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arxiv: 2512.05310 · v3 · submitted 2025-12-04 · 💻 cs.HC

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Systematically Evaluating Equivalent Purpose for Digital Maps

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classification 💻 cs.HC
keywords mapsframeworkequivalentpurposeaccessibilitycriteriadigitalinformation
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Digital geographic maps remain largely inaccessible to blind and low-vision individuals (BLVIs), despite global legislation adopting the Web Content Accessibility Guidelines (WCAG). A critical gap exists in defining "equivalent purpose" for maps under WCAG Success Criterion 1.1.1, which requires that non-text content provide a text alternative that serves the "equivalent purpose". This paper proposes a systematic framework for evaluating map accessibility, called the Map Equivalent-Purpose Framework (MEP Framework), defining purpose through three items (Generalized, Spatial Information, and Spatial Relationships), and establishing 15 measurable criteria for equivalent information communication. Eight text map representations were evaluated against visual map baselines using the proposed MEP Framework. Results show that legacy methods such as tables and turn-by-turn directions fail to meet the MEP Framework criteria, while Audiom Maps, Multi User Domain (MUD) Maps, and Audio Descriptions meet the criteria. The evaluation highlights the necessity of holistic, systematic approaches to ensure non-visual maps convey all generalized spatial information and relationships present in visual maps. The MEP Framework provides a replicable methodology for comprehensively assessing digital map accessibility, clarifying WCAG's "equivalent purpose", and guiding compliant and usable map creation. Compliant maps will support BLVIs' participation in map-dependent professions and civic engagement.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. A Spatial Knowledge Acquisition Comparison Between Digital Visual Thematic Maps, Non-Visual Interactive Text Thematic Maps, and Tables

    cs.HC 2026-05 unverdicted novelty 4.0

    Interactive text thematic maps enable spatial knowledge acquisition comparable to visual maps and superior to tables for both sighted and blind users.