Finding visualizations with desired patterns is a common goal during data exploration. However, due to the limited expressiveness and flexibility of existing visual analytics systems, pattern-based querying of visualizations has largely been a manual process. We demonstrate ShapeSearch. a system that enables users to express their desired patterns in trend lines using multiple flexible mechanisms — including natural language and visual regular expressions, and automates the search via an optimized execution engine. Internally, the system leverages an expressive shape query algebra that supports a range of operators and primitives for representing ShapeSearch queries. In our demonstration, conference attendees will learn how the various components of ShapeSearch help accelerate scientific discovery by automating the search for meaningful patterns in trend lines in domains such as genomics and material science.
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