"Hey Dashboard!": Supporting Voice, Text, and Pointing Modalities in Dashboard Onboarding using Large Language Models

Vaishali Dhanoa, Gabriela Molina León, Eve Hoggan, Eduard Gröller, Marc Streit, Niklas Elmqvist · 2026 · 1 citationsRead the paper

Visualization dashboards are regularly used for data exploration and analysis, but their complex interactions and interlinked views often require time-consuming onboarding sessions from dashboard authors. Preparing these onboarding materials is labor-intensive and requires manual updates when dashboards change. Recent advances in multimodal interaction powered by large language models (LLMs) provide ways to support self-guided onboarding. We present Diana (Dashboard Interactive Assistant for Navigation and Analysis), a multimodal dashboard assistant that helps users for navigation and guided analysis through chat, audio, and mouse-based interactions. Users can choose any interaction modality or a combination of them to onboard themselves on the dashboard. Each modality highlights relevant dashboard features to support user orientation. Unlike typical LLM systems that rely solely on text-based chat, Diana combines multiple modalities to provide explanations directly in the dashboard interface. We conducted a comparative qualitative user study to understand the use of different modalities for different types of onboarding tasks and their complexities.

1 idea Seedlabs derived from this research