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Paul Parsons

Publications and source records attributed to Paul Parsons.

At least 19 recordsLinked to original sources

Talking Inspiration: A Discourse Analysis of Data Visualization Podcasts

Data visualization practitioners routinely invoke inspiration, yet we know little about how it is constructed in public conversations. We conduct a discourse analysis of 31 episodes from five popular data visualization podcasts. Podcasts are public-facing and inherently performative: guests manage impressions, articulate values, and model "good practice" for broad audiences. We use this performative setting to examine how legitimacy, identity, and practice are negotiated in community talk. We show that "inspiration talk" is operative rather than ornamental: speakers legitimize what counts, who counts, and how work proceeds. Our analysis surfaces four adjustable evaluation criteria by which inspiration is judged-novelty, authority, authenticity, and affect-and three operative metaphors that license different practices-spark, muscle, and resource bank. We argue that treating inspiration as a boundary object helps explain why these frames coexist across contexts. Findings provide a vocabulary for examining how inspiration is mobilized in visualization practice, with implications for evaluation, pedagogy, and the design of galleries and repositories that surface inspirational examples.

cs.HC

Identifying Framing Practices in Visualization Design Through Practitioner Reflections

Framing -- how designers define and reinterpret problems, shape narratives, and guide audience understanding -- is central to design practice. Yet in visualization research, framing has been examined mostly through its rhetorical and perceptual effects on audiences, leaving its role in the design process underexplored. This study addresses that gap by analyzing publicly available podcasts and book chapters in which over 80 professional visualization designers reflect on their work. We find that framing is a pervasive, iterative activity, evident in scoping problems, interpreting data, aligning with stakeholder goals, and shaping narrative direction. Our analysis identifies the conditions that trigger reframing and the strategies practitioners use to navigate uncertainty and guide design. These findings position framing as a core dimension of visualization practice and underscore the need for research and education to support the interpretive and strategic judgment that practitioners exercise throughout the design process.

cs.HC

Rethinking Citation of AI Sources in Student-AI Collaboration within HCI Design Education

The growing integration of AI tools in student design projects presents an unresolved challenge in HCI education: how should AI-generated content be cited and documented? Traditional citation frameworks -- grounded in credibility, retrievability, and authorship -- struggle to accommodate the dynamic and ephemeral nature of AI outputs. In this paper, we examine how undergraduate students in a UX design course approached AI usage and citation when given the freedom to integrate generative tools into their design process. Through qualitative analysis of 35 team projects and reflections from 175 students, we identify varied citation practices ranging from formal attribution to indirect or absent acknowledgment. These inconsistencies reveal gaps in existing frameworks and raise questions about authorship, assessment, and pedagogical transparency. We argue for rethinking AI citation as a reflective and pedagogical practice; one that supports metacognitive engagement by prompting students to critically evaluate how and why they used AI throughout the design process. We propose alternative strategies -- such as AI contribution statements and process-aware citation models that better align with the iterative and reflective nature of design education. This work invites educators to reconsider how citation practices can support meaningful student--AI collaboration.

cs.HC

Tracing the Invisible: Understanding Students' Judgment in AI-Supported Design Work

As generative AI tools become integrated into design workflows, students increasingly engage with these tools not just as aids, but as collaborators. This study analyzes reflections from 33 student teams in an HCI design course to examine the kinds of judgments students make when using AI tools. We found both established forms of design judgment (e.g., instrumental, appreciative, quality) and emergent types: agency-distribution judgment and reliability judgment. These new forms capture how students negotiate creative responsibility with AI and assess the trustworthiness of its outputs. Our findings suggest that generative AI introduces new layers of complexity into design reasoning, prompting students to reflect not only on what AI produces, but also on how and when to rely on it. By foregrounding these judgments, we offer a conceptual lens for understanding how students engage in co-creative sensemaking with AI in design contexts.

cs.HC

Coping with Uncertainty in UX Design Practice: Practitioner Strategies and Judgment

The complexity of UX design practice extends beyond ill-structured design problems to include uncertainties shaped by shifting stakeholder priorities, team dynamics, limited resources, and implementation constraints. While prior research in related fields has addressed uncertainty in design more broadly, the specific character of uncertainty in UX practice remains underexplored. This study examines how UX practitioners experience and respond to uncertainty in real-world projects, drawing on a multi-week diary study and follow-up interviews with ten designers. We identify a range of practitioner strategies-including adaptive framing, negotiation, and judgment-that allow designers to move forward amid ambiguity. Our findings highlight the central role of design judgment in navigating uncertainty, including emergent forms such as temporal and sacrificial judgment, and extend prior understandings by showing how UX practitioners engage uncertainty as a persistent, situated feature of practice.

cs.HC

Are Cognitive Biases as Important as they Seem for Data Visualization?

