50 citations · 152 across the 14 of their papers we have counts for
16 papers
AI-Centered Grand Challenges in Visual Analytics for Healthcare: Synthesizing the VAHC 2025 Community Experience
Jürgen Bernard, David Gotz, Robert S Laramee +4
The intersection of AI, healthcare, and visualization is evolving rapidly, posing challenges that cut across disciplinary boundaries and resist easy resolution. The Visual Analytic…
What Makes a Visualization Image Complex?
Mengdi Chu, Zefeng Qiu, Meng Ling +4
We investigate the perceived visual complexity (VC) in data visualizations using objective image-based metrics. We collected VC scores through a large-scale crowdsourcing experimen…
Mastery Learning Improves Performance on Complex Tasks on PCP Literacy Test
Chandana Srinivas, Elif E. Firat, Robert S. Laramee +1
Developing literacy with unfamiliar data visualization techniques such as Parallel Coordinate Plots (PCPs) can be a significant challenge for students. We adopted the Revised Bloom…
An Image-based Typology for Visualization
Jian Chen, Petra Isenberg, Robert S. Laramee +4
We present and discuss the results of a qualitative analysis of visualization images to derive an image-based typology of visualizations. For each image, we seek to identify its ma…
Challenges and Opportunities in Data Visualization Education: A Call to Action
Benjamin Bach, Mandy Keck, Fateme Rajabiyazdi +18
This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we nee…
Not As Easy As You Think -- Experiences and Lessons Learnt from Trying to Create a Bottom-Up Visualization Image Typology
Jian Chen, Petra Isenberg, Robert S. Laramee +4
We present and discuss the results of a two-year qualitative analysis of images published in IEEE Visualization (VIS) papers. Specifically, we derive a typology of 13 visualization…
Characterizing Grounded Theory Approaches in Visualization
Alexandra Diehl, Alfie Abdul-Rahman, Benjamin Bach +5
Grounded theory (GT) is a research methodology that entails a systematic workflow for theory generation grounded on emergent data. In this paper, we juxtapose GT workflows with typ…
Visualization for Epidemiological Modelling: Challenges, Solutions, Reflections & Recommendations
Jason Dykes, Alfie Abdul-Rahman, Daniel Archambault +30
We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs -- a series of ideas,…
Visualization Resources: A Starting Point
Xiaoxiao Liu, Mohammad Alharbi, Joe Best +6
Visualization, as a vibrant field for researchers, practitioners, and higher educational institutions, is growing and evolving very rapidly. Tremendous progress has been made since…
Document Domain Randomization for Deep Learning Document Layout Extraction
Meng Ling, Jian Chen, Torsten Möller +7
We present document domain randomization (DDR), the first successful transfer of convolutional neural networks (CNNs) trained only on graphically rendered pseudo-paper pages to rea…
VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications
Jian Chen, Meng Ling, Rui Li +8
We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis…
RAMPVIS: Towards a New Methodology for Developing Visualisation Capabilities for Large-scale Emergency Responses
M. Chen, A. Abdul-Rahman, D. Archambault +18
The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, an…
Studying Visualization Guidelines According to Grounded Theory
Alexandra Diehl, Matthias Kraus, Alfie Abdul-Rahman +5
Visualization guidelines, if defined properly, are invaluable to both practical applications and the theoretical foundation of visualization. In this paper, we present a collection…
Joint Contour Net Analysis for Feature Detection in Lattice Quantum Chromodynamics Data
Dean P. Thomas, Rita Borgo, Robert S. Laramee +1
In this paper we demonstrate the use of multivariate topological algorithms to analyse and interpret Lattice Quantum Chromodynamics (QCD) data. Lattice QCD is a long established fi…
QCDVis: a tool for the visualisation of Quantum Chromodynamics (QCD) Data
Dean P. Thomas, Rita Borgo, Robert S. Laramee +1
Quantum chromodynamics, most commonly referred to as QCD, is a relativistic quantum field theory for the strong interaction between subatomic particles called quarks and gluons. Th…
Glyph Sorting: Interactive Visualization for Multi-dimensional Data
David H. S. Chung, Philip A. Legg, Matthew L. Parry +4
Glyph-based visualization is an effective tool for depicting multivariate information. Since sorting is one of the most common analytical tasks performed on individual attributes o…