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CHI2023Top-tier venue

ChartDetective: Easy and Accurate Interactive Data Extraction from Complex Vector Charts

Damien Masson, Sylvain Malacria, Daniel Vogel, Edward Lank, Géry Casiez

2023Year
22Citations
11Top-tier citations

Abstract

Extracting underlying data from rasterized charts is tedious and inaccurate; values might be partially occluded or hard to distinguish, and the quality of the image limits the precision of the data being recovered. To address these issues, we introduce a semi-automatic system leveraging vector charts to extract the underlying data easily and accurately. The system is designed to make the most of vector information by relying on a drag-and-drop interface combined with selection, filtering, and previsualization features. A user study showed that participants spent less than 4 minutes to accurately recover data from charts published at CHI with diverse styles, thousands of data points, a combination of different encodings, and elements partially or completely occluded. Compared to other approaches relying on raster images, our tool successfully recovered all data, even when hidden, with a 78% lower relative error.

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