Data Visualization for Use in Website Design

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Increasingly complicated data are being translated by organizations and individuals for consumption by the general public. As technologies have grown more advanced, visualizing data has become an increasingly popular means to convey complex data to decision-makers and the public. However, this work is assuming that the general public can accurately interpret these visualizations. Researchers have a responsibility to ensure their work, especially when translating complex ideas and relationships to the public, is interpreted correctly. To this end, the New York State Center for Rural Schools has sought assistance from us. We have attempted to ascertain the extent to which users of the NYSCRS website can accurately and quickly interpret the types of visualizations presented on the website. In an effort to better understand the effectiveness of these visualizations for website users, a survey was designed and implemented to better understand how users interpret school district-related data visualizations. Specifically, we sought to ascertain the differences in accuracy and latency when interpreting identical data visualized as scatterplots, bar graphs, line graphs, and in tabular formats. This was accomplished through asking survey respondents to correctly identify trends or relationships displayed in different data visualizations (tabular, line graph, bar chart, and scatterplot), multiple times. The amount of time taken to answer correctly was recorded, and then compared against the amount of time taken to correctly answer the same question using a different visualization. Once the survey data was collected, we used statistical techniques to analyze the results, specifically seeking to understand any existing relationships between the demographic identifiers of respondents and respondents’ ability to accurately and swiftly interpret data visualizations. Details concerning this analysis can be found in the following pages, and the surveys can be found in the Appendix of this paper. In summary, our results suggest that the NYSCRS website should focus on performance, financial, and demographic data. These were the types of data for which respondents expressed the most interest, and for which administrators indicated they use the most frequently. The website should also maximize the usage of the most effective forms of visualizations. Our results suggest the most effective forms of visualizations with respect to accuracy and latency are line graphs and tables of non-bivariate relationships. Scatterplots, if used, should be constructed thoughtfully and with clear, concise labeling in order to assist with users’ understanding of the data displayed. Finally, the ‘matrix’ visualizations currently displayed on the website should be reevaluated to determine whether the information displayed is too complex or redundant. This may assist users in more quickly and accurately garnering information from the visualization. Across all of these initiatives, design should pay attention to aesthetic. Our findings suggest that when users identify a visualization or tabular representation as aesthetically pleasing, they are, generally, more likely to answer those questions correctly. As outlined throughout this paper, our research was specific to the school district level data, and we recommend further research in ascertaining the effects of data visualization across and within visualization types.

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New York State Center for Rural Schools

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data visualization; design


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Attribution-NonCommercial-NoDerivatives 4.0 International



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