  Data visualizations are created and shared on the web at an unprecedented
speed, raising new needs and questions for processing and analyzing
visualizations after they have been generated and digitized. However, existing
formalisms focus on operating on a single visualization instead of multiple
visualizations, making it challenging to perform analysis tasks such as sorting
and clustering visualizations. Through a systematic analysis of previous work,
we abstract visualization-related tasks into mathematical operators such as
union and propose a design space of visualization operations. We realize the
design by developing ComputableViz, a library that supports operations on
multiple visualization specifications. To demonstrate its usefulness and
extensibility, we present multiple usage scenarios concerning processing and
analyzing visualization, such as generating visualization embeddings and
automatically making visualizations accessible. We conclude by discussing
research opportunities and challenges for managing and exploiting the massive
visualizations on the web.
