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• W2904287913 abstract "Many real-world datasets are incomplete due to factors such as data collection failures or misalignments between fused datasets. Visualizations of incomplete datasets should allow analysts to draw conclusions from their data while effectively reasoning about the quality of the data and resulting conclusions. We conducted a pair of crowdsourced studies to measure how the methods used to impute and visualize missing data may influence analysts' perceptions of data quality and their confidence in their conclusions. Our experiments used different design choices for line graphs and bar charts to estimate averages and trends in incomplete time series datasets. Our results provide preliminary guidance for visualization designers to consider when working with incomplete data in different domains and scenarios." @default.
• W2904287913 created "2018-12-22" @default.
• W2904287913 creator A5013335258 @default.
• W2904287913 creator A5056903170 @default.
• W2904287913 date "2019-01-01" @default.
• W2904287913 modified "2023-10-14" @default.
• W2904287913 title "Where's My Data? Evaluating Visualizations with Missing Data" @default.
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• W2904287913 doi "https://doi.org/10.1109/tvcg.2018.2864914" @default.
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