Investigating Difficulties and Decisions in Information Visualization Design
Resumo
Interpreting and creating data visualizations is an essential skill in the data-intensive age. Visualizations are a tool to extract and communicate information from data. However, people often need help in creating visualizations. Understanding the existing difficulties and investigating ways to improve data visualization design aims to empower novices’ data exploration. This research focuses on investigating the visualization design process to identify aspects to support novices in information visualization design and education. We performed an in-depth empirical study with five practitioners in the software industry but novices in data visualization. The participants selected visualizations to answer six analytical questions. The creation process was conducted by a researcher and recorded by video. In total, the participants created 63 visualizations. We analyzed the videos and extracted the steps followed in this process. Also, two visualization experts inspected the content participants had created and identified problems in selecting the visualization type and designing the visualization. As a result, we identified difficulties in selecting appropriate visualizations, mapping data into visual variables correctly, and some issues used as the basis for decisions during the design process.
Palavras-chave:
information visualization, design, teaching
Referências
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Alberto Cairo. 2016. The Truthful Art: Data, Charts, and Maps for Communication (1 edition ed.). New Riders, Place of publication not identified.
Stuart K. Card, Jock Mackinlay, and Ben Shneiderman. 1999. Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann. Google-Books-ID: wdh2gqWfQmgC
Damla Çay, Till Nagel, and Asım Evren Yantac. 2020. ColVis: collaborative visualization design workshops for diverse user groups. In 2020 24th International Conference Information Visualisation (IV). IEEE, 550–558.
Anamaria Crisan, Brittany Fiore-Gartland, and Melanie Tory. 2020. Passing the data baton: A retrospective analysis on data science work and workers. IEEE Transactions on Visualization and Computer Graphics 27, 2 (2020), 1860–1870.
Karin Eberhard. 2023. The effects of visualization on judgment and decisionmaking: a systematic literature review. Management Review Quarterly 73, 1 (2023), 167–214.
Elif E Firat, Alark Joshi, and Robert S Laramee. 2022. Interactive visualization literacy: The state-of-the-art. Information Visualization 21, 3 (2022), 285–310.
Steven L Franconeri, Lace M Padilla, Priti Shah, Jeffrey M Zacks, and Jessica Hullman. 2021. The science of visual data communication: What works. Psychological Science in the public interest 22, 3 (2021), 110–161.
Lily W Ge, Yuan Cui, and Matthew Kay. 2023. Calvi: Critical thinking assessment for literacy in visualizations. In Proceedings of the 2023 CHI conference on human factors in computing systems. 1–18.
Lily W Ge, Maryam Hedayati, Yuan Cui, Yiren Ding, Karen Bonilla, Alark Joshi, Alvitta Ottley, Benjamin Bach, Bum Chul Kwon, David N Rapp, et al. 2024. Toward a More Comprehensive Understanding of Visualization Literacy. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1–7.
Lars Grammel, Melanie Tory, and Margaret-Anne Storey. 2010. How information visualization novices construct visualizations. IEEE transactions on visualization and computer graphics 16, 6 (2010), 943–952.
Mandy Keck and Rainer Groh. 2019. A Construction Kit for Visual Exploration Interfaces.. In EuroVis (Short Papers). 79–83.
Mandy Keck, Rainer Groh, and Zana Vosough. 2020. A didactic methodology for crafting information visualizations. In 2020 IEEE Visualization Conference (VIS). IEEE, 186–190.
Sukwon Lee, Sung-Hee Kim, and Bum Chul Kwon. 2016. Vlat: Development of a visualization literacy assessment test. IEEE transactions on visualization and computer graphics 23, 1 (2016), 551–560.
Jock Mackinlay. 1986. Automating the design of graphical presentations of relational information. ACM Trans. Graph. 5, 2 (April 1986), 110–141. DOI: 10.1145/22949.22950
Adam V. Maltese, Joseph A. Harsh, and Dubravka Svetina. 2015. Data Visualization Literacy: Investigating Data Interpretation Along the Novice—Expert Continuum. Journal of College Science Teaching 45, 1 (2015), 84–90. [link] Publisher: National Science Teachers Association.
Seungeun Park, Betty Bekemeier, Abraham Flaxman, and Melinda Schultz. 2022. Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review. Informatics for Health and Social Care 47, 2 (2022), 175–193.
Paul Parsons. 2021. Understanding data visualization design practice. IEEE Transactions on Visualization and Computer Graphics 28, 1 (2021), 665–675.
Maryam Rezaie, Melanie Tory, and Sheelagh Carpendale. 2024. Struggles and Strategies in Understanding Information Visualizations. IEEE Transactions on Visualization and Computer Graphics 30, 6 (2024), 3035 – 3048.
Ariane Moraes Bueno Rodrigues, Gabriel Diniz Junqueira Barbosa, Hélio Côrtes Vieira Lopes, and Simone Diniz Junqueira Barbosa. 2021. What questions reveal about novices’ attempts to make sense of data visualizations: Patterns and misconceptions. Computers & Graphics 94 (2021), 32–42.
Christina Stoiber, Markus Wagner, Florian Grassinger, Margit Pohl, Holger Stitz, Marc Streit, Benjamin Potzmann, and Wolfgang Aigner. 2023. Visualization onboarding grounded in educational theories. In Visualization Psychology. Springer, 139–164.
Antony Unwin. 2020. Why is data visualization important? what is important in data visualization? Harvard Data Science Review 2, 1 (2020), 1.
Andrea Vázquez-Ingelmo, Alicia García-Holgado, Sonia Verdugo-Castro, Roberto Theron, and Francisco José García-Penalvo. 2024. Data visualization and domain knowledge: Insights through focus groups of researchers in Spain. Computers in Human Behavior 155 (2024), 108162.
