Sheelagh Carpendale

Matthew Brehmer, Maxime Cordeil, Christophe Hurter et al.

We characterize 16 challenges faced by those investigating and developing remote and synchronous collaborative experiences around visualization. Our work reflects the perspectives and prior research efforts of an international group of 29 experts from across human-computer interaction and visualization sub-communities. The challenges are anchored around five collaborative activities that exhibit a centrality of visualization and multimodal communication. These activities include exploratory data analysis, creative ideation, visualization-rich presentations, joint decision making grounded in data, and real-time data monitoring. The challenges also reflect the changing dynamics of these activities in the face of recent advances in extended reality (XR) and artificial intelligence (AI). As an organizing scheme for future research at the intersection of visualization and computer-supported cooperative work, we align the challenges with a sequence of four sets of research and development activities: technological choices, social factors, AI assistance, and evaluation.

Xingyu Lan, Leni Yang, Zezhong Wang et al.

Storytelling is an ancient and precious human ability that has been rejuvenated in the digital age. Over the last decade, there has been a notable surge in the recognition and application of data storytelling, both in academia and industry. Recently, the rapid development of generative AI has brought new opportunities and challenges to this field, sparking numerous new questions. These questions may not necessarily be quickly transformed into papers, but we believe it is necessary to promptly discuss them to help the community better clarify important issues and research agendas for the future. We thus invite you to join our workshop (Gen4DS) to discuss questions such as: How can generative AI facilitate the creation of data stories? How might generative AI alter the workflow of data storytellers? What are the pitfalls and risks of incorporating AI in storytelling? We have designed both paper presentations and interactive activities (including hands-on creation, group discussion pods, and debates on controversial issues) for the workshop. We hope that participants will learn about the latest advances and pioneering work in data storytelling, engage in critical conversations with each other, and have an enjoyable, unforgettable, and meaningful experience at the event.

Fateme Rajabiyazdi, Julie Babione, Doreen M. Rabi et al.

Creating supportive technologies for people living with multiple chronic conditions is extremely challenging. These patients are often faced with substantial visible and invisible treatment work as well as their everyday responsibilities, including coordinating across providers, tracking information, and repeating communication in emotionally charged contexts. In the Cumulative Complexity Model (CuCoM), the balance between patient workload and patient capacity shapes what patients can realistically take on, including whether a digital tool can be adopted and sustained. In this paper, we report engagement lessons from implementing MyCareCompass, a patient-facing digital health intervention (DHI) intended to support day-to-day self-management for people living with multiple chronic conditions. We define engagement as patient uptake and sustained use during a two-month pilot study of our platform, drawing on usage analytics and follow-up feedback, and distill three implementation lessons for designing for engagement in complex chronic care.

Fateme Rajabiyazdi, Charles Perin, Lora Oehlberg et al.

Designing patient-collected health data visualizations to support discussing patient data during clinical visits is a challenging problem due to the heterogeneity of the parties involved: patients, healthcare providers, and healthcare systems. Designers must ensure that all parties' needs are met. This complexity makes it challenging to find a definitive solution that can work for every individual. We have approached this research problem -- communicating patient data during clinical visits -- as a wicked problem. In this article, we outline how wicked problem characteristics apply to our research problem. We then describe the research methodologies we employed to explore the design space of individualized patient data visualization solutions. Last, we reflect on the insights and experiences we gained through this exploratory design process. We conclude with a call to action for researchers and visualization designers to consider patients' and healthcare providers' individualities when designing patient data visualizations.

Wesley Willett, Bon Adriel Aseniero, Sheelagh Carpendale et al.

We explore how the lens of fictional superpowers can help characterize how visualizations empower people and provide inspiration for new visualization systems. Researchers and practitioners often tout visualizations' ability to "make the invisible visible" and to "enhance cognitive abilities." Meanwhile superhero comics and other modern fiction often depict characters with similarly fantastic abilities that allow them to see and interpret the world in ways that transcend traditional human perception. We investigate the intersection of these domains, and show how the language of superpowers can be used to characterize existing visualization systems and suggest opportunities for new and empowering ones. We introduce two frameworks: The first characterizes seven underlying mechanisms that form the basis for a variety of visual superpowers portrayed in fiction. The second identifies seven ways in which visualization tools and interfaces can instill a sense of empowerment in the people who use them. Building on these observations, we illustrate a diverse set of "visualization superpowers" and highlight opportunities for the visualization community to create new systems and interactions that empower new experiences with data.

Tatiana Losev, Sarah Storteboom, Sheelagh Carpendale et al.

