Reasonable abstractions: Semantics for dynamic data visualization. Cottam, J., A. & Lumsdaine, A. In VAST 2011 - IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings, pages 269-270, 2011.
Reasonable abstractions: Semantics for dynamic data visualization [link]Website  doi  abstract   bibtex   
Chi showed how to treat visualization programing models abstractly. This provided a firm theoretical basis for the data-state model of visualization. However, Chi's models did not look deeper into fine-grained program properties, such as execution semantics. We present conditionally deterministic and resource bounded semantics for the data flow model of visualization based on E-FRP. These semantics are used in the Stencil system to move between data state and data flow execution, build task-based parallelism, and build complex analysis chains for dynamic data. This initial work also shows promise for other complex operators, compilation techniques to enable efficient use of time and space, and mixing task and data parallelism. © 2011 IEEE.
@inproceedings{
 title = {Reasonable abstractions: Semantics for dynamic data visualization},
 type = {inproceedings},
 year = {2011},
 keywords = {Compilation techniques; Complex analysis; Data flo,Data flow analysis,Data transfer; Data visualization; Graphical user},
 pages = {269-270},
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 notes = {cited By 0; Conference of 2nd IEEE Conference on Visual Analytics Science and Technology 2011, VAST 2011 ; Conference Date: 23 October 2011 Through 28 October 2011; Conference Code:88078},
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 abstract = {Chi showed how to treat visualization programing models abstractly. This provided a firm theoretical basis for the data-state model of visualization. However, Chi's models did not look deeper into fine-grained program properties, such as execution semantics. We present conditionally deterministic and resource bounded semantics for the data flow model of visualization based on E-FRP. These semantics are used in the Stencil system to move between data state and data flow execution, build task-based parallelism, and build complex analysis chains for dynamic data. This initial work also shows promise for other complex operators, compilation techniques to enable efficient use of time and space, and mixing task and data parallelism. © 2011 IEEE.},
 bibtype = {inproceedings},
 author = {Cottam, J A and Lumsdaine, A},
 doi = {10.1109/VAST.2011.6102468},
 booktitle = {VAST 2011 - IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings}
}

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