DIG Lab at VIS 2026

November 5, 2026

Authors from Carnegie Mellon University's Data Interaction Group contributed to four papers at the 2026 IEEE: Visualization & Visual Analytics conference. IEEE VIS — the premier forum for advances in visualization and visual analytics — will be held November 9–13 in Boston. 

This year, the DIG Lab authors' vis work spans accessible data experiences, interactive visualization tools, and artificial intelligence (AI) agents. DIG is a research group within the CMU Human-Computer Interaction Institute. 

Two papers with HCII authors will be recognized with awards at VIS 2026. 

• Skeleton - The 2026 paper "Skeleton: Visual Authoring of Non-visual Data Experiences" received a Best Paper Award. The Skeleton team includes HCII authors Frank Elavsky (HCII PhD 2026), Associate Professor Patrick Carrington, Assistant Professor Dominik Moritz, and collaborators Chieri J Nnadozie and Lucas Nadolskis.  
• Vega-Lite - Moritz and collaborators Arvind Satyanarayan, Kanit Wongsuphasawat, and Jeffrey Heer will receive the 10-year InfoVis Test of Time Award for their InfoVis 2016 paper, "Vega-Lite: A Grammar of Interactive Graphics."

Congratulations to all of the authors. 

Read more at DIG Lab at VIS 2026, or see below for a list of DIG Lab papers and brief descriptions. 
 

🏆 VIS 2026 Best Paper
Skeleton: Visual Authoring of Non-visual Data Experiences 
Frank Elavsky, Chieri J Nnadozie, Lucas Nadolskis, Patrick Carrington, Dominik Moritz

We make three contributions: First, we introduce technical advancements for making the properties of accessible navigation structure visible and directly manipulable during authoring, grounded in two foundational pieces of infrastructure produced by our co-design work: an Inspector and Dimensions API. Second, building on these, we present Skeleton, a direct-manipulation authoring environment in which the properties of an accessible navigation structure are translated into visual representations authors can observe and manipulate. Third, we evaluate Skeleton through an in-situ study with 8 practitioners across visualization design, engineering, and research. Making navigation structure visible changed how practitioners engaged with accessible design: they reconsidered the architecture of their own visualizations, attended to a broader range of input modalities, and shifted from treating accessibility as a compliance task to treating it as a design problem. 
 

Point, Revise, Review: Grounded Agentic Analysis in Reactive Notebooks with marimo-lens 
Péter Ferenc Gyarmati, Trevor Manz, Dominik Moritz, Mennatallah El-Assady  VISxGenAI at VIS 2026

In a computational notebook, a human can point to a rendered result and ask about "this," while an agent acts through cells, dependencies, and runtime state. When what the human sees and what the agent operates on are disconnected, the human must describe what they mean and trace what the agent did in prose that strips away situated visual and computational context. We present marimo-lens, an extension to the reactive Python notebook marimo for grounded human-agent analysis. 

Toward Softerware: Enabling Personalization of Interactive Data Representations for Users With Disabilities 
Frank Elavsky, Marita Vindedal, Ted Gies, Patrick Carrington, Dominik Moritz, Øystein Moseng  IEEE Computer Graphics and Applications 2026

Accessible design for some may still produce barriers for others. This tension, called access friction, creates challenges for both designers and end-users with disabilities. To address this, we present the concept of softerware, a system design approach that provides end users with agency to meaningfully customize and adapt interfaces to their needs. To apply softerware to visualization, we assembled 195 data visualization customization options centered on the barriers we expect users with disabilities will experience... We observed access frictions between our participant's designs and they expressed that for softerware's success, current and future systems must be designed with accessible defaults, interoperability, persistence, and respect for a user's perceived effort-to-outcome ratio. 

VACP: Visual Analytics Context Protocol 
Tobias Stähle, Péter Ferenc Gyarmati, Thilo Spinner, Rita Sevastjanova, Dominik Moritz, Mennatallah El-Assady  VIS 2026

The rise of AI agents introduces a fundamental shift in Visual Analytics (VA), in which agents act as a new user group. Current agentic approaches - based on computer vision and raw DOM access - fail to perform VA tasks accurately and efficiently. This paper introduces the Visual Analytics Context Protocol (VACP), a framework designed to make VA applications "agent-ready" that extends generic protocols by explicitly exposing application state, available interactions, and mechanisms for direct execution... VACP closes the gap between human-centric VA interfaces and machine perceivability, ensuring agents can reliably act as collaborative users in VA systems.