Jeremy Boy, Ronald A. Rensink, Enrico Bertini, and Jean-Daniel Fekete. 2014. A Principled Way of Assessing Visualization Literacy. IEEE Transactions on Visualization and Computer Graphics 20, 12 (Dec. 2014), 1963–1972. DOI: 10.1109/TVCG.2014.2346984 Conference Name: IEEE Transactions on Visualization and Computer Graphics.
Alberto Cairo. 2016. The Truthful Art: Data, Charts, and Maps for Communication (1 edition ed.). New Riders, Place of publication not identified.
Stuart K. Card, Jock Mackinlay, and Ben Shneiderman. 1999. Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann. Google-Books-ID: wdh2gqWfQmgC
Damla Çay, Till Nagel, and Asım Evren Yantac. 2020. ColVis: collaborative visualization design workshops for diverse user groups. In 2020 24th International Conference Information Visualisation (IV). IEEE, 550–558.
Anamaria Crisan, Brittany Fiore-Gartland, and Melanie Tory. 2020. Passing the data baton: A retrospective analysis on data science work and workers. IEEE Transactions on Visualization and Computer Graphics 27, 2 (2020), 1860–1870.
Karin Eberhard. 2023. The effects of visualization on judgment and decisionmaking: a systematic literature review. Management Review Quarterly 73, 1 (2023), 167–214.
Elif E Firat, Alark Joshi, and Robert S Laramee. 2022. Interactive visualization literacy: The state-of-the-art. Information Visualization 21, 3 (2022), 285–310.
Steven L Franconeri, Lace M Padilla, Priti Shah, Jeffrey M Zacks, and Jessica Hullman. 2021. The science of visual data communication: What works. Psychological Science in the public interest 22, 3 (2021), 110–161.
Lily W Ge, Yuan Cui, and Matthew Kay. 2023. Calvi: Critical thinking assessment for literacy in visualizations. In Proceedings of the 2023 CHI conference on human factors in computing systems. 1–18.
Lily W Ge, Maryam Hedayati, Yuan Cui, Yiren Ding, Karen Bonilla, Alark Joshi, Alvitta Ottley, Benjamin Bach, Bum Chul Kwon, David N Rapp, et al. 2024. Toward a More Comprehensive Understanding of Visualization Literacy. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1–7.
Lars Grammel, Melanie Tory, and Margaret-Anne Storey. 2010. How information visualization novices construct visualizations. IEEE transactions on visualization and computer graphics 16, 6 (2010), 943–952.
Mandy Keck and Rainer Groh. 2019. A Construction Kit for Visual Exploration Interfaces.. In EuroVis (Short Papers). 79–83.
Mandy Keck, Rainer Groh, and Zana Vosough. 2020. A didactic methodology for crafting information visualizations. In 2020 IEEE Visualization Conference (VIS). IEEE, 186–190.
Sukwon Lee, Sung-Hee Kim, and Bum Chul Kwon. 2016. Vlat: Development of a visualization literacy assessment test. IEEE transactions on visualization and computer graphics 23, 1 (2016), 551–560.
Jock Mackinlay. 1986. Automating the design of graphical presentations of relational information. ACM Trans. Graph. 5, 2 (April 1986), 110–141. DOI: 10.1145/22949.22950
Adam V. Maltese, Joseph A. Harsh, and Dubravka Svetina. 2015. Data Visualization Literacy: Investigating Data Interpretation Along the Novice—Expert Continuum. Journal of College Science Teaching 45, 1 (2015), 84–90. [link] Publisher: National Science Teachers Association.
Seungeun Park, Betty Bekemeier, Abraham Flaxman, and Melinda Schultz. 2022. Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review. Informatics for Health and Social Care 47, 2 (2022), 175–193.
Paul Parsons. 2021. Understanding data visualization design practice. IEEE Transactions on Visualization and Computer Graphics 28, 1 (2021), 665–675.
Maryam Rezaie, Melanie Tory, and Sheelagh Carpendale. 2024. Struggles and Strategies in Understanding Information Visualizations. IEEE Transactions on Visualization and Computer Graphics 30, 6 (2024), 3035 – 3048.
Ariane Moraes Bueno Rodrigues, Gabriel Diniz Junqueira Barbosa, Hélio Côrtes Vieira Lopes, and Simone Diniz Junqueira Barbosa. 2021. What questions reveal about novices’ attempts to make sense of data visualizations: Patterns and misconceptions. Computers & Graphics 94 (2021), 32–42.
Christina Stoiber, Markus Wagner, Florian Grassinger, Margit Pohl, Holger Stitz, Marc Streit, Benjamin Potzmann, and Wolfgang Aigner. 2023. Visualization onboarding grounded in educational theories. In Visualization Psychology. Springer, 139–164.
Antony Unwin. 2020. Why is data visualization important? what is important in data visualization? Harvard Data Science Review 2, 1 (2020), 1.
Andrea Vázquez-Ingelmo, Alicia García-Holgado, Sonia Verdugo-Castro, Roberto Theron, and Francisco José García-Penalvo. 2024. Data visualization and domain knowledge: Insights through focus groups of researchers in Spain. Computers in Human Behavior 155 (2024), 108162.
Publicado
07/11/2024
Como Citar
FERREIRA, Bruna Moraes; RODRIGUES, Ariane Moraes Bueno; BARBOSA, Gabriel Diniz Junqueira; BARBOSA, Simone Diniz Junqueira.
Investigating Difficulties and Decisions in Information Visualization Design. In: SIMPÓSIO BRASILEIRO SOBRE FATORES HUMANOS EM SISTEMAS COMPUTACIONAIS (IHC), 23. , 2024, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 703-713.