We reflect on our experiences as designers of COVID-19 data visualizations working in a distributed synchronous design space during the pandemic. This is especially relevant as the pandemic posed new challenges to distributed collaboration amidst civic lockdown measures and an increased dependency on spatially distributed teamwork across almost all sectors. Working from home being 'the new normal', we explored potential solutions for collaborating and prototyping remotely from our own homes using the existing tools at our disposal. Since members of our cross-disciplinary team had different technical skills, we used a range of synchronous remote design tools and methods. We aimed to preserve the richness of co-located collaboration such as face-to-face physical presence, body gestures, facial expressions, and the making and sharing of physical artifacts. While meeting over Zoom, we sketched on paper and used digital collaboration tools, such as Miro and Google Docs. Using an auto-ethnographic approach, we articulate our challenges and strategies throughout the process, providing useful insights about synchronous distributed collaboration.

Bon Adriel Aseniero, Charles Perin, Wesley Willett et al.

We present Activity River, a personal visualization tool which enables individuals to plan, log, and reflect on their self-defined activities. We are interested in supporting this type of reflective practice as prior work has shown that reflection can help people plan and manage their time effectively. Hence, we designed Activity River based on five design goals (visualize historical and contextual data, facilitate comparison of goals and achievements, engage viewers with delightful visuals, support authorship, and enable flexible planning and logging) which we distilled from the Information Visualization and Human-Computer Interaction literature. To explore our approach's strengths and limitations, we conducted a qualitative study of Activity River using a role-playing method. Through this qualitative exploration, we illustrate how our participants envisioned using our visualization to perform dynamic and continuous reflection on their activities. We observed that they were able to assess their progress towards their plans and adapt to unforeseen circumstances using our tool.

Gonzalo Gabriel Méndez, Jagoda Walny, Søren Knudsen et al.

Constructive approaches to visualization authoring have been shown to offer advantages such as providing options for flexible outputs, scaffolding and ideation of new data mappings, personalized exploration of data, as well as supporting data understanding and literacy. However, visualization authoring tools based on a constructive approach do not scale well to larger datasets. As construction often involves manipulating small pieces of data and visuals, it requires a significant amount of time, effort, and repetitive steps. We present ReConstructor, an authoring tool in which a visualization is constructed by instantiating its structural and functional components through four interaction elements (objects, modifiers, activators, and tools). This design preserves most of the benefits of a constructive process while avoiding scalability issues by allowing designers to propagate individual mapping steps to all the elements of a visualization. We also discuss the perceived benefits of our approach and propose avenues for future research in this area.

Kyle Wm. Hall, Adam J. Bradley, Uta Hinrichs et al.

While previous work exists on how to conduct and disseminate insights from problem-driven visualization projects and design studies, the literature does not address how to accomplish these goals in transdisciplinary teams in ways that advance all disciplines involved. In this paper we introduce and define a new methodological paradigm we call design by immersion, which provides an alternative perspective on problem-driven visualization work. Design by immersion embeds transdisciplinary experiences at the center of the visualization process by having visualization researchers participate in the work of the target domain (or domain experts participate in visualization research). Based on our own combined experiences of working on cross-disciplinary, problem-driven visualization projects, we present six case studies that expose the opportunities that design by immersion enables, including (1) exploring new domain-inspired visualization design spaces, (2) enriching domain understanding through personal experiences, and (3) building strong transdisciplinary relationships. Furthermore, we illustrate how the process of design by immersion opens up a diverse set of design activities that can be combined in different ways depending on the type of collaboration, project, and goals. Finally, we discuss the challenges and potential pitfalls of design by immersion.

Jagoda Walny, Christian Frisson, Mieka West et al.

Complex data visualization design projects often entail collaboration between people with different visualization-related skills. For example, many teams include both designers who create new visualization designs and developers who implement the resulting visualization software. We identify gaps between data characterization tools, visualization design tools, and development platforms that pose challenges for designer-developer teams working to create new data visualizations. While it is common for commercial interaction design tools to support collaboration between designers and developers, creating data visualizations poses several unique challenges that are not supported by current tools. In particular, visualization designers must characterize and build an understanding of the underlying data, then specify layouts, data encodings, and other data-driven parameters that will be robust across many different data values. In larger teams, designers must also clearly communicate these mappings and their dependencies to developers, clients, and other collaborators. We report observations and reflections from five large multidisciplinary visualization design projects and highlight six data-specific visualization challenges for design specification and handoff. These challenges include adapting to changing data, anticipating edge cases in data, understanding technical challenges, articulating data-dependent interactions, communicating data mappings, and preserving the integrity of data mappings across iterations. Based on these observations, we identify opportunities for future tools for prototyping, testing, and communicating data-driven designs, which might contribute to more successful and collaborative data visualization design.