activity
20192026
most citedVisualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations

22 citations · 71 across the 17 of their papers we have counts for

collaborators

18 papers

cs.HC2026

Exploring 3D Glyph Physicalizations for Public Engagement through River Health

Maria Teresa Ortoleva, Min Chen, Rita Borgo +1

Introduction: In this paper, we present the preliminary design of a toolkit for making glyph-based physicalizations for public engagement. We use London river health data as a case…

cs.HC2026

Optimizing Visual Analytics Workflows: From Theory to Practice

Philip Beaucamp, Alfie Abdul-Rahman, Rita Borgo +5

The principle of visual analytics (VA) is to provide integrated workflows where human-centric processes (e.g., visualization and interaction) and machine-centric processes (e.g., s…

cs.HC2026★ 1 cited

Chasing Meaning and/or Insight? A Survey on Evaluation Practices at the Intersection of Visualization and the Humanities

Alejandro Benito-Santos, Florian Windhager, Aida Horaniet Ibañez +3

The intersection of visualization and the humanities (VIS*H) is marked by a tension between chasing analytical "insight" and interpretive "meaning." The effectiveness of visualizat…

cs.HC2024

Complexity as Design Material

Florian Windhager, Alfie Abduhl-Rahman, Mark-Jan Bludau +5

Complexity is often seen as a inherent negative in information design, with the job of the designer being to reduce or eliminate complexity, and with principles like Tufte's "data-…

cs.HC2024

Mental Well-being Opportunities in Interacting and Reflecting with Personal Data Sculptures of EEG

Maria Teresa Ortoleva, Rita Borgo, Alfie Abdul-Rahman

Data physicalization is a research area in quick expansion whose necessity and popularity are motivated by the pervasiveness of data in our everyday. While the reflective ability o…

cs.CL2024

Visual Analytics for Fine-grained Text Classification Models and Datasets

Munkhtulga Battogtokh, Yiwen Xing, Cosmin Davidescu +3

In natural language processing (NLP), text classification tasks are increasingly fine-grained, as datasets are fragmented into a larger number of classes that are more difficult to…