A language for visualization variation and transformation

Improvements in computer technology have spawned an exponential growth in both the scope and volume of data collection, as well as a corresponding shortage of capable analysts. This applies not just to scientists, but also to consumers who are gaining unprecedented access to data from their cars, homes, phones, and other devices. Meanwhile, visualization has emerged as an effective tool for exploring and gathering insight from large quantities of data. However, constructing effective visualizations is often difficult, and current tools often lack either the flexibility to extend to custom problem domains or else require low-level graphics programming expertise to generate even simple visualizations. Furthermore, most solutions are ad hoc, preventing users from transforming and evolving visualizations, instead forcing them into a rigid, linear workflow. One possible approach to solving these problems is through the definition of a domain-specific language (DSL). This approach offers a number of potential advantages, the most immediate being flexibility. A visualization DSL could support multiple levels of abstraction at once, each of which could be targeted at different user needs and expertise levels. This, in turn, could allow users with varying levels of expertise to make use of the abstraction layers they find most appropriate, and support the creation of simple and common visualizations without sacrificing the option for more detailed control when necessary. This layering could also allow implementation details to be hidden when desired. Pixel position information, for example, could be hidden behind a scalable and unitless environment which would allow the user to place and size visualization components in relation to one another.