Guidelines for Information Visualization Design: Extending the Plain Language
Abstract
Citizen Language is a technique that seeks to improve the understanding of texts through a set of practices. However, there are no specific guidelines to improve understanding of data. We publish here a proposal to complement the practices of Citizen Language with specific elements for this purpose. A set of guidelines selected with the methodological rigor of a literature review in the area of information visualization. The objective is to support the non-specialist developer in the production of more efficient views, whether for reports or public portals of published data and thus contributing to the citizen's understanding.
Keywords:
Plain Language, Information Visualization, Understandability
References
Barcellos, R. Avaliação da Qualidade e Interpretabilidade de Visualizações de Dados. (Dissertação de Mestrado, Universidade Federal Fluminense) Niterói, 2017. 87 p.
Brasil. (2011) Lei nº 12.527 – Lei de acesso à informação. Disponível em: <http://www.planalto.gov.br/ccivil_03/_ato2011-2014/2011/lei/l12527.htm> Acesso em 01 de junho de 2021.
Song, C., & Lee, J. (2016). Citizens’ use of social media in government, perceived transparency, and trust in government. Public Performance & Management Review, 39(2), 430-453.
Cappelli, C. Uma Abordagem para Transparência em Processos Organizacionais Utilizando Aspectos. Tese de Doutorado, PUC-Rio, Rio de Janeiro, Brasil, 2009.
Card, S. K.; Moran, T. P.; Newell, A. The Psychology of Human-Computer Interaction. Lawrence Erlbaum Associates, New Jersey, 1983.
Plain Language Association International. What is plain language? 2021. Disponível em: <https://plainlanguagenetwork.org/plain-language/what-is-plain-language/> Acesso em 15 de maio de 2021.
Barboza, E. M. F. (2010). A linguagem clara em conteúdos de websites governamentais para promover a acessibilidade a cidadãos com baixo nível de escolaridade. Inc. Soc., Brasília, DF, v. 4 n. 1, p.52-66, jul./dez. 2010.
Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings 1996 IEEE symposium on visual languages (pp. 336-343). IEEE.
Fischer, H., Mont'Alvão, C., & dos Santos Rodrigues, E. (2019). O Papel do Texto na Compreensibilidade de E-serviços. Ergodesign & HCI, 7(Especial), 207-219.
Barboza, E. M. F. (2010). A linguagem clara em conteúdos de websites governamentais para promover a acessibilidade a cidadãos com baixo nível de escolaridade. Inc. Soc., Brasília, DF, v. 4 n. 1, p.52-66, jul./dez. 2010
Munzner, Tamara. Visualization analysis and design. CRC press, 2014.
Park, S., & Gil-Garcia, J. R. (2017). Understanding transparency and accountability in open government ecosystems: The case of health data visualizations in a state government. In Proceedings of the 18th Annual International Conference on Digital Government Research (pp. 39-47).
Engelke, U., Abdul-Rahman, A., & Chen, M. (2018). VISupply: A Supply-Chain Process Model for Visualization Guidelines. In 2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA) (pp. 1-9). IEEE.
Passera, S. (2012). Enhancing contract usability and user experience through visualization-an experimental evaluation. In 2012 16th International Conference on Information Visualisation (pp. 376-382). IEEE.
Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004), 1-26.
Lee, N., & Rojas, E. M. (2009). Developing effective visual representations to monitor project performance. In Construction Research Congress 2009: Building a Sustainable Future (pp. 826-835).
Isett, K. R., & Hicks, D. M. (2018). Providing public servants what they need: Revealing the “unseen” through data visualization. Public Administration Review, 78(3), 479-485.
Senay, H., & Ignatius, E. (1990). Rules and principles of scientific data visualization. Institute for Information Science and Technology, Department of Electrical Engineering and Computer Science, School of Engineering and Applied Science, George Washington University.
Kelleher, C., & Wagener, T. (2011). Ten guidelines for effective data visualization in scientific publications. Environmental Modelling & Software, 26(6), 822-827.
Rheingans, P. L. (2000). Task-based color scale design. In 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making (Vol. 3905, pp. 35-43). International Society for Optics and Photonics.
Siirtola, H. (2019). The cost of pie charts. In 2019 23rd International Conference Information Visualisation (IV) (pp. 151-156). IEEE.
Grainger, S., Mao, F., & Buytaert, W. (2016). Environmental data visualisation for non-scientific contexts: Literature review and design framework. Environmental Modelling & Software, 85, 299-318.
Kopp, T., Riekert, M., & Utz, S. (2018). When cognitive fit outweighs cognitive load: Redundant data labels in charts increase accuracy and speed of information extraction. Computers in Human Behavior, 86, 367-376.
Gramazio, C. C., Schloss, K. B., & Laidlaw, D. H. (2014). The relation between visualization size, grouping, and user performance. IEEE transactions on visualization and computer graphics, 20(12), 1953-1962.
Rees, D., & Laramee, R. S. (2019). A survey of information visualization books. In Computer Graphics Forum (Vol. 38, No. 1, pp. 610-646).
Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals. John Wiley & Sons.
Wilke, C. O. (2019). Fundamentals of data visualization: a primer on making informative and compelling figures. O'Reilly Media.
Brasil. (2011) Lei nº 12.527 – Lei de acesso à informação. Disponível em: <http://www.planalto.gov.br/ccivil_03/_ato2011-2014/2011/lei/l12527.htm> Acesso em 01 de junho de 2021.
Song, C., & Lee, J. (2016). Citizens’ use of social media in government, perceived transparency, and trust in government. Public Performance & Management Review, 39(2), 430-453.
Cappelli, C. Uma Abordagem para Transparência em Processos Organizacionais Utilizando Aspectos. Tese de Doutorado, PUC-Rio, Rio de Janeiro, Brasil, 2009.
Card, S. K.; Moran, T. P.; Newell, A. The Psychology of Human-Computer Interaction. Lawrence Erlbaum Associates, New Jersey, 1983.
Plain Language Association International. What is plain language? 2021. Disponível em: <https://plainlanguagenetwork.org/plain-language/what-is-plain-language/> Acesso em 15 de maio de 2021.
Barboza, E. M. F. (2010). A linguagem clara em conteúdos de websites governamentais para promover a acessibilidade a cidadãos com baixo nível de escolaridade. Inc. Soc., Brasília, DF, v. 4 n. 1, p.52-66, jul./dez. 2010.
Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings 1996 IEEE symposium on visual languages (pp. 336-343). IEEE.
Fischer, H., Mont'Alvão, C., & dos Santos Rodrigues, E. (2019). O Papel do Texto na Compreensibilidade de E-serviços. Ergodesign & HCI, 7(Especial), 207-219.
Barboza, E. M. F. (2010). A linguagem clara em conteúdos de websites governamentais para promover a acessibilidade a cidadãos com baixo nível de escolaridade. Inc. Soc., Brasília, DF, v. 4 n. 1, p.52-66, jul./dez. 2010
Munzner, Tamara. Visualization analysis and design. CRC press, 2014.
Park, S., & Gil-Garcia, J. R. (2017). Understanding transparency and accountability in open government ecosystems: The case of health data visualizations in a state government. In Proceedings of the 18th Annual International Conference on Digital Government Research (pp. 39-47).
Engelke, U., Abdul-Rahman, A., & Chen, M. (2018). VISupply: A Supply-Chain Process Model for Visualization Guidelines. In 2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA) (pp. 1-9). IEEE.
Passera, S. (2012). Enhancing contract usability and user experience through visualization-an experimental evaluation. In 2012 16th International Conference on Information Visualisation (pp. 376-382). IEEE.
Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004), 1-26.
Lee, N., & Rojas, E. M. (2009). Developing effective visual representations to monitor project performance. In Construction Research Congress 2009: Building a Sustainable Future (pp. 826-835).
Isett, K. R., & Hicks, D. M. (2018). Providing public servants what they need: Revealing the “unseen” through data visualization. Public Administration Review, 78(3), 479-485.
Senay, H., & Ignatius, E. (1990). Rules and principles of scientific data visualization. Institute for Information Science and Technology, Department of Electrical Engineering and Computer Science, School of Engineering and Applied Science, George Washington University.
Kelleher, C., & Wagener, T. (2011). Ten guidelines for effective data visualization in scientific publications. Environmental Modelling & Software, 26(6), 822-827.
Rheingans, P. L. (2000). Task-based color scale design. In 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making (Vol. 3905, pp. 35-43). International Society for Optics and Photonics.
Siirtola, H. (2019). The cost of pie charts. In 2019 23rd International Conference Information Visualisation (IV) (pp. 151-156). IEEE.
Grainger, S., Mao, F., & Buytaert, W. (2016). Environmental data visualisation for non-scientific contexts: Literature review and design framework. Environmental Modelling & Software, 85, 299-318.
Kopp, T., Riekert, M., & Utz, S. (2018). When cognitive fit outweighs cognitive load: Redundant data labels in charts increase accuracy and speed of information extraction. Computers in Human Behavior, 86, 367-376.
Gramazio, C. C., Schloss, K. B., & Laidlaw, D. H. (2014). The relation between visualization size, grouping, and user performance. IEEE transactions on visualization and computer graphics, 20(12), 1953-1962.
Rees, D., & Laramee, R. S. (2019). A survey of information visualization books. In Computer Graphics Forum (Vol. 38, No. 1, pp. 610-646).
Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business professionals. John Wiley & Sons.
Wilke, C. O. (2019). Fundamentals of data visualization: a primer on making informative and compelling figures. O'Reilly Media.
Published
2021-07-18
How to Cite
OLIVEIRA, Rodrigo; CAPPELLI, Claudia; OLIVEIRA, Jonice.
Guidelines for Information Visualization Design: Extending the Plain Language. In: LATIN AMERICAN SYMPOSIUM ON DIGITAL GOVERNMENT (LASDIGOV), 9. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 259-266.
ISSN 2763-8723.
DOI: https://doi.org/10.5753/wcge.2021.15994.
