Accessible Bar Charts Through Textual Description Templates

Authors

DOI:

https://doi.org/10.5753/jbcs.2023.2301

Keywords:

Human-Computer Interaction, Charts Textual Description Templates, Accessibility

Abstract

Data charts are very prevalent in everyday life in different contexts, from economics to politics. However, people with blindness and low vision do not have easy access to this information since they use screen reader software. This software does not extract the information available graphically, but only the chart legend and the text. Among the solutions proposed in the literature, there are crowdsourcing techniques when a person is responsible for interpreting the chart, which can cause bias in the chart’s interpretation. To solve this problem, we proposed textual description templates for simple and grouped bar charts to inform the chart data in a standardized way to users, excluding the interpretation bias. The methodology of this work was divided into three stages: a definition of templates for textual description and testing with 30 participants; the application of textual description templates in an assistive technology tool and testing with 45 participants; the validation of the results found through interviews and tests with 3 specialists. We have iteratively refined templates generated at each stage with users tests, and we carried out quantitative and qualitative analyses. An assistive technology tool, ChartVision, was developed to consume the templates. Finally, we interviewed a specialist about how he would explain chart materials to blind students at university, and we carried out a validation of the final templates with two other professionals from the health and education areas who deal with people with blind people in their daily lives. The main contributions are three textual description bar charts templates: simple bar for applications with sequential reading or reading on-demand, grouped bar for applications with sequential reading, and grouped bar for applications on-demand. The secondary contribution is ChartVision. Other findings include considerations about the synthetic voice used in the tests, expected characteristics for a better understanding of the chart, and interaction ways to access the information.

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References

Awada, A., Issa, Y. B., Tekli, J., and Chbeir, R. (2013). Evaluation of touch screen vibration accessibility for blind users. In Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS '13, pages 48:1-48:2, New York, NY, USA. ACM. DOI: 10.1145/2513383.2513430.

Battle, L., Duan, P., Miranda, Z., Mukusheva, D., Chang, R., and Stonebraker, M. (2018). Beagle: Automated Extraction and Interpretation of Visualizations from the Web. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18, pages 1-8, New York, New York, USA. ACM Press. DOI: 10.1145/3173574.3174168.

Borges, J. A. (1996). Dosvox-um novo acesso dos cegos à cultura e ao trabalho. Benjamin Constant, (3).

Caldwell, B., Cooper, M., Reid, L. G., and Vanderheiden, G. (2008). Web content accessibility guidelines (wcag) 2.0. WWW Consortium (W3C).

Cardoso, C. and Clarkson, P. J. (2012). Simulation in user-centred design: helping designers to empathise with atypical users. Journal of Engineering Design, 23(1):1-22.

ChartVisionApp (2020). Chartvision github repository.

de Oliveira, C. L. T. (2020). Proposta e avaliação de modelos de descrição textual para vocalização de gráficos de barras. Master's thesis, Programa de Pós-Graduação em Ciência da Computação, ICEN, UFPA.

de Oliveira, C. L. T., de Almeida Silva, A. T., de Morais, J. M. a., and Mota, M. P. (2020). Chartvision: Accessible vertical bar charts. In Proceedings of the 19th Brazilian Symposium on Human Factors in Computing Systems, IHC '20, New York, NY, USA. Association for Computing Machinery. DOI: 10.1145/3424953.3426644.

de Oliveira, C. L. T., Silva, A. T. D. A., Campos, E. M., Araújo, T. D. O., Mota, M. P., Meiguins, B. S., and De Morais, J. M. (2019). Proposal and evaluation of textual description templates for bar charts vocalization. In 2019 23rd International Conference Information Visualisation (IV), pages 163-169. IEEE.

Demir, S., Carberry, S., and McCoy, K. F. (2008). Generating textual summaries of bar charts. In Proceedings of the Fifth International Natural Language Generation Conference, pages 7-15. Association for Computational Linguistics.

Demir, S., Oliver, D., Schwartz, E., Elzer, S., Carberry, S., Mccoy, K. F., and Chester, D. (2010). Interactive SIGHT: textual access to simple bar charts. New Review of Hypermedia and Multimedia, 16(3):245-279. DOI: 10.1080/13614568.2010.534186.

Etikan, I., Musa, S. A., and Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1):1-4.

Ferres, L., Lindgaard, G., and Sumegi, L. (2010). Evaluating a tool for improving accessibility to charts and graphs. In Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility - ASSETS '10, page 83, New York, New York, USA. ACM Press. DOI: 10.1145/1878803.1878820.