Research on cognitive biases and heuristics has become increasingly popular in the visualization literature in recent years. Researchers have studied the effects of biases on visualization interpretation and subsequent decision-making. While this work is important, we contend that the view on biases has presented human cognitive abilities in an unbalanced manner, placing too much emphasis on the flaws and limitations of human decision-making, and potentially suggesting that it should not be trusted. Several decision researchers have argued that the flip side of biases -- i.e., mental shortcuts or heuristics -- demonstrate human ingenuity and serve as core markers of adaptive expertise. In this paper, we review the perspectives and sentiments of the visualization community on biases and describe literature arguing for more balanced views of biases and heuristics. We hope this paper will encourage visualization researchers to consider a fuller picture of human cognitive limitations and strategies for making decisions in complex environments.

cs.HC

De-skilling, Cognitive Offloading, and Misplaced Responsibilities: Potential Ironies of AI-Assisted Design

The rapid adoption of generative AI (GenAI) in design has sparked discussions about its benefits and unintended consequences. While AI is often framed as a tool for enhancing productivity by automating routine tasks, historical research on automation warns of paradoxical effects, such as de-skilling and misplaced responsibilities. To assess UX practitioners' perceptions of AI, we analyzed over 120 articles and discussions from UX-focused subreddits. Our findings indicate that while practitioners express optimism about AI reducing repetitive work and augmenting creativity, they also highlight concerns about over-reliance, cognitive offloading, and the erosion of critical design skills. Drawing from human-automation interaction literature, we discuss how these perspectives align with well-documented automation ironies and function allocation challenges. We argue that UX professionals should critically evaluate AI's role beyond immediate productivity gains and consider its long-term implications for creative autonomy and expertise. This study contributes empirical insights into practitioners' perspectives and links them to broader debates on automation in design.

cs.HC

How Visualization Designers Perceive and Use Inspiration

Inspiration plays an important role in design, yet its specific impact on data visualization design practice remains underexplored. This study investigates how professional visualization designers perceive and use inspiration in their practice. Through semi-structured interviews, we examine their sources of inspiration, the value they place on them, and how they navigate the balance between inspiration and imitation. Our findings reveal that designers draw from a diverse array of sources, including existing visualizations, real-world phenomena, and personal experiences. Participants describe a mix of active and passive inspiration practices, often iterating on sources to create original designs. This research offers insights into the role of inspiration in visualization practice, the need to expand visualization design theory, and the implications for the development of visualization tools that support inspiration and for training future visualization designers.

cs.HC

Understanding Data Visualization Design Practice

Professional roles for data visualization designers are growing in popularity, and interest in relationships between the academic research and professional practice communities is gaining traction. However, despite the potential for knowledge sharing between these communities, we have little understanding of the ways in which practitioners design in real-world, professional settings. Inquiry in numerous design disciplines indicates that practitioners approach complex situations in ways that are fundamentally different from those of researchers. In this work, I take a practice-led approach to understanding visualization design practice on its own terms. Twenty data visualization practitioners were interviewed and asked about their design process, including the steps they take, how they make decisions, and the methods they use. Findings suggest that practitioners do not follow highly systematic processes, but instead rely on situated forms of knowing and acting in which they draw from precedent and use methods and principles that are determined appropriate in the moment. These findings have implications for how visualization researchers understand and engage with practitioners, and how educators approach the training of future data visualization designers.

cs.HC

Fixation and Creativity in Data Visualization Design: Experiences and Perspectives of Practitioners

Data visualization design often requires creativity, and research is needed to understand its nature and means for promoting it. The current visualization literature on creativity is not well developed, especially with respect to the experiences of professional data visualization designers. We conducted semi-structured interviews with 15 data visualization practitioners, focusing on a specific aspect of creativity known as design fixation. Fixation occurs when designers adhere blindly or prematurely to a set of ideas that limit creative outcomes. We present practitioners' experiences and perspectives from their own design practice, specifically focusing on their views of (i) the nature of fixation, (ii) factors encouraging fixation, and (iii) factors discouraging fixation. We identify opportunities for future research related to chart recommendations, inspiration, and perspective shifts in data visualization design.

cs.HC

Hack.VR: A Programming Game in Virtual Reality

In this article we describe Hack.VR, an object-oriented programming game in virtual reality. Hack.VR uses a VR programming language in which nodes represent functions and node connections represent data flow. Using this programming framework, players reprogram VR objects such as elevators, robots, and switches. Hack.VR has been designed to be highly interactable both physically and semantically.

cs.HC

How do Visualization Designers Think? Design Cognition as a Core Aspect of Visualization Psychology

There are numerous opportunities for engaging in research at the intersection of psychology and visualization. While most opportunities taken up by the VIS community will likely focus on the psychology of users, there are also opportunities for studying the psychology of designers. In this position paper, I argue the importance of studying design cognition as a necessary component of a holistic program of research on visualization psychology. I provide a brief overview of research on design cognition in other disciplines, and discuss opportunities for VIS to build an analogous research program. Doing so can lead to a stronger integration of research and design practice, can provide a better understanding of how to educate and train future designers, and will likely surface both challenges and opportunities for future research.

