Validation of a heuristic set to evaluate the accessibility of statistical charts

Fecha de publicación

2024-06-18T11:23:00Z

2024-06-18T11:23:00Z

2022-09

Resumen

A remote user test was performed with two versions (one accessible and another one non-accessible) of three types of web-based charts (horizontal bar chart, vertical stacked bar chart, and line chart). The objectives of the test were a) to validate a set of heuristic indicators for the evaluation of the accessibility of statistical charts presented in a previous work 7; b) to identify new barriers and preferences for users with low vision in the access and use of this content not previously contemplated. 12 users were tested, with a variety of conditions associated with low vision: low visual acuity (6 users), reduced central vision (2 users), reduced peripheral vision (2 users), blurry vision (1 user), sensitivity to light (3 users), Nystagmus (2 users) and color vision deficiency (CVD) (4 users). From a quantitative standpoint, accessible versions of charts were more efficient, effective, and satisfactory. From a qualitative point of view, results verify the relevance of heuristics H2, Legend; H3, Axes; H6, Data source (as data table); H10, Safe colors; H11, Contrast; H12, Legibility; H13, Image quality; H14, Resize; H16, Focus visible; H17, Independent navigation; related to the proposed tasks. As new observations, tooltips were highly valued by all users, but their implementation must be improved to avoid covering up significant parts of the charts when displayed. The data table has also been frequently used by all users, especially in the non-accessible versions, allowing them to carry out tasks more efficiently. The position and size of the legend can be a significant barrier if it is too small or appears in an unusual position. Finally, despite the limitations related to color perception, users prefer color graphics to black and white, so, to target all profiles, it is necessary to redundantly encode categories with colors and patterns as well.

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Association for Computing Machinery

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versió postprint del document publicat a: https://doi.org/10.1145/3549865.3549893

Comunicació / Presentació a: Interacción '22: Proceedings of the XXII International Conference on Human Computer InteractionSeptember 2022, num. 2, pp. 1–9

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(c) ACM, 2022

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