Visualization Retrieval for Data Literacy: Position Paper

TL;DR

This paper advocates for visualization retrieval systems as vital tools in data literacy education, enabling dynamic exploration, comparison, and critique of visualizations to enhance learning and data understanding.

Contribution

It introduces the concept of visualization retrieval as essential infrastructure for data literacy, outlining opportunities for system design and future research.

Findings

Retrieval facilitates design space exploration and vocabulary expansion.

Supports data consumption through visualization comparison and critique.

Aids data management via resource curation.

Abstract

Current resources for data literacy education, such as visualization galleries and datasets, provide useful examples but lack mechanisms for learners to query, compare, and navigate the visualization design space efficiently. This position paper advocates for visualization retrieval as essential infrastructure for data literacy, transforming static collections into dynamic, inquiry-based learning environments. We analyze the role of retrieval across the data lifecycle, demonstrating how it facilitates design space exploration and vocabulary expansion, supports data consumption through visualization comparison and critique, and aids data management via resource curation. We outline key opportunities for future research and system design, including integrated retrieval-authoring environments, pedagogical relevance modeling, and collaborative educational corpora. Ultimately, we argue that visualization retrieval systems empower learners to articulate intent, bridge technical barriers, and proactively reason with data.