Declarative Visualization Queries

In an ideal interaction with machines, scientists may prefer to write declarative queries saying "what" they want from a machine than to write code stating "how" the machine is going to address the user request. For example, in relational database, users have long relied on specifying queries using Structured Query Language (SQL), a declarative language to request data results from a database management system. In the context of visualizations, we see that users are still writing code based on complex visualization toolkit APIs. With the goal of improving the scientists' experience of using visualization technology, we have applied this query-answering pattern to a visualization setting, where scientists specify what visualizations they want generated using a declarative SQL-like notation. A knowledge enhanced management system ingests the query and knows the following: (1) know how to translate the query into visualization pipelines; and (2) how to execute the visualization pipelines to generate the requested visualization. We define visualization queries as declarative requests for visualizations specified in an SQL like language. Visualization queries specify what category of visualization to generate (e.g., volumes, contours, surfaces) as well as associated display attributes (e.g., color and opacity), without any regards for implementation, thus allowing scientists to remain partially unaware of a wide range of visualization toolkit (e.g., Generic Mapping Tools and Visualization Toolkit) specific implementation details. Implementation details are only a concern for our knowledge-based visualization management system, which uses both the information specified in the query and knowledge about visualization toolkit functions to construct visualization pipelines. Knowledge about the use of visualization toolkits includes what data formats the toolkit operates on, what formats they output, and what views they can generate. Visualization knowledge, which is not necessarily entirely exposed to scientists writing visualization queries, facilitates the automated construction of visualization pipelines. VisKo queries have been successfully used in support of visualization scenarios from Earth Science domains including: velocity model isosurfaces, gravity data raster, and contour map renderings. Our synergistic environment provided by our CYBER-ShARE initiative at the University of Texas at El Paso has allowed us to work closely with Earth Science experts that have both provided us our test data as well as validation as to whether the execution of VisKo queries are returning visualizations that can be used for data analysis. Additionally, we have employed VisKo queries to support visualization scenarios associated with Giovanni, an online platform for data analysis developed by NASA GES DISC. VisKo-enhanced visualizations included time series plotting of aerosol data as well as contour and raster map generation of gridded brightness-temperature data.