cs.HC

Design Judgment in Data Visualization Practice

Data visualization is becoming an increasingly popular field of design practice. Although many studies have highlighted the knowledge required for effective data visualization design, their focus has largely been on formal knowledge and logical decision-making processes that can be abstracted and codified. Less attention has been paid to the more situated and personal ways of knowing that are prevalent in all design activity. In this study, we conducted semi-structured interviews with data visualization practitioners during which they were asked to describe the practical and situated aspects of their design processes. Using a philosophical framework of design judgment from Nelson and Stolterman [23], we analyzed the transcripts to describe the volume and complex layering of design judgments that are used by data visualization practitioners as they describe and interrogate their work. We identify aspects of data visualization practice that require further investigation beyond notions of rational, model- or principle-directed decision-making processes.

cs.HC

Data Visualization Practitioners' Perspectives on Chartjunk

Chartjunk is a popular yet contentious topic. Previous studies have shown that extreme minimalism is not always best, and that visual embellishments can be useful depending on the context. While more knowledge is being developed regarding the effects of embellishments on users, less attention has been given to the perspectives of practitioners regarding how they design with embellishments. We conducted semi-structured interviews with 20 data visualization practitioners, investigating how they understand chartjunk and the factors that influence how and when they make use of embellishments. Our investigation uncovers a broad and pluralistic understanding of chartjunk among practitioners, and foregrounds a variety of personal and situated factors that influence the use of chartjunk beyond context. We highlight the personal nature of design practice, and discuss the need for more practice-led research to better understand the ways in which concepts like chartjunk are interpreted and used by practitioners.

cs.HC

Using Java for distributed computing in the Gaia satellite data processing

In recent years Java has matured to a stable easy-to-use language with the flexibility of an interpreter (for reflection etc.) but the performance and type checking of a compiled language. When we started using Java for astronomical applications around 1999 they were the first of their kind in astronomy. Now a great deal of astronomy software is written in Java as are many business applications. We discuss the current environment and trends concerning the language and present an actual example of scientific use of Java for high-performance distributed computing: ESA's mission Gaia. The Gaia scanning satellite will perform a galactic census of about 1000 million objects in our galaxy. The Gaia community has chosen to write its processing software in Java. We explore the manifold reasons for choosing Java for this large science collaboration. Gaia processing is numerically complex but highly distributable, some parts being embarrassingly parallel. We describe the Gaia processing architecture and its realisation in Java. We delve into the astrometric solution which is the most advanced and most complex part of the processing. The Gaia simulator is also written in Java and is the most mature code in the system. This has been successfully running since about 2005 on the supercomputer "Marenostrum" in Barcelona. We relate experiences of using Java on a large shared machine. Finally we discuss Java, including some of its problems, for scientific computing.

cs.CE

The Behaviour Of Cosmological Models With Varying-G

We provide a detailed analysis of Friedmann-Robertson-Walker universes in a wide range of scalar-tensor theories of gravity. We apply solution-generating methods to three parametrised classes of scalar-tensor theory which lead naturally to general relativity in the weak-field limit. We restrict the parameters which specify these theories by the requirements imposed by the weak-field tests of gravitation theories in the solar system and by the requirement that viable cosmological solutions be obtained. We construct a range of exact solutions for open, closed, and flat isotropic universes containing matter with equation of state $p\leq \frac{1}{3}ρ$ and in vacuum. We study the range of early and late-time behaviours displayed, examine when there is a `bounce' at early times, and expansion maxima in closed models.

gr-qc

Inflationary Models with Logarithmic Potentials

We examine inflationary universe models driven by scalar fields with logarithmic potentials of the form $V(ϕ) = V_0 ϕ^p(\ln ϕ)^q$. Combining the slow-roll approximation with asymptotic techniques, we identify regions of the potential where inflation may occur and obtain analytic expressions for the evolution of the field and the metric in these cases. We construct a family of exact solutions to the equations of motion with potentials resembling the above form and demonstrate their inflationary nature; deflationary and conflationary cosmological behaviours are also defined and identified. Finally, a computation of scalar density and tensor gravitational perturbations produced by the model is presented.

astro-ph

Generalised Scalar Field Potentials and Inflation

We investigate the range of inflationary universe models driven by scalar fields possessing a general interaction potential of the form $V(ϕ) = V_0 ϕ^n \exp(-λϕ^m)$. Power-law, de Sitter and intermediate inflationary universes emerge as special cases together with several new varieties of inflation. Analysing the behaviour of these models at the extrema of $ϕ$ we derive sufficient constraints on the $m$ - $n$ parameter space such that inflation may occur as both an early and late-time phenomenon. We also compute the scalar and tensor perturbations produced in the model and compare these results with recent observations.

astro-ph