Investigating whether people identify how suitable a data visualization is for answering specific analysis questions

Resumo


Choosing the type of chart to represent data can go beyond the combination of data type and analysis task. Various books and websites provide catalogs of data visualizations to help choose the correct chart for certain situations. However, they often do not consider the analyst's goal, as expressed by certain analysis questions. In this work, we studied how participants assess the suitability of certain data visualizations for answering specific analysis questions before and after being exposed to related guides that mimic what is often found in those catalogs. We also investigated whether they could assess suggestions (both textual and visual) to change the charts to better answer the analysis questions or recommend suitable alternative modifications to improve them. We discovered that, for basic charts, the participants could identify whether the visualization is suitable to answer an analysis question. However, when they find it unsuitable, they cannot always recommend changes to improve them. When presented with alternative visualizations, the participants seemed to provide assessments in line with the literature more often than when presented with textual descriptions of recommended changes, but the difference was not significant. Our results showed that guidelines, either in a textual or visual format, may not help novices effectively relate analysis questions to specific chart properties. The guidelines also failed to help novices improve charts to better answer specific questions. They can even confuse them and lead them to make mistakes they might not have made otherwise.
Palavras-chave: visualization literacy, data visualization, exploratory data analysis

Referências

Andrew Abela. 2008. Advanced presentations by design: creating communication that drives action. John Wiley & Sons, California.

Christopher Ahlberg. 1996. Spotfire: An Information Exploration Environment. SIGMOD Rec. 25, 4 (dec 1996), 25--29.

R. Amar, J. Eagan, and J. Stasko. 2005. Low-level components of analytic activity in information visualization. In IEEE Symposium on Information Visualization. IEEE, Minneapolis, 111--117.

Jacques Bertin. 1983. Semiology of graphics: diagrams, networks, maps. California, Esri Press.

Fatma Bouali, Abdelheq Guettala, and Gilles Venturini. 2016. VizAssist: an interactive user assistant for visual data mining. The Visual Computer 32, 11 (Nov. 2016), 1447--1463.

Lee J. Cronbach. 1951. Coefficient alpha and the internal structure of tests. Psychometrika 16, 3 (Sept. 1951), 297--334.

Raul de Araújo Lima and Simone Diniz Junqueira Barbosa. 2020. A question-oriented visualization recommendation approach for data exploration. In Proceedings of the International Conference on Advanced Visual Interfaces. Association for Computing Machinery, New York, 1--5.

Taissa Abdalla Filgueiras de Sousa and Simone Diniz Junqueira Barbosa. 2014. Recommender system to support chart constructions with statistical data. In Human-Computer Interaction. Theories, Methods, and Tools. Springer International Publishing, Edinburgh, 631--642.

Sakunthala Gnanamgari. 1981. Information presentation through default displays. PhD dissertation. The Wharton School, University of Pennsylvania.

David Gotz and Zhen Wen. 2009. Behavior-Driven Visualization Recommendation. In Proceedings of the 14th International Conference on Intelligent User Interfaces. Association for Computing Machinery, Sanibel Island Florida USA, 315--324.

David Gotz, Zhen When, Jie Lu, Peter Kissa, Nan Cao, Wei Hong Qian, Shi Xia Liu, and Michelle X Zhou. 2010. HARVEST: an intelligent visual analytic tool for the masses. In Proceedings of the first international workshop on Intelligent visual interfaces for text analysis. Association for Computing Machinery, Association for Computing Machinery, Hong Kong China, 1--4.

Pat Hanrahan. 2006. VizQL: A Language for Query, Analysis and Visualization. In Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data. Association for Computing Machinery, Chicago, 721.

Jeffrey Heer and Michael Bostock. 2010. Crowdsourcing graphical perception: using mechanical turk to assess visualization design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 203--212.

Tanja Keller, Peter Gerjets, Katharina Scheiter, and Bärbel Garsoffky. 2006. Information visualizations for knowledge acquisition: the impact of dimensionality and color coding. Computers in Human Behavior 22, 1 (2006), 43--65.

Alicia Key, Bill Howe, Daniel Perry, and Cecilia Aragon. 2012. VizDeck: self-organizing dashboards for visual analytics. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data (Scottsdale, Arizona, USA). Association for Computing Machinery, Scottsdale, 681--684.

Younghoon Kim and Jeffrey Heer. 2018. Assessing effects of task and data distribution on the Eeffectiveness of visual encodings. Computer Graphics Forum 37, 3 (2018), 157--167.

S. Lee, S. Kim, and B. C. Kwon. 2017. VLAT: Development of a visualization literacy assessment test. IEEE Transactions on Visualization and Computer Graphics 23, 1 (Jan. 2017), 551--560.

