qualitative uncertainty is crucial in gaining a holistic and accurate understanding of regional spatio-temporal patterns of human settlements over millennia. We therefore investigated the impact of visualizing qualitative implicit errors on the sense-making process via a probe that deliberately represented three distinct implicit errors, i.e., differing collection methods, subjectivity of data interpretations and assumptions on temporal continuity. By analyzing the interactions of 14 archaeologists with different levels of domain expertise, we discovered that novices became more actively aware of typically overlooked data issues and domain experts became more confident of the visualization itself. We observed how participants quoted social factors to alleviate some uncertainty, while in order to minimize it they requested additional contextual breadth or depth of the data. While our visualization did not alleviate all uncertainty, we recognized how it sparked reflective meta-insights regarding methodological directions of the data. We believe our findings inform future visualizations on how to handle the complexity of implicit errors for a range of user typologies and for highly data-critical application domains such as the digital humanities.