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An ontology-based framework for improving color vision deficiency accessibility

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Abstract

Web technologies provide resources for the intensive use of colors in web pages. They are a core element in the design of interactive interfaces and are essential in the perception and understanding of information. However, color intensive design on the web affects the accessibility for users with color vision deficiency (CVD), who face difficulties in recognizing or distinguishing colors. CVD users may experience limitations and barriers in exploring web pages, even for simple tasks. Interface adaptation techniques may deal with several CVD visualization issues. Nevertheless, different situations and individual preferences turn choosing the most suitable recoloring technique into a complex task. Existing proposals in the literature fail in not considering various pathology types and individual preferences. This article defines a framework and techniques for the development of adaptive interfaces that facilitate the interaction of CVD people with web systems. The proposed research develops the FAIBOUD framework, which uses ontologies as artifacts for representing knowledge about CVD types, recoloring algorithms, and users’ access contexts and preferences. The FAIBOUD includes algorithms to support an adaptation decision process, which selects the most suited adaptation technique according to CVD type and access context. Our solution allows for the determination and automatic application of the best recoloring techniques to adapt interfaces for CVD users. Our experimental evaluation was conducted with fifteen CVD users. The results obtained from several illustrative scenarios demonstrate the benefits and enhancement of web interface accessibility based on our adaptive approach.

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Notes

  1. https://www.w3.org/TR/WCAG20/.

  2. https://www.w3.org/OWL/.

  3. https://www.w3.org/Submission/SWRL/.

  4. https://www.w3.org/TR/WCAG20-TECHS/.

  5. This situation was specified based on our previous user studies [9], which showed that [24] was the most suitable technique for this situation among the studied automatic recoloring techniques.

  6. https://github.com/ricardoaraujobe/faiboud.git.

  7. http://pellet.owldl.com/.

  8. https://www.w3.org/TR/UNDER STAND ING-WCAG20/visual-audio -contr ast-contrast.html.

  9. Participants have signed a consent form and were duly informed about this research, the involved procedures, as well as the possible risks and benefits arising from their participation. This online procedure was approved by the Unifaccamp post-graduation board (07032017).

  10. Translation made by the authors from the original response in Brazilian Portuguese.

  11. https://www.who.int/classifications/icf/en/.

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Authors and Affiliations

  1. Center for Information Technology Renato Archer and UNIFACCAMP, Rodovia Dom Pedro I, km 143, 6, Campinas, SP, 13069901, Brazil

    Rodrigo Bonacin

  2. Institute of Computing, University of Campinas, Av. Albert Einstein, 1251, Campinas, SP, 13083852, Brazil

    Julio Cesar dos Reis

  3. Federal Institute of Education, Science and Technology of Sul de Minas (IFSULDEMINAS), Pouso Alegre, MG, 37550000, Brazil

    Ricardo José de Araujo

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  1. Rodrigo Bonacin
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Bonacin, R., Reis, J.C.d. & de Araujo, R.J. An ontology-based framework for improving color vision deficiency accessibility. Univ Access Inf Soc 21, 691–716 (2022). https://doi.org/10.1007/s10209-021-00791-6

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