Goodman-Deane, J., Langdon, P. M., Clarkson, P. J., Caldwell, N. H., and Sarhan, A. M. (2007). Equipping designers by simulating the effects of visual and hearing impairments. In Proceedings of the 9th international ACM SIGACCESS conference on computers and accessibility, pages 241-242.

Goodman-Deane, J., Waller, S., Collins, A.-C., and Clarkson, P. J. (2013). Simulating vision loss. In Contemporary Ergonomics and Human Factors 2013, volume 347, pages 347-354. ROUTLEDGE in association with GSE Research, Cambridge, UK.

Gunnarsson, C., Hammenberg, J., Bornemalm, K., and Rassmus-Gröhn, K. (2018). Automation of audio descriptions of large bar charts for persons with visual impairment: Prototyping and proof of concept. Technology and Disability, 30(1-2):53-62. DOI: 10.3233/TAD-170181.

IBGE, C. (2010). Censo demográfico. Available online [link]. Accessed on 12 November 2019.

Kamel, H. M. and Landay, J. A. (2002). Sketching images eyes-free: A grid-based dynamic drawing tool for the blind. In Proceedings of the Fifth International ACM Conference on Assistive Technologies, Assets '02, pages 33-40, New York, NY, USA. ACM. DOI: 10.1145/638249.638258.

Lai, C., Lin, Z., Jiang, R., Han, Y., Liu, C., and Yuan, X. (2020). Automatic annotation synchronizing with textual description for visualization. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pages 1-13.

Monet (2019). Instituto benjamin constant lança o programa monet - gerador de gráficos táteis. Available online [link]. Accessed on 14 November 2019.

Morash, V. S., Siu, Y.-T., Miele, J. A., Hasty, L., and Landau, S. (2015). Guiding Novice Web Workers in Making Image Descriptions Using Templates. ACM Transactions on Accessible Computing, 7(4):1-21. DOI: 10.1145/2764916.

Pascolini, D. and Mariotti, S. P. (2012). Global estimates of visual impairment: 2010. British Journal of Ophthalmology, 96(5):614-618.

Pires, D., Furtado, B., Carregã, T., Reis, L., Pereira, L. L., Craveirinha, R., and Roque, L. (2013). The blindfold soundscape game: A case for participation-centered gameplay experience design and evaluation. In Proceedings of the 8th Audio Mostly Conference, AM '13, pages 9:1-9:7, New York, NY, USA. ACM. DOI: 10.1145/2544114.2544122.

Potter, J. and Edwards, D. (1996). Discourse analysis. In Introducing psychological research, pages 419-425. Springer, London, UK.

Scientific, F. (2011). Jaws for windows. Available online [link].

Silva, A. T. d. A. (2019). ChartVision: Gráficos de Barras Verticais Acessíveis. Monografia (Engenheiro e, Engenharia da Computação), UFPA (Universidade Federal do Pará), Belém, Brasil.

Statcounter (2020). Mobile operating system market share united states of america. Available at: https://gs.statcounter.com/os-market-share/mobile/united-states-of-america. Accessed on 30 June 2020.

Stephanidis, C. (2009). The universal access handbook. CRC, Press.

Wallgren, A., Wallgren, B., Persson, R., Jorner, U., and Haaland, J.-A. (1996). Graphing statistics & data: Creating better charts. Sage, Sage.

WHO (2012). Global data on visual impairments 2010. Geneva: World Health Organization.

Yang, H., Li, Y., and Zhou, M. X. (2014). Understand users' comprehension and preferences for composing information visualizations. ACM Transactions on Computer-Human Interaction, 21(1):1-30. DOI: 10.1145/2541288.

Zagar, M. and Baggarly, S. (2010). Low vision simulator goggles in pharmacy education. American journal of pharmaceutical education, 74(5):83.

Zimmerman (2019). Zimmerman low vision simulation kit. Available online [link]. Accessed on 05 November 2019.

Zou, H. (2015). Making Stock Market Charts Accessible through Provision of Textual Information in a Common Interface. PhD thesis, OCAD University.

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Published

2023-02-09

How to Cite

Oliveira, C. L. T. de, Silva, A. T. de A., Morais, J. M. de, & Mota, M. P. (2023). Accessible Bar Charts Through Textual Description Templates. Journal of the Brazilian Computer Society, 29(1), 1–18. https://doi.org/10.5753/jbcs.2023.2301

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Articles