  We present a search engine for D3 visualizations that allows queries based on
their visual style and underlying structure. To build the engine we crawl a
collection of 7860 D3 visualizations from the Web and deconstruct each one to
recover its data, its data-encoding marks and the encodings describing how the
data is mapped to visual attributes of the marks. We also extract axes and
other non-data-encoding attributes of marks (e.g., typeface, background color).
Our search engine indexes this style and structure information as well as
metadata about the webpage containing the chart. We show how visualization
developers can search the collection to find visualizations that exhibit
specific design characteristics and thereby explore the space of possible
designs. We also demonstrate how researchers can use the search engine to
identify commonly used visual design patterns and we perform such a demographic
design analysis across our collection of D3 charts. A user study reveals that
visualization developers found our style and structure based search engine to
be significantly more useful and satisfying for finding different designs of D3
charts, than a baseline search engine that only allows keyword search over the
webpage containing a chart.
