UBC Computer Science publishes 5 papers at world’s premier visualization conference
InfoVis group represents UBC Computer Science at leading forum for advances in visualization and visual analytics
Data is everywhere, from your healthcare information to your online consumer habits to your school records. Whether it’s through a graph, table or chart, conveying information visually is crucial for helping people understand data quickly and in an unbiased way.
To discuss the latest research in data visualization and analytics, UBC’s InfoVis Group, led by Professor Tamara Munzner, will join an international community of visualization researchers and practitioners in Vienna, Austria for the annual IEEE VIS (Visualization and Visual Analytics) conference from Nov 2-7, 2025. Researchers from the InfoVis Group have five papers accepted at the conference and associated workshops, which they will be presenting.
UBC Computer Science Ph.D. students Mara Solen and Matt Oddo developed a design space to help visualization designers and researchers present datasets with a large range in size. In their paper, A Design Space for Multiscale Visualization, the researchers tested their design space on 52 examples, outlining four strategies for multiscale visualization design.
Former UBC Computer Science postdoctoral fellow Dr. Charles Berret led a paper, Iceberg Sensemaking: A Process Model for Critical Data Analysis, which offers a new model for gathering and analyzing data to answer specific questions. Their three-phase process model uses an iceberg analogy, with data as the visible tip of the iceberg. The researchers validated the descriptive and prescriptive power of their model and discussed the interpretivist model of sensemaking, which focuses on subjective meaning and experiences.
In a position paper for the Input Vis workshop, UBC Computer Science Ph.D. student Ryan Smith argues that certain visual aspects of visualization such as the axes, ranges, labels and visualized data, influence what users perceive as appropriate, complete and accurate input. The paper, Potential Areas of Bias in Visualization-as-Input Systems, highlights the need for design strategies that promote more representative user data.
A study led by UBC Computer Science Ph.D. student Matt Oddo in collaboration with Stephen Kobourov from the Technical University of Munich, introduced a new algorithm for describing data with complex networks. In the paper, The Census-Stub Graph Invariant Descriptor, the researchers present new visualizations that capture meaningful structural features of networks, especially when using traditional visualization techniques would result in cluttered visuals that are hard to understand.
In a paper for the VisComm Workshop, Ph.D. student Mara Solen, in collaboration with researchers at the Washington University in St. Louis and UBC Computer Science lecturer Dr. Firas Moosvi, discusses how existing literature describe visualization literacy and its connection to textual literacy. In the paper, Visualization Literacy or Skillset? Beyond the Analogy to Textual Literacy, they propose a new and more flexible term “visualization skillset” to describe the spectrum of proficiency.
In addition to the papers, Dr. Munzner is a panelist in a discussion on IEEE VIS Reviewing and is presenting a tutorial on Visualization Analysis and Design, which is based on her book. She is co-editor of the AK Peters Visualization book series published by CRC/Routledge, which will have a physical table at the conference.