HCMar 2

Towards Measuring Interactive Visualization Abilities: Connecting With Existing Literacies and Assessments

arXiv:2604.15320h-index: 16
Originality Synthesis-oriented
AI Analysis

This addresses a gap in visualization literacy assessment for researchers and practitioners, but it is incremental as it builds on prior work without presenting new empirical results.

The paper tackles the lack of formal methods to assess people's abilities to interact with data visualizations, proposing and comparing different approaches based on existing literacy concepts and assessments.

How do we assess people's abilities to interact with data visualizations? The current state-of-the-art visualization literacy tests -- such as VLAT and its derivatives -- only involve the use of static visualizations. Despite advances in investigating multiple visualization abilities, we do not yet have formal methods to assess the ability of a person to interact with a data visualization effectively. In this position paper, we discuss related literacy concepts and assessments to propose and compare different approaches for assessing the abilities that people leverage to use visualizations in interactive sensemaking tasks.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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