Shixia Liu, Weiwei Cui, Yingcai Wu, and Mengchen Liu. 2014. A survey on information visualization: recent advances and challenges. The Visual Computer 30, 12 (2014), 1373--1393.

Jock Mackinlay, Pat Hanrahan, and Chris Stolte. 2007. Show me: automatic presentation for visual analysis. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1137--1144.

Tamara Munzner. 2009. A nested model for visualization design and validation. IEEE Transactions on Visualization and Computer Graphics 15, 6 (2009), 921--928.

Fernanda C Ribeiro, Luan Costa, Melise de Paula, and Jano Moreira de Souza. 2014. Uma proposta para classificação baseada em contexto para técnicas de visualização. In Proceedings of the 13th Brazilian Symposium on Human Factors in Computing Systems. Sociedade Brasileira de Computação, Sociedade Brasileira de Computação, Foz do Iguaçu, Brazil, 401--404.

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.

Bahador Saket, Alex Endert, and Çağatay Demiralp. 2019. Task-Based Effectiveness of Basic Visualizations. IEEE Transactions on Visualization and Computer Graphics 25, 7 (July 2019), 2505--2512.

Arvind Satyanarayan, Dominik Moritz, Kanit Wongsuphasawat, and Jeffrey Heer. 2017. Vega-lite: A grammar of interactive graphics. IEEE Transactions on Visualization and Computer Graphics 23, 1 (2017), 341--350.

Vidya Setlur, Sarah E. Battersby, Melanie Tory, Rich Gossweiler, and Angel X. Chang. 2016. Eviza: A Natural Language Interface for Visual Analysis. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology. Association for Computing Machinery, Tokyo, Japan, 365--377.

B. Shneiderman. 1996. The eyes have it: a task by data type taxonomy for information visualizations. In Proceedings 1996 IEEE Symposium on Visual Languages. IEEE, Maryland, 336--343.

Arjun Srinivasan, Steven M. Drucker, Alex Endert, and John Stasko. 2019. Augmenting Visualizations with Interactive Data Facts to Facilitate Interpretation and Communication. IEEE Transactions on Visualization and Computer Graphics 25, 1 (Jan 2019), 672--681.

Danielle Albers Szafir. 2018. Modeling color difference for visualization design. IEEE Transactions on Visualization and Computer Graphics 24, 1 (2018), 392--401.

Tableau. 2003. Tableau Software. http://www.tableausoftware.com/.

Dereck Toker, Cristina Conati, Giuseppe Carenini, and Mona Haraty. 2012. Towards adaptive information visualization: on the influence of user characteristics. In International Conference on User Modeling, Adaptation, and Personalization. Springer, Springer, Berlin, 274--285.

Edward R Tufte, Nora Hillman Goeler, and Richard Benson. 1990. Envisioning information. Vol. 126. Graphics press Cheshire, Cheshire.

Manasi Vartak, Silu Huang, Tarique Siddiqui, Samuel Madden, and Aditya Parameswaran. 2017. Towards Visualization Recommendation Systems. SIGMOD Rec. 45, 4 (may 2017), 34--39.

Fernanda B Viegas, Martin Wattenberg, Frank Van Ham, Jesse Kriss, and Matt McKeon. 2007. Manyeyes: a site for visualization at internet scale. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1121--1128.

Martin Voigt, Stefan Pietschmann, Lars Grammel, and Klaus Meißner. 2012. Context-aware recommendation of visualization components. In The Fourth International Conference on Information, Process, and Knowledge Management. Citeseer, IARIA XPS Press, Wilmington, DE, 101--109.

Kanit Wongsuphasawat, Dominik Moritz, Anushka Anand, Jock Mackinlay, Bill Howe, and Jeffrey Heer. 2016. Voyager: exploratory analysis via faceted browsing of visualization recommendations. IEEE Transactions on Visualization and Computer Graphics 22, 1 (2016), 649--658.

Michelle X Zhou and Steven K Feiner. 1998. Visual task characterization for automated visual discourse synthesis. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, 392--399.
Publicado
17/10/2022
Como Citar

Selecione um Formato
BUENO RODRIGUES, Ariane Moraes; BARBOSA, Gabriel Diniz Junqueira; LOPES, Hélio Côrtes Vieira; BARBOSA, Simone Diniz Junqueira. Investigating whether people identify how suitable a data visualization is for answering specific analysis questions. In: SIMPÓSIO BRASILEIRO SOBRE FATORES HUMANOS EM SISTEMAS COMPUTACIONAIS (IHC), 21. , 2022, Diamantina